MarineTrafficAPI.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8a283189",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import json\n",
    "import urllib as u\n",
    "import datetime\n",
    "import os"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f84e5df",
   "metadata": {},
   "source": [
    "### Get data from Marinetime Traffic API"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "0f1cae9f",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "#create APL link \n",
    "domain='https://services.marinetraffic.com/api/portcalls/8521c2e6e2a9a70eded303bc092f4e2943dd2e64'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "6731c8e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'https://services.marinetraffic.com/api/portcalls/8521c2e6e2a9a70eded303bc092f4e2943dd2e64'"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "domain"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "7745b140",
   "metadata": {},
   "outputs": [],
   "source": [
    "qValue= {'v':'4','portid':'150','fromdate':'2020-01-01 00:00','todate':'2020-01-20 23:59','gt_min':'5000','protocol':'json','msgtype':'extended'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "319eb9ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'v=4&portid=150&fromdate=2019-01-21+00%3A00&todate=2019-01-31+23%3A59&gt_min=4000&protocol=json&msgtype=extended'"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qPrams = u.parse.urlencode(qValue)\n",
    "qPrams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "9c7dbedb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'https://services.marinetraffic.com/api/portcalls/8521c2e6e2a9a70eded303bc092f4e2943dd2e64?v=4&portid=150&fromdate=2019-01-21+00%3A00&todate=2019-01-31+23%3A59&gt_min=4000&protocol=json&msgtype=extended'"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "url = domain + '?' + qPrams\n",
    "url"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "35a6d82e",
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = [[\"232079000\",\"CITY OF ROME\",\"183675\",\"2019-01-04T21:51:00\",\"2019-01-04T21:51:00\",\"0\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"220449000\",\"KING SEAWAYS\",\"159262\",\"2019-01-04T17:05:00\",\"2019-01-04T17:05:00\",\"1\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"235089915\",\"VECTIS EAGLE\",\"198521\",\"2019-01-04T14:59:00\",\"2019-01-04T14:59:00\",\"1\",\"General Cargo\",\"150\",\"TYNE\",\"GBTYN\"],[\"353941000\",\"NORD PACIFIC\",\"5202902\",\"2019-01-04T13:24:00\",\"2019-01-04T13:24:00\",\"0\",\"Bulk Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"246824000\",\"FINNBORG\",\"272291\",\"2019-01-04T12:46:00\",\"2019-01-04T12:46:00\",\"1\",\"Cargo\\/Containership\",\"150\",\"TYNE\",\"GBTYN\"],[\"255805578\",\"BG ROTTERDAM\",\"300119\",\"2019-01-04T10:46:00\",\"2019-01-04T10:46:00\",\"0\",\"Container Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"220449000\",\"KING SEAWAYS\",\"159262\",\"2019-01-04T08:48:00\",\"2019-01-04T08:48:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"232215000\",\"SAND FALCON\",\"183875\",\"2019-01-03T19:30:00\",\"2019-01-03T19:30:00\",\"1\",\"Hopper Dredger\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-01-03T16:58:00\",\"2019-01-03T16:58:00\",\"1\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-01-03T08:43:00\",\"2019-01-03T08:43:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "9e5af2cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "df3 = [[\"563835000\",\"CITY OF OSLO\",\"727150\",\"2019-01-20T18:49:00\",\"2019-01-20T18:49:00\",\"1\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"370852000\",\"PLEIADES SPIRIT\",\"459493\",\"2019-01-20T11:21:00\",\"2019-01-20T11:21:00\",\"0\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"563835000\",\"CITY OF OSLO\",\"727150\",\"2019-01-20T06:13:00\",\"2019-01-20T06:13:00\",\"0\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"233234000\",\"CITY OF BARCELONA\",\"184903\",\"2019-01-19T20:58:00\",\"2019-01-19T20:58:00\",\"0\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-01-19T16:54:00\",\"2019-01-19T16:54:00\",\"1\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-01-19T08:49:00\",\"2019-01-19T08:49:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"212967000\",\"SHEILA\",\"3819695\",\"2019-01-19T08:08:00\",\"2019-01-19T08:08:00\",\"0\",\"Bulk Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"355922000\",\"GREEN GEM\",\"5748751\",\"2019-01-19T05:26:00\",\"2019-01-19T05:26:00\",\"1\",\"Bulk Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"210521000\",\"STEEN\",\"125002\",\"2019-01-18T21:36:00\",\"2019-01-18T21:36:00\",\"1\",\"Container Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"353083000\",\"CITY OF ST.PETERSBURG\",\"411554\",\"2019-01-18T19:39:00\",\"2019-01-18T19:39:00\",\"1\",\"Ro-Ro Cargo\",\"150\",\"TYNE\",\"GBTYN\"],[\"319392000\",\"IRIS ACE\",\"385690\",\"2019-01-18T17:40:00\",\"2019-01-18T17:40:00\",\"1\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"257392000\",\"BETTY KNUTSEN\",\"306511\",\"2019-01-18T17:17:00\",\"2019-01-18T17:17:00\",\"1\",\"Shuttle Tanker\",\"150\",\"TYNE\",\"GBTYN\"],[\"353083000\",\"CITY OF ST.PETERSBURG\",\"411554\",\"2019-01-17T23:49:00\",\"2019-01-17T23:49:00\",\"0\",\"Ro-Ro Cargo\",\"150\",\"TYNE\",\"GBTYN\"],[\"246733000\",\"BANDURA\",\"270897\",\"2019-01-17T20:22:00\",\"2019-01-17T20:22:00\",\"1\",\"General Cargo\",\"150\",\"TYNE\",\"GBTYN\"],[\"233150000\",\"CITY OF SUNDERLAND\",\"184852\",\"2019-01-17T17:18:00\",\"2019-01-17T17:18:00\",\"1\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-01-17T17:12:00\",\"2019-01-17T17:12:00\",\"1\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"257392000\",\"BETTY KNUTSEN\",\"306511\",\"2019-01-17T16:06:00\",\"2019-01-17T16:06:00\",\"0\",\"Shuttle Tanker\",\"150\",\"TYNE\",\"GBTYN\"],[\"319392000\",\"IRIS ACE\",\"385690\",\"2019-01-17T14:00:00\",\"2019-01-17T14:00:00\",\"0\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-01-17T08:56:00\",\"2019-01-17T08:56:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"246733000\",\"BANDURA\",\"270897\",\"2019-01-16T23:12:00\",\"2019-01-16T23:12:00\",\"0\",\"General Cargo\",\"150\",\"TYNE\",\"GBTYN\"],[\"233150000\",\"CITY OF SUNDERLAND\",\"184852\",\"2019-01-16T20:29:00\",\"2019-01-16T20:29:00\",\"0\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"210521000\",\"STEEN\",\"125002\",\"2019-01-16T17:28:00\",\"2019-01-16T17:28:00\",\"0\",\"Container Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"304972000\",\"ALDEBARAN J\",\"362839\",\"2019-01-16T05:04:00\",\"2019-01-16T05:04:00\",\"1\",\"Container Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"431339000\",\"PEGASUS ACE\",\"418270\",\"2019-01-16T03:52:00\",\"2019-01-16T03:52:00\",\"1\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"355922000\",\"GREEN GEM\",\"5748751\",\"2019-01-15T21:27:00\",\"2019-01-15T21:27:00\",\"0\",\"Bulk Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"215061000\",\"WILSON NANJING\",\"149099\",\"2019-01-15T20:06:00\",\"2019-01-15T20:06:00\",\"1\",\"General Cargo\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-01-15T17:14:00\",\"2019-01-15T17:14:00\",\"1\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"232079000\",\"CITY OF ROME\",\"183675\",\"2019-01-15T15:36:00\",\"2019-01-15T15:36:00\",\"1\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"304972000\",\"ALDEBARAN J\",\"362839\",\"2019-01-15T13:19:00\",\"2019-01-15T13:19:00\",\"0\",\"Container Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-01-15T08:47:00\",\"2019-01-15T08:47:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"215061000\",\"WILSON NANJING\",\"149099\",\"2019-01-14T23:51:00\",\"2019-01-14T23:51:00\",\"0\",\"General Cargo\",\"150\",\"TYNE\",\"GBTYN\"],[\"219617000\",\"EMMA BULKER\",\"409819\",\"2019-01-14T18:50:00\",\"2019-01-14T18:50:00\",\"1\",\"Bulk Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"258882000\",\"HOEGH TRADER\",\"312911\",\"2019-01-14T16:06:00\",\"2019-01-14T16:06:00\",\"1\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"232079000\",\"CITY OF ROME\",\"183675\",\"2019-01-14T08:03:00\",\"2019-01-14T08:03:00\",\"0\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"431339000\",\"PEGASUS ACE\",\"418270\",\"2019-01-13T19:56:00\",\"2019-01-13T19:56:00\",\"0\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-01-13T17:07:00\",\"2019-01-13T17:07:00\",\"1\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-01-13T09:04:00\",\"2019-01-13T09:04:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"258882000\",\"HOEGH TRADER\",\"312911\",\"2019-01-12T17:21:00\",\"2019-01-12T17:21:00\",\"0\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"563835000\",\"CITY OF OSLO\",\"727150\",\"2019-01-12T17:02:00\",\"2019-01-12T17:02:00\",\"1\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"219696000\",\"THUNDER BIRD\",\"205260\",\"2019-01-12T16:40:00\",\"2019-01-12T16:40:00\",\"1\",\"General Cargo\",\"150\",\"TYNE\",\"GBTYN\"],[\"564446000\",\"VIKING ODESSA\",\"728323\",\"2019-01-12T15:31:00\",\"2019-01-12T15:31:00\",\"1\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"563835000\",\"CITY OF OSLO\",\"727150\",\"2019-01-12T01:16:00\",\"2019-01-12T01:16:00\",\"0\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"219696000\",\"THUNDER BIRD\",\"205260\",\"2019-01-11T18:21:00\",\"2019-01-11T18:21:00\",\"0\",\"General Cargo\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-01-11T17:04:00\",\"2019-01-11T17:04:00\",\"1\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"233234000\",\"CITY OF BARCELONA\",\"184903\",\"2019-01-11T15:39:00\",\"2019-01-11T15:39:00\",\"1\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"564446000\",\"VIKING ODESSA\",\"728323\",\"2019-01-11T13:20:00\",\"2019-01-11T13:20:00\",\"0\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-01-11T08:44:00\",\"2019-01-11T08:44:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"219617000\",\"EMMA BULKER\",\"409819\",\"2019-01-11T05:26:00\",\"2019-01-11T05:26:00\",\"0\",\"Bulk Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"233234000\",\"CITY OF BARCELONA\",\"184903\",\"2019-01-10T16:16:00\",\"2019-01-10T16:16:00\",\"0\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"210521000\",\"STEEN\",\"125002\",\"2019-01-10T13:26:00\",\"2019-01-10T13:26:00\",\"1\",\"Container Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"636017904\",\"EXPLORER\",\"302906\",\"2019-01-10T12:16:00\",\"2019-01-10T12:16:00\",\"1\",\"Bulk Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"232079000\",\"CITY OF ROME\",\"183675\",\"2019-01-09T19:33:00\",\"2019-01-09T19:33:00\",\"1\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-01-09T18:41:00\",\"2019-01-09T18:41:00\",\"1\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"353941000\",\"NORD PACIFIC\",\"5202902\",\"2019-01-09T18:33:00\",\"2019-01-09T18:33:00\",\"1\",\"Bulk Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"232585000\",\"BIBBY POLARIS\",\"184208\",\"2019-01-09T15:16:00\",\"2019-01-09T15:16:00\",\"0\",\"Offshore Supply Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-01-09T14:02:00\",\"2019-01-09T14:02:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"372002000\",\"CITY OF ROTTERDAM\",\"461962\",\"2019-01-09T05:40:00\",\"2019-01-09T05:40:00\",\"1\",\"Ro-Ro Cargo\",\"150\",\"TYNE\",\"GBTYN\"],[\"210521000\",\"STEEN\",\"125002\",\"2019-01-08T17:23:00\",\"2019-01-08T17:23:00\",\"0\",\"Container Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-01-07T17:08:00\",\"2019-01-07T17:08:00\",\"1\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"372002000\",\"CITY OF ROTTERDAM\",\"461962\",\"2019-01-07T14:28:00\",\"2019-01-07T14:28:00\",\"0\",\"Ro-Ro Cargo\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-01-07T08:47:00\",\"2019-01-07T08:47:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"636017904\",\"EXPLORER\",\"302906\",\"2019-01-07T03:59:00\",\"2019-01-07T03:59:00\",\"0\",\"Bulk Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"636009548\",\"YEOMAN BANK\",\"752608\",\"2019-01-07T03:03:00\",\"2019-01-07T03:03:00\",\"1\",\"Self Discharging Bulk Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"220449000\",\"KING SEAWAYS\",\"159262\",\"2019-01-06T16:54:00\",\"2019-01-06T16:54:00\",\"1\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"218553000\",\"WIEBKE\",\"360293\",\"2019-01-06T15:38:00\",\"2019-01-06T15:38:00\",\"1\",\"General Cargo\",\"150\",\"TYNE\",\"GBTYN\"],[\"220449000\",\"KING SEAWAYS\",\"159262\",\"2019-01-06T08:43:00\",\"2019-01-06T08:43:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-01-05T17:04:00\",\"2019-01-05T17:04:00\",\"1\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"373774000\",\"TEAL BULKER\",\"465572\",\"2019-01-05T14:49:00\",\"2019-01-05T14:49:00\",\"1\",\"Bulk Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"218553000\",\"WIEBKE\",\"360293\",\"2019-01-05T13:21:00\",\"2019-01-05T13:21:00\",\"0\",\"General Cargo\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-01-05T08:49:00\",\"2019-01-05T08:49:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"255805578\",\"BG ROTTERDAM\",\"300119\",\"2019-01-05T04:32:00\",\"2019-01-05T04:32:00\",\"1\",\"Container Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"636009548\",\"YEOMAN BANK\",\"752608\",\"2019-01-05T02:12:00\",\"2019-01-05T02:12:00\",\"0\",\"Self Discharging Bulk Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"370395000\",\"FLORINDA\",\"458519\",\"2019-01-05T01:28:00\",\"2019-01-05T01:28:00\",\"1\",\"Bulk Carrier\",\"150\",\"TYNE\",\"GBTYN\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "6a85b6b1",
   "metadata": {},
   "outputs": [],
   "source": [
    "df4 = [[\"233234000\",\"CITY OF BARCELONA\",\"184903\",\"2019-01-31T21:20:00\",\"2019-01-31T21:20:00\",\"0\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-01-31T17:05:00\",\"2019-01-31T17:05:00\",\"1\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-01-31T08:46:00\",\"2019-01-31T08:46:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"564185000\",\"HOEGH INCHON\",\"727837\",\"2019-01-31T04:43:00\",\"2019-01-31T04:43:00\",\"1\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"244044000\",\"PRINSENGRACHT\",\"366252\",\"2019-01-30T22:15:00\",\"2019-01-30T22:15:00\",\"0\",\"Heavy Load Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"564185000\",\"HOEGH INCHON\",\"727837\",\"2019-01-30T08:27:00\",\"2019-01-30T08:27:00\",\"0\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"372002000\",\"CITY OF 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   "cell_type": "code",
   "execution_count": 73,
   "id": "3735172a",
   "metadata": {},
   "outputs": [],
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  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "88438eff",
   "metadata": {},
   "outputs": [],
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  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "8f24033d",
   "metadata": {},
   "outputs": [],
   "source": [
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  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "2574acfe",
   "metadata": {},
   "outputs": [],
   "source": [
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  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "a4998373",
   "metadata": {},
   "outputs": [],
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  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "9da2d685",
   "metadata": {},
   "outputs": [],
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  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "38ddd655",
   "metadata": {},
   "outputs": [],
   "source": [
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  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "bd3df1e3",
   "metadata": {},
   "outputs": [],
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  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "bac06c5d",
   "metadata": {},
   "outputs": [],
   "source": [
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  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "7059ccd2",
   "metadata": {},
   "outputs": [],
   "source": [
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   "execution_count": 96,
   "id": "787550ef",
   "metadata": {},
   "outputs": [],
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  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "8425b1ab",
   "metadata": {},
   "outputs": [],
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ACE\",\"408252\",\"2019-12-16T09:30:00\",\"2019-12-16T09:30:00\",\"0\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"220449000\",\"KING SEAWAYS\",\"159262\",\"2019-12-16T08:53:00\",\"2019-12-16T08:53:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"311002800\",\"SERENITY ACE\",\"372222\",\"2019-12-16T08:47:00\",\"2019-12-16T08:47:00\",\"1\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"314449000\",\"NORDIKA DESGAGNES\",\"365190\",\"2019-12-16T04:45:00\",\"2019-12-16T04:45:00\",\"0\",\"General Cargo\",\"150\",\"TYNE\",\"GBTYN\"],[\"636011258\",\"ROSINA TOPIC\",\"753022\",\"2019-12-16T03:16:00\",\"2019-12-16T03:16:00\",\"0\",\"Bulk Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"257786000\",\"OLYMPIC ORION\",\"308693\",\"2019-12-16T00:48:00\",\"2019-12-16T00:48:00\",\"0\",\"Supply Vessel\",\"150\",\"TYNE\",\"GBTYN\"],[\"246663000\",\"HAPPY DIAMOND\",\"5834574\",\"2019-12-15T17:12:00\",\"2019-12-15T17:12:00\",\"0\",\"General Cargo\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-12-15T17:02:00\",\"2019-12-15T17:02:00\",\"1\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"357094000\",\"VALKYRIE\",\"5974929\",\"2019-12-15T16:14:00\",\"2019-12-15T16:14:00\",\"0\",\"Bulk Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"257341000\",\"OLYMPIC ARES\",\"3354528\",\"2019-12-15T12:55:00\",\"2019-12-15T12:55:00\",\"0\",\"Multi Purpose Offshore Vessel\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-12-15T09:03:00\",\"2019-12-15T09:03:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"354013000\",\"PRT ACE\",\"1109615\",\"2019-12-15T04:19:00\",\"2019-12-15T04:19:00\",\"0\",\"Bulk Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"220449000\",\"KING SEAWAYS\",\"159262\",\"2019-12-14T17:12:00\",\"2019-12-14T17:12:00\",\"1\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"212836000\",\"ISADORA\",\"146267\",\"2019-12-14T16:32:00\",\"2019-12-14T16:32:00\",\"1\",\"Bulk Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"305621000\",\"AMOENITAS\",\"365304\",\"2019-12-14T13:23:00\",\"2019-12-14T13:23:00\",\"1\",\"General Cargo\",\"150\",\"TYNE\",\"GBTYN\"],[\"220449000\",\"KING SEAWAYS\",\"159262\",\"2019-12-14T08:48:00\",\"2019-12-14T08:48:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"311002800\",\"SERENITY ACE\",\"372222\",\"2019-12-14T01:05:00\",\"2019-12-14T01:05:00\",\"0\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"564446000\",\"VIKING ODESSA\",\"728323\",\"2019-12-13T22:19:00\",\"2019-12-13T22:19:00\",\"0\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-12-13T17:02:00\",\"2019-12-13T17:02:00\",\"1\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"305866000\",\"HC LARA\",\"366597\",\"2019-12-13T09:07:00\",\"2019-12-13T09:07:00\",\"0\",\"General Cargo\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-12-13T08:50:00\",\"2019-12-13T08:50:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"563835000\",\"CITY OF OSLO\",\"727150\",\"2019-12-12T21:17:00\",\"2019-12-12T21:17:00\",\"1\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"232215000\",\"SAND FALCON\",\"183875\",\"2019-12-12T19:53:00\",\"2019-12-12T19:53:00\",\"1\",\"Hopper Dredger\",\"150\",\"TYNE\",\"GBTYN\"],[\"220449000\",\"KING SEAWAYS\",\"159262\",\"2019-12-12T17:05:00\",\"2019-12-12T17:05:00\",\"1\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"255805770\",\"BALTIC WINTER\",\"758556\",\"2019-12-12T16:42:00\",\"2019-12-12T16:42:00\",\"1\",\"General Cargo\",\"150\",\"TYNE\",\"GBTYN\"],[\"563835000\",\"CITY OF OSLO\",\"727150\",\"2019-12-12T13:55:00\",\"2019-12-12T13:55:00\",\"0\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"305621000\",\"AMOENITAS\",\"365304\",\"2019-12-12T13:14:00\",\"2019-12-12T13:14:00\",\"0\",\"General Cargo\",\"150\",\"TYNE\",\"GBTYN\"],[\"353083000\",\"CITY OF ST.PETERSBURG\",\"411554\",\"2019-12-12T13:01:00\",\"2019-12-12T13:01:00\",\"1\",\"Ro-Ro Cargo\",\"150\",\"TYNE\",\"GBTYN\"],[\"232215000\",\"SAND FALCON\",\"183875\",\"2019-12-12T12:10:00\",\"2019-12-12T12:10:00\",\"0\",\"Hopper Dredger\",\"150\",\"TYNE\",\"GBTYN\"],[\"538006475\",\"STH NEW YORK\",\"5783431\",\"2019-12-12T11:49:00\",\"2019-12-12T11:49:00\",\"1\",\"Bulk Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"220449000\",\"KING SEAWAYS\",\"159262\",\"2019-12-12T08:38:00\",\"2019-12-12T08:38:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"351757000\",\"COMET ACE\",\"408252\",\"2019-12-12T01:31:00\",\"2019-12-12T01:31:00\",\"1\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-12-11T17:04:00\",\"2019-12-11T17:04:00\",\"1\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"353083000\",\"CITY OF ST.PETERSBURG\",\"411554\",\"2019-12-11T08:52:00\",\"2019-12-11T08:52:00\",\"0\",\"Ro-Ro Cargo\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-12-11T08:45:00\",\"2019-12-11T08:45:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"232215000\",\"SAND FALCON\",\"183875\",\"2019-12-11T07:47:00\",\"2019-12-11T07:47:00\",\"1\",\"Hopper Dredger\",\"150\",\"TYNE\",\"GBTYN\"],[\"564488000\",\"HOEGH PUSAN\",\"728417\",\"2019-12-11T06:19:00\",\"2019-12-11T06:19:00\",\"1\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"212836000\",\"ISADORA\",\"146267\",\"2019-12-11T01:21:00\",\"2019-12-11T01:21:00\",\"0\",\"Bulk Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"232215000\",\"SAND FALCON\",\"183875\",\"2019-12-10T22:52:00\",\"2019-12-10T22:52:00\",\"0\",\"Hopper Dredger\",\"150\",\"TYNE\",\"GBTYN\"],[\"220449000\",\"KING SEAWAYS\",\"159262\",\"2019-12-10T16:54:00\",\"2019-12-10T16:54:00\",\"1\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"220449000\",\"KING SEAWAYS\",\"159262\",\"2019-12-10T08:45:00\",\"2019-12-10T08:45:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"564488000\",\"HOEGH PUSAN\",\"728417\",\"2019-12-10T05:17:00\",\"2019-12-10T05:17:00\",\"0\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"255806008\",\"OLAND\",\"302268\",\"2019-12-10T03:55:00\",\"2019-12-10T03:55:00\",\"1\",\"Container Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"351757000\",\"COMET ACE\",\"408252\",\"2019-12-10T00:42:00\",\"2019-12-10T00:42:00\",\"0\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"232215000\",\"SAND FALCON\",\"183875\",\"2019-12-09T19:25:00\",\"2019-12-09T19:25:00\",\"1\",\"Hopper Dredger\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-12-09T16:54:00\",\"2019-12-09T16:54:00\",\"1\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-12-09T08:48:00\",\"2019-12-09T08:48:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"232215000\",\"SAND FALCON\",\"183875\",\"2019-12-09T06:50:00\",\"2019-12-09T06:50:00\",\"0\",\"Hopper Dredger\",\"150\",\"TYNE\",\"GBTYN\"],[\"538006475\",\"STH NEW YORK\",\"5783431\",\"2019-12-09T00:30:00\",\"2019-12-09T00:30:00\",\"0\",\"Bulk Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"220449000\",\"KING SEAWAYS\",\"159262\",\"2019-12-08T17:47:00\",\"2019-12-08T17:47:00\",\"1\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"255805770\",\"BALTIC WINTER\",\"758556\",\"2019-12-08T12:26:00\",\"2019-12-08T12:26:00\",\"0\",\"General Cargo\",\"150\",\"TYNE\",\"GBTYN\"],[\"220449000\",\"KING SEAWAYS\",\"159262\",\"2019-12-08T08:41:00\",\"2019-12-08T08:41:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"232215000\",\"SAND FALCON\",\"183875\",\"2019-12-08T06:13:00\",\"2019-12-08T06:13:00\",\"1\",\"Hopper Dredger\",\"150\",\"TYNE\",\"GBTYN\"],[\"232215000\",\"SAND FALCON\",\"183875\",\"2019-12-07T21:23:00\",\"2019-12-07T21:23:00\",\"0\",\"Hopper Dredger\",\"150\",\"TYNE\",\"GBTYN\"],[\"255806008\",\"OLAND\",\"302268\",\"2019-12-07T19:45:00\",\"2019-12-07T19:45:00\",\"0\",\"Container Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-12-07T17:17:00\",\"2019-12-07T17:17:00\",\"1\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-12-07T08:47:00\",\"2019-12-07T08:47:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"220449000\",\"KING SEAWAYS\",\"159262\",\"2019-12-06T17:02:00\",\"2019-12-06T17:02:00\",\"1\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"220449000\",\"KING SEAWAYS\",\"159262\",\"2019-12-06T08:44:00\",\"2019-12-06T08:44:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"209184000\",\"IMAVERE\",\"732904\",\"2019-12-06T00:48:00\",\"2019-12-06T00:48:00\",\"1\",\"Bulk Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"309586000\",\"NORDIC ACE\",\"370244\",\"2019-12-05T23:30:00\",\"2019-12-05T23:30:00\",\"1\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-12-05T17:19:00\",\"2019-12-05T17:19:00\",\"1\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"564446000\",\"VIKING ODESSA\",\"728323\",\"2019-12-05T13:01:00\",\"2019-12-05T13:01:00\",\"1\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"249335000\",\"NORTH OCEAN 102\",\"288378\",\"2019-12-05T10:24:00\",\"2019-12-05T10:24:00\",\"1\",\"Offshore Supply Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-12-05T08:49:00\",\"2019-12-05T08:49:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"564446000\",\"VIKING ODESSA\",\"728323\",\"2019-12-04T21:49:00\",\"2019-12-04T21:49:00\",\"0\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"431339000\",\"PEGASUS ACE\",\"418270\",\"2019-12-04T18:34:00\",\"2019-12-04T18:34:00\",\"1\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"309586000\",\"NORDIC ACE\",\"370244\",\"2019-12-04T17:16:00\",\"2019-12-04T17:16:00\",\"0\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"220449000\",\"KING SEAWAYS\",\"159262\",\"2019-12-04T17:06:00\",\"2019-12-04T17:06:00\",\"1\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"538006520\",\"TOMINI DESTINY\",\"3819730\",\"2019-12-04T16:57:00\",\"2019-12-04T16:57:00\",\"1\",\"Bulk Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"220449000\",\"KING SEAWAYS\",\"159262\",\"2019-12-04T08:47:00\",\"2019-12-04T08:47:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-12-03T16:56:00\",\"2019-12-03T16:56:00\",\"1\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-12-03T08:48:00\",\"2019-12-03T08:48:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"431339000\",\"PEGASUS ACE\",\"418270\",\"2019-12-03T05:47:00\",\"2019-12-03T05:47:00\",\"0\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"220449000\",\"KING SEAWAYS\",\"159262\",\"2019-12-02T17:04:00\",\"2019-12-02T17:04:00\",\"1\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"209184000\",\"IMAVERE\",\"732904\",\"2019-12-02T12:34:00\",\"2019-12-02T12:34:00\",\"0\",\"Bulk Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"477222100\",\"WU GUI SHAN\",\"686490\",\"2019-12-02T11:45:00\",\"2019-12-02T11:45:00\",\"1\",\"Bulk Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"220449000\",\"KING SEAWAYS\",\"159262\",\"2019-12-02T08:49:00\",\"2019-12-02T08:49:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"255806008\",\"OLAND\",\"302268\",\"2019-12-02T05:32:00\",\"2019-12-02T05:32:00\",\"1\",\"Container Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-12-01T17:03:00\",\"2019-12-01T17:03:00\",\"1\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"],[\"250005053\",\"ARKLOW DUSK\",\"264354\",\"2019-12-01T12:45:00\",\"2019-12-01T12:45:00\",\"1\",\"Cargo\\/Containership\",\"150\",\"TYNE\",\"GBTYN\"],[\"354123000\",\"AQUARIUS ACE\",\"413769\",\"2019-12-01T11:28:00\",\"2019-12-01T11:28:00\",\"1\",\"Vehicles Carrier\",\"150\",\"TYNE\",\"GBTYN\"],[\"220489000\",\"PRINCESS SEAWAYS\",\"159354\",\"2019-12-01T09:05:00\",\"2019-12-01T09:05:00\",\"0\",\"Ro-Ro\\/Passenger Ship\",\"150\",\"TYNE\",\"GBTYN\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "00137916",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "list"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(dfDec)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "9dd6b08e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Writing to sample.json\n",
    "with open('E:\\\\20190923 Newcastle-M.Res\\\\OneDrive - Newcastle University\\\\21_22_autumn\\\\211018\\\\code\\\\data\\\\vesseldata\\\\191201-191231.json', 'w+') as f:\n",
    "    json.dump(dfDec, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d796c92a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "0a3da908",
   "metadata": {},
   "source": [
    "### Extended Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "19bd5e49",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d5bf67c9",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "c7efdca9",
   "metadata": {},
   "outputs": [],
   "source": [
    "null = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "4e26c50d",
   "metadata": {},
   "outputs": [],
   "source": [
    "#### extended data from 2019/01/01 00:00 to 2019/01/19 23:59\n",
    "ex1 = [\n",
    "  [\n",
    "    \"212967000\",\n",
    "    \"SHEILA\",\n",
    "    \"3819695\",\n",
    "    \"2019-01-19T08:08:00\",\n",
    "    \"2019-01-19T08:08:00\",\n",
    "    \"0\",\n",
    "    \"Bulk Carrier\",\n",
    "    \"150\",\n",
    "    \"TYNE\",\n",
    "    \"GBTYN\",\n",
    "    \"87\",\n",
    "    \"1\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"711\",\n",
    "    \"122\",\n",
    "    \"156\",\n",
    "    \"11\",\n",
    "    \"3503\",\n",
    "    \"0\",\n",
    "    \"DRY BULK\",\n",
    "    \"HANDYMAX\"\n",
    "  ],\n",
    "  [\n",
    "    \"355922000\",\n",
    "    \"GREEN GEM\",\n",
    "    \"5748751\",\n",
    "    \"2019-01-19T05:26:00\",\n",
    "    \"2019-01-19T05:26:00\",\n",
    "    \"1\",\n",
    "    \"Bulk Carrier\",\n",
    "    \"150\",\n",
    "    \"TYNE\",\n",
    "    \"GBTYN\",\n",
    "    \"64\",\n",
    "    \"1\",\n",
    "    \"2\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    null,\n",
    "    \"26177\",\n",
    "    null,\n",
    "    \"DRY BULK\",\n",
    "    \"HANDYSIZE\"\n",
    "  ],\n",
    "  [\n",
    "    \"257392000\",\n",
    "    \"BETTY KNUTSEN\",\n",
    "    \"306511\",\n",
    "    \"2019-01-18T17:17:00\",\n",
    "    \"2019-01-18T17:17:00\",\n",
    "    \"1\",\n",
    "    \"Shuttle Tanker\",\n",
    "    \"150\",\n",
    "    \"TYNE\",\n",
    "    \"GBTYN\",\n",
    "    \"55\",\n",
    "    \"1\",\n",
    "    \"4\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    null,\n",
    "    \"1908\",\n",
    "    null,\n",
    "    \"WET BULK\",\n",
    "    \"HANDYSIZE\"\n",
    "  ],\n",
    "  [\n",
    "    \"257392000\",\n",
    "    \"BETTY KNUTSEN\",\n",
    "    \"306511\",\n",
    "    \"2019-01-17T16:06:00\",\n",
    "    \"2019-01-17T16:06:00\",\n",
    "    \"0\",\n",
    "    \"Shuttle Tanker\",\n",
    "    \"150\",\n",
    "    \"TYNE\",\n",
    "    \"GBTYN\",\n",
    "    \"52\",\n",
    "    \"1\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
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    "    \"91\",\n",
    "    \"21\",\n",
    "    \"397\",\n",
    "    \"0\",\n",
    "    \"WET BULK\",\n",
    "    \"HANDYSIZE\"\n",
    "  ],\n",
    "  [\n",
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    "    \"GREEN GEM\",\n",
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    "    \"2019-01-15T21:27:00\",\n",
    "    \"2019-01-15T21:27:00\",\n",
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    "    \"150\",\n",
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    "    \"GBTYN\",\n",
    "    \"101\",\n",
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    "    \"0\",\n",
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    "    \"154\",\n",
    "    \"0\",\n",
    "    \"21378\",\n",
    "    \"4026\",\n",
    "    \"DRY BULK\",\n",
    "    \"HANDYSIZE\"\n",
    "  ],\n",
    "  [\n",
    "    \"219617000\",\n",
    "    \"EMMA BULKER\",\n",
    "    \"409819\",\n",
    "    \"2019-01-14T18:50:00\",\n",
    "    \"2019-01-14T18:50:00\",\n",
    "    \"1\",\n",
    "    \"Bulk Carrier\",\n",
    "    \"150\",\n",
    "    \"TYNE\",\n",
    "    \"GBTYN\",\n",
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    "    \"2\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
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    "    \"33152\",\n",
    "    null,\n",
    "    \"DRY BULK\",\n",
    "    \"HANDYSIZE\"\n",
    "  ],\n",
    "  [\n",
    "    \"258882000\",\n",
    "    \"HOEGH TRADER\",\n",
    "    \"312911\",\n",
    "    \"2019-01-14T16:06:00\",\n",
    "    \"2019-01-14T16:06:00\",\n",
    "    \"1\",\n",
    "    \"Vehicles Carrier\",\n",
    "    \"150\",\n",
    "    \"TYNE\",\n",
    "    \"GBTYN\",\n",
    "    \"81\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    null,\n",
    "    \"4035\",\n",
    "    null,\n",
    "    \"RO/RO\",\n",
    "    null\n",
    "  ],\n",
    "  [\n",
    "    \"258882000\",\n",
    "    \"HOEGH TRADER\",\n",
    "    \"312911\",\n",
    "    \"2019-01-12T17:21:00\",\n",
    "    \"2019-01-12T17:21:00\",\n",
    "    \"0\",\n",
    "    \"Vehicles Carrier\",\n",
    "    \"150\",\n",
    "    \"TYNE\",\n",
    "    \"GBTYN\",\n",
    "    \"89\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"299\",\n",
    "    \"146\",\n",
    "    \"177\",\n",
    "    \"19\",\n",
    "    \"1230\",\n",
    "    \"0\",\n",
    "    \"RO/RO\",\n",
    "    null\n",
    "  ],\n",
    "  [\n",
    "    \"219617000\",\n",
    "    \"EMMA BULKER\",\n",
    "    \"409819\",\n",
    "    \"2019-01-11T05:26:00\",\n",
    "    \"2019-01-11T05:26:00\",\n",
    "    \"0\",\n",
    "    \"Bulk Carrier\",\n",
    "    \"150\",\n",
    "    \"TYNE\",\n",
    "    \"GBTYN\",\n",
    "    \"96\",\n",
    "    \"3\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"5351\",\n",
    "    \"109\",\n",
    "    \"155\",\n",
    "    \"514\",\n",
    "    \"28028\",\n",
    "    \"0\",\n",
    "    \"DRY BULK\",\n",
    "    \"HANDYSIZE\"\n",
    "  ],\n",
    "  [\n",
    "    \"636017904\",\n",
    "    \"EXPLORER\",\n",
    "    \"302906\",\n",
    "    \"2019-01-10T12:16:00\",\n",
    "    \"2019-01-10T12:16:00\",\n",
    "    \"1\",\n",
    "    \"Bulk Carrier\",\n",
    "    \"150\",\n",
    "    \"TYNE\",\n",
    "    \"GBTYN\",\n",
    "    \"58\",\n",
    "    null,\n",
    "    \"2\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    null,\n",
    "    \"26413\",\n",
    "    null,\n",
    "    \"DRY BULK\",\n",
    "    \"HANDYSIZE\"\n",
    "  ],\n",
    "  [\n",
    "    \"353941000\",\n",
    "    \"NORD PACIFIC\",\n",
    "    \"5202902\",\n",
    "    \"2019-01-09T18:33:00\",\n",
    "    \"2019-01-09T18:33:00\",\n",
    "    \"1\",\n",
    "    \"Bulk Carrier\",\n",
    "    \"150\",\n",
    "    \"TYNE\",\n",
    "    \"GBTYN\",\n",
    "    \"69\",\n",
    "    \"1\",\n",
    "    \"2\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    null,\n",
    "    \"62861\",\n",
    "    null,\n",
    "    \"DRY BULK\",\n",
    "    \"PANAMAX\"\n",
    "  ],\n",
    "  [\n",
    "    \"636017904\",\n",
    "    \"EXPLORER\",\n",
    "    \"302906\",\n",
    "    \"2019-01-07T03:59:00\",\n",
    "    \"2019-01-07T03:59:00\",\n",
    "    \"0\",\n",
    "    \"Bulk Carrier\",\n",
    "    \"150\",\n",
    "    \"TYNE\",\n",
    "    \"GBTYN\",\n",
    "    \"82\",\n",
    "    \"2\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"4290\",\n",
    "    \"126\",\n",
    "    \"164\",\n",
    "    \"462\",\n",
    "    \"21596\",\n",
    "    \"0\",\n",
    "    \"DRY BULK\",\n",
    "    \"HANDYSIZE\"\n",
    "  ],\n",
    "  [\n",
    "    \"636009548\",\n",
    "    \"YEOMAN BANK\",\n",
    "    \"752608\",\n",
    "    \"2019-01-07T03:03:00\",\n",
    "    \"2019-01-07T03:03:00\",\n",
    "    \"1\",\n",
    "    \"Self Discharging Bulk Carrier\",\n",
    "    \"150\",\n",
    "    \"TYNE\",\n",
    "    \"GBTYN\",\n",
    "    \"68\",\n",
    "    \"1\",\n",
    "    \"2\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    null,\n",
    "    \"6107\",\n",
    "    null,\n",
    "    \"DRY BULK\",\n",
    "    \"HANDYMAX\"\n",
    "  ],\n",
    "  [\n",
    "    \"373774000\",\n",
    "    \"TEAL BULKER\",\n",
    "    \"465572\",\n",
    "    \"2019-01-05T14:49:00\",\n",
    "    \"2019-01-05T14:49:00\",\n",
    "    \"1\",\n",
    "    \"Bulk Carrier\",\n",
    "    \"150\",\n",
    "    \"TYNE\",\n",
    "    \"GBTYN\",\n",
    "    \"118\",\n",
    "    \"3\",\n",
    "    \"1\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    null,\n",
    "    \"10656\",\n",
    "    null,\n",
    "    \"DRY BULK\",\n",
    "    \"HANDYMAX\"\n",
    "  ],\n",
    "  [\n",
    "    \"636009548\",\n",
    "    \"YEOMAN BANK\",\n",
    "    \"752608\",\n",
    "    \"2019-01-05T02:12:00\",\n",
    "    \"2019-01-05T02:12:00\",\n",
    "    \"0\",\n",
    "    \"Self Discharging Bulk Carrier\",\n",
    "    \"150\",\n",
    "    \"TYNE\",\n",
    "    \"GBTYN\",\n",
    "    \"116\",\n",
    "    \"3\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"479\",\n",
    "    \"118\",\n",
    "    \"150\",\n",
    "    \"724\",\n",
    "    \"3176\",\n",
    "    \"1\",\n",
    "    \"DRY BULK\",\n",
    "    \"HANDYMAX\"\n",
    "  ],\n",
    "  [\n",
    "    \"370395000\",\n",
    "    \"FLORINDA\",\n",
    "    \"458519\",\n",
    "    \"2019-01-05T01:28:00\",\n",
    "    \"2019-01-05T01:28:00\",\n",
    "    \"1\",\n",
    "    \"Bulk Carrier\",\n",
    "    \"150\",\n",
    "    \"TYNE\",\n",
    "    \"GBTYN\",\n",
    "    \"63\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    null,\n",
    "    \"40685\",\n",
    "    null,\n",
    "    \"DRY BULK\",\n",
    "    \"HANDYMAX\"\n",
    "  ],\n",
    "  [\n",
    "    \"353941000\",\n",
    "    \"NORD PACIFIC\",\n",
    "    \"5202902\",\n",
    "    \"2019-01-04T13:24:00\",\n",
    "    \"2019-01-04T13:24:00\",\n",
    "    \"0\",\n",
    "    \"Bulk Carrier\",\n",
    "    \"150\",\n",
    "    \"TYNE\",\n",
    "    \"GBTYN\",\n",
    "    \"119\",\n",
    "    \"3\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"9747\",\n",
    "    \"115\",\n",
    "    \"152\",\n",
    "    \"3972\",\n",
    "    \"55352\",\n",
    "    \"0\",\n",
    "    \"DRY BULK\",\n",
    "    \"PANAMAX\"\n",
    "  ],\n",
    "  [\n",
    "    \"209184000\",\n",
    "    \"IMAVERE\",\n",
    "    \"732904\",\n",
    "    \"2019-01-02T19:29:00\",\n",
    "    \"2019-01-02T19:29:00\",\n",
    "    \"1\",\n",
    "    \"Bulk Carrier\",\n",
    "    \"150\",\n",
    "    \"TYNE\",\n",
    "    \"GBTYN\",\n",
    "    \"62\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    \"0\",\n",
    "    null,\n",
    "    \"10628\",\n",
    "    null,\n",
    "    \"DRY BULK\",\n",
    "    \"HANDYSIZE\"\n",
    "  ]\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "037050e3",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "      <th>0</th>\n",
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       "      <td>212967000</td>\n",
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       "      <td>355922000</td>\n",
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       "      <td>2019-01-19T05:26:00</td>\n",
       "      <td>2019-01-19T05:26:00</td>\n",
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       "      <td>TYNE</td>\n",
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       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>257392000</td>\n",
       "      <td>BETTY KNUTSEN</td>\n",
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       "      <td>2019-01-18T17:17:00</td>\n",
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       "      <td>TYNE</td>\n",
       "      <td>GBTYN</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>1908</td>\n",
       "      <td>None</td>\n",
       "      <td>WET BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>257392000</td>\n",
       "      <td>BETTY KNUTSEN</td>\n",
       "      <td>306511</td>\n",
       "      <td>2019-01-17T16:06:00</td>\n",
       "      <td>2019-01-17T16:06:00</td>\n",
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       "      <td>Shuttle Tanker</td>\n",
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       "      <td>TYNE</td>\n",
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       "      <td>0</td>\n",
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       "      <td>GREEN GEM</td>\n",
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       "      <td>2019-01-15T21:27:00</td>\n",
       "      <td>2019-01-15T21:27:00</td>\n",
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       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>GBTYN</td>\n",
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       "      <td>HANDYSIZE</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>219617000</td>\n",
       "      <td>EMMA BULKER</td>\n",
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       "      <td>2019-01-14T18:50:00</td>\n",
       "      <td>2019-01-14T18:50:00</td>\n",
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       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>33152</td>\n",
       "      <td>None</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>258882000</td>\n",
       "      <td>HOEGH TRADER</td>\n",
       "      <td>312911</td>\n",
       "      <td>2019-01-14T16:06:00</td>\n",
       "      <td>2019-01-14T16:06:00</td>\n",
       "      <td>1</td>\n",
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       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>GBTYN</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>4035</td>\n",
       "      <td>None</td>\n",
       "      <td>RO/RO</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>258882000</td>\n",
       "      <td>HOEGH TRADER</td>\n",
       "      <td>312911</td>\n",
       "      <td>2019-01-12T17:21:00</td>\n",
       "      <td>2019-01-12T17:21:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Vehicles Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>GBTYN</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>299</td>\n",
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       "      <td>177</td>\n",
       "      <td>19</td>\n",
       "      <td>1230</td>\n",
       "      <td>0</td>\n",
       "      <td>RO/RO</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>219617000</td>\n",
       "      <td>EMMA BULKER</td>\n",
       "      <td>409819</td>\n",
       "      <td>2019-01-11T05:26:00</td>\n",
       "      <td>2019-01-11T05:26:00</td>\n",
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       "      <td>Bulk Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>GBTYN</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5351</td>\n",
       "      <td>109</td>\n",
       "      <td>155</td>\n",
       "      <td>514</td>\n",
       "      <td>28028</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>636017904</td>\n",
       "      <td>EXPLORER</td>\n",
       "      <td>302906</td>\n",
       "      <td>2019-01-10T12:16:00</td>\n",
       "      <td>2019-01-10T12:16:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>GBTYN</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>26413</td>\n",
       "      <td>None</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>353941000</td>\n",
       "      <td>NORD PACIFIC</td>\n",
       "      <td>5202902</td>\n",
       "      <td>2019-01-09T18:33:00</td>\n",
       "      <td>2019-01-09T18:33:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>GBTYN</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>62861</td>\n",
       "      <td>None</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>PANAMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>636017904</td>\n",
       "      <td>EXPLORER</td>\n",
       "      <td>302906</td>\n",
       "      <td>2019-01-07T03:59:00</td>\n",
       "      <td>2019-01-07T03:59:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>GBTYN</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4290</td>\n",
       "      <td>126</td>\n",
       "      <td>164</td>\n",
       "      <td>462</td>\n",
       "      <td>21596</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>636009548</td>\n",
       "      <td>YEOMAN BANK</td>\n",
       "      <td>752608</td>\n",
       "      <td>2019-01-07T03:03:00</td>\n",
       "      <td>2019-01-07T03:03:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Self Discharging Bulk Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>GBTYN</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>6107</td>\n",
       "      <td>None</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>373774000</td>\n",
       "      <td>TEAL BULKER</td>\n",
       "      <td>465572</td>\n",
       "      <td>2019-01-05T14:49:00</td>\n",
       "      <td>2019-01-05T14:49:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>GBTYN</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>10656</td>\n",
       "      <td>None</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>636009548</td>\n",
       "      <td>YEOMAN BANK</td>\n",
       "      <td>752608</td>\n",
       "      <td>2019-01-05T02:12:00</td>\n",
       "      <td>2019-01-05T02:12:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Self Discharging Bulk Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>GBTYN</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>479</td>\n",
       "      <td>118</td>\n",
       "      <td>150</td>\n",
       "      <td>724</td>\n",
       "      <td>3176</td>\n",
       "      <td>1</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>370395000</td>\n",
       "      <td>FLORINDA</td>\n",
       "      <td>458519</td>\n",
       "      <td>2019-01-05T01:28:00</td>\n",
       "      <td>2019-01-05T01:28:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>GBTYN</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>40685</td>\n",
       "      <td>None</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>353941000</td>\n",
       "      <td>NORD PACIFIC</td>\n",
       "      <td>5202902</td>\n",
       "      <td>2019-01-04T13:24:00</td>\n",
       "      <td>2019-01-04T13:24:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>GBTYN</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9747</td>\n",
       "      <td>115</td>\n",
       "      <td>152</td>\n",
       "      <td>3972</td>\n",
       "      <td>55352</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>PANAMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>209184000</td>\n",
       "      <td>IMAVERE</td>\n",
       "      <td>732904</td>\n",
       "      <td>2019-01-02T19:29:00</td>\n",
       "      <td>2019-01-02T19:29:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>GBTYN</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>10628</td>\n",
       "      <td>None</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>18 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           0              1        2                    3   \\\n",
       "0   212967000         SHEILA  3819695  2019-01-19T08:08:00   \n",
       "1   355922000      GREEN GEM  5748751  2019-01-19T05:26:00   \n",
       "2   257392000  BETTY KNUTSEN   306511  2019-01-18T17:17:00   \n",
       "3   257392000  BETTY KNUTSEN   306511  2019-01-17T16:06:00   \n",
       "4   355922000      GREEN GEM  5748751  2019-01-15T21:27:00   \n",
       "5   219617000    EMMA BULKER   409819  2019-01-14T18:50:00   \n",
       "6   258882000   HOEGH TRADER   312911  2019-01-14T16:06:00   \n",
       "7   258882000   HOEGH TRADER   312911  2019-01-12T17:21:00   \n",
       "8   219617000    EMMA BULKER   409819  2019-01-11T05:26:00   \n",
       "9   636017904       EXPLORER   302906  2019-01-10T12:16:00   \n",
       "10  353941000   NORD PACIFIC  5202902  2019-01-09T18:33:00   \n",
       "11  636017904       EXPLORER   302906  2019-01-07T03:59:00   \n",
       "12  636009548    YEOMAN BANK   752608  2019-01-07T03:03:00   \n",
       "13  373774000    TEAL BULKER   465572  2019-01-05T14:49:00   \n",
       "14  636009548    YEOMAN BANK   752608  2019-01-05T02:12:00   \n",
       "15  370395000       FLORINDA   458519  2019-01-05T01:28:00   \n",
       "16  353941000   NORD PACIFIC  5202902  2019-01-04T13:24:00   \n",
       "17  209184000        IMAVERE   732904  2019-01-02T19:29:00   \n",
       "\n",
       "                     4  5                              6    7     8      9   \\\n",
       "0   2019-01-19T08:08:00  0                   Bulk Carrier  150  TYNE  GBTYN   \n",
       "1   2019-01-19T05:26:00  1                   Bulk Carrier  150  TYNE  GBTYN   \n",
       "2   2019-01-18T17:17:00  1                 Shuttle Tanker  150  TYNE  GBTYN   \n",
       "3   2019-01-17T16:06:00  0                 Shuttle Tanker  150  TYNE  GBTYN   \n",
       "4   2019-01-15T21:27:00  0                   Bulk Carrier  150  TYNE  GBTYN   \n",
       "5   2019-01-14T18:50:00  1                   Bulk Carrier  150  TYNE  GBTYN   \n",
       "6   2019-01-14T16:06:00  1               Vehicles Carrier  150  TYNE  GBTYN   \n",
       "7   2019-01-12T17:21:00  0               Vehicles Carrier  150  TYNE  GBTYN   \n",
       "8   2019-01-11T05:26:00  0                   Bulk Carrier  150  TYNE  GBTYN   \n",
       "9   2019-01-10T12:16:00  1                   Bulk Carrier  150  TYNE  GBTYN   \n",
       "10  2019-01-09T18:33:00  1                   Bulk Carrier  150  TYNE  GBTYN   \n",
       "11  2019-01-07T03:59:00  0                   Bulk Carrier  150  TYNE  GBTYN   \n",
       "12  2019-01-07T03:03:00  1  Self Discharging Bulk Carrier  150  TYNE  GBTYN   \n",
       "13  2019-01-05T14:49:00  1                   Bulk Carrier  150  TYNE  GBTYN   \n",
       "14  2019-01-05T02:12:00  0  Self Discharging Bulk Carrier  150  TYNE  GBTYN   \n",
       "15  2019-01-05T01:28:00  1                   Bulk Carrier  150  TYNE  GBTYN   \n",
       "16  2019-01-04T13:24:00  0                   Bulk Carrier  150  TYNE  GBTYN   \n",
       "17  2019-01-02T19:29:00  1                   Bulk Carrier  150  TYNE  GBTYN   \n",
       "\n",
       "    ... 12 13    14   15   16    17     18    19        20         21  \n",
       "0   ...  0  0   711  122  156    11   3503     0  DRY BULK   HANDYMAX  \n",
       "1   ...  2  0     0    0    0  None  26177  None  DRY BULK  HANDYSIZE  \n",
       "2   ...  4  0     0    0    0  None   1908  None  WET BULK  HANDYSIZE  \n",
       "3   ...  0  0    32   51   91    21    397     0  WET BULK  HANDYSIZE  \n",
       "4   ...  0  0  4026  111  154     0  21378  4026  DRY BULK  HANDYSIZE  \n",
       "5   ...  2  0     0    0    0  None  33152  None  DRY BULK  HANDYSIZE  \n",
       "6   ...  0  0     0    0    0  None   4035  None     RO/RO       None  \n",
       "7   ...  0  0   299  146  177    19   1230     0     RO/RO       None  \n",
       "8   ...  0  0  5351  109  155   514  28028     0  DRY BULK  HANDYSIZE  \n",
       "9   ...  2  0     0    0    0  None  26413  None  DRY BULK  HANDYSIZE  \n",
       "10  ...  2  0     0    0    0  None  62861  None  DRY BULK    PANAMAX  \n",
       "11  ...  0  0  4290  126  164   462  21596     0  DRY BULK  HANDYSIZE  \n",
       "12  ...  2  0     0    0    0  None   6107  None  DRY BULK   HANDYMAX  \n",
       "13  ...  1  0     0    0    0  None  10656  None  DRY BULK   HANDYMAX  \n",
       "14  ...  0  0   479  118  150   724   3176     1  DRY BULK   HANDYMAX  \n",
       "15  ...  0  0     0    0    0  None  40685  None  DRY BULK   HANDYMAX  \n",
       "16  ...  0  0  9747  115  152  3972  55352     0  DRY BULK    PANAMAX  \n",
       "17  ...  0  0     0    0    0  None  10628  None  DRY BULK  HANDYSIZE  \n",
       "\n",
       "[18 rows x 22 columns]"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ex1 = pd.DataFrame(ex1)\n",
    "ex1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "e651299e",
   "metadata": {},
   "outputs": [],
   "source": [
    "ex1.to_csv('ex1.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "50fff121",
   "metadata": {},
   "outputs": [],
   "source": [
    "ex1 = pd.read_csv('ex1.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "32d4eee7",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "ex1 = ex1.loc[::-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "55fc2e88",
   "metadata": {},
   "outputs": [],
   "source": [
    "ex1.to_json('ex1.json')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "7aa1c70a",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "ex1 = pd.read_json('ex1.json')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "43f1038d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "a058efb0",
   "metadata": {},
   "outputs": [],
   "source": [
    "ex2 = [[\"244044000\",\"PRINSENGRACHT\",\"366252\",\"2019-01-30T22:15:00\",\"2019-01-30T22:15:00\",\"0\",\"Heavy Load Carrier\",\"150\",\"TYNE\",\"GBTYN\",\"75\",\"2\",\"0\",\"0\",\"609\",\"133\",\"151\",\"232\",\"2917\",\"0\",\"DRY BREAKBULK\",\"HANDYSIZE\"],[\"212967000\",\"SHEILA\",\"3819695\",\"2019-01-27T20:11:00\",\"2019-01-27T20:11:00\",\"1\",\"Bulk Carrier\",\"150\",\"TYNE\",\"GBTYN\",\"121\",\"3\",\"1\",\"0\",\"0\",\"0\",\"0\",null,\"15746\",null,\"DRY BULK\",\"HANDYMAX\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "2dabed8f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
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       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>...</th>\n",
       "      <th>12</th>\n",
       "      <th>13</th>\n",
       "      <th>14</th>\n",
       "      <th>15</th>\n",
       "      <th>16</th>\n",
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       "      <th>18</th>\n",
       "      <th>19</th>\n",
       "      <th>20</th>\n",
       "      <th>21</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>212967000</td>\n",
       "      <td>SHEILA</td>\n",
       "      <td>3819695</td>\n",
       "      <td>2019-01-27T20:11:00</td>\n",
       "      <td>2019-01-27T20:11:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15746</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>244044000</td>\n",
       "      <td>PRINSENGRACHT</td>\n",
       "      <td>366252</td>\n",
       "      <td>2019-01-30T22:15:00</td>\n",
       "      <td>2019-01-30T22:15:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Heavy Load Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>609</td>\n",
       "      <td>133</td>\n",
       "      <td>151</td>\n",
       "      <td>232.0</td>\n",
       "      <td>2917</td>\n",
       "      <td>0.0</td>\n",
       "      <td>DRY BREAKBULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0          0              1        2                    3  \\\n",
       "1           1  212967000         SHEILA  3819695  2019-01-27T20:11:00   \n",
       "0           0  244044000  PRINSENGRACHT   366252  2019-01-30T22:15:00   \n",
       "\n",
       "                     4  5                   6    7     8  ... 12  13   14  \\\n",
       "1  2019-01-27T20:11:00  1        Bulk Carrier  150  TYNE  ...  1   0    0   \n",
       "0  2019-01-30T22:15:00  0  Heavy Load Carrier  150  TYNE  ...  0   0  609   \n",
       "\n",
       "    15   16     17     18   19             20         21  \n",
       "1    0    0    NaN  15746  NaN       DRY BULK   HANDYMAX  \n",
       "0  133  151  232.0   2917  0.0  DRY BREAKBULK  HANDYSIZE  \n",
       "\n",
       "[2 rows x 23 columns]"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ex2 = pd.DataFrame(ex2)\n",
    "ex2.to_csv('ex2.csv')\n",
    "ex2 = pd.read_csv('ex2.csv')\n",
    "ex2 = ex2.loc[::-1]\n",
    "ex2.to_json('ex2.json')\n",
    "ex2 = pd.read_json('ex2.json')\n",
    "ex2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "e0d71e12",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>...</th>\n",
       "      <th>12</th>\n",
       "      <th>13</th>\n",
       "      <th>14</th>\n",
       "      <th>15</th>\n",
       "      <th>16</th>\n",
       "      <th>17</th>\n",
       "      <th>18</th>\n",
       "      <th>19</th>\n",
       "      <th>20</th>\n",
       "      <th>21</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>17</td>\n",
       "      <td>209184000</td>\n",
       "      <td>IMAVERE</td>\n",
       "      <td>732904</td>\n",
       "      <td>2019-01-02T19:29:00</td>\n",
       "      <td>2019-01-02T19:29:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10628</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>16</td>\n",
       "      <td>353941000</td>\n",
       "      <td>NORD PACIFIC</td>\n",
       "      <td>5202902</td>\n",
       "      <td>2019-01-04T13:24:00</td>\n",
       "      <td>2019-01-04T13:24:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9747</td>\n",
       "      <td>115</td>\n",
       "      <td>152</td>\n",
       "      <td>3972.0</td>\n",
       "      <td>55352</td>\n",
       "      <td>0.0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>PANAMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>15</td>\n",
       "      <td>370395000</td>\n",
       "      <td>FLORINDA</td>\n",
       "      <td>458519</td>\n",
       "      <td>2019-01-05T01:28:00</td>\n",
       "      <td>2019-01-05T01:28:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40685</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>14</td>\n",
       "      <td>636009548</td>\n",
       "      <td>YEOMAN BANK</td>\n",
       "      <td>752608</td>\n",
       "      <td>2019-01-05T02:12:00</td>\n",
       "      <td>2019-01-05T02:12:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Self Discharging Bulk Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>479</td>\n",
       "      <td>118</td>\n",
       "      <td>150</td>\n",
       "      <td>724.0</td>\n",
       "      <td>3176</td>\n",
       "      <td>1.0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13</td>\n",
       "      <td>373774000</td>\n",
       "      <td>TEAL BULKER</td>\n",
       "      <td>465572</td>\n",
       "      <td>2019-01-05T14:49:00</td>\n",
       "      <td>2019-01-05T14:49:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10656</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12</td>\n",
       "      <td>636009548</td>\n",
       "      <td>YEOMAN BANK</td>\n",
       "      <td>752608</td>\n",
       "      <td>2019-01-07T03:03:00</td>\n",
       "      <td>2019-01-07T03:03:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Self Discharging Bulk Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6107</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11</td>\n",
       "      <td>636017904</td>\n",
       "      <td>EXPLORER</td>\n",
       "      <td>302906</td>\n",
       "      <td>2019-01-07T03:59:00</td>\n",
       "      <td>2019-01-07T03:59:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4290</td>\n",
       "      <td>126</td>\n",
       "      <td>164</td>\n",
       "      <td>462.0</td>\n",
       "      <td>21596</td>\n",
       "      <td>0.0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10</td>\n",
       "      <td>353941000</td>\n",
       "      <td>NORD PACIFIC</td>\n",
       "      <td>5202902</td>\n",
       "      <td>2019-01-09T18:33:00</td>\n",
       "      <td>2019-01-09T18:33:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>62861</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>PANAMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>9</td>\n",
       "      <td>636017904</td>\n",
       "      <td>EXPLORER</td>\n",
       "      <td>302906</td>\n",
       "      <td>2019-01-10T12:16:00</td>\n",
       "      <td>2019-01-10T12:16:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26413</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>219617000</td>\n",
       "      <td>EMMA BULKER</td>\n",
       "      <td>409819</td>\n",
       "      <td>2019-01-11T05:26:00</td>\n",
       "      <td>2019-01-11T05:26:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5351</td>\n",
       "      <td>109</td>\n",
       "      <td>155</td>\n",
       "      <td>514.0</td>\n",
       "      <td>28028</td>\n",
       "      <td>0.0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>258882000</td>\n",
       "      <td>HOEGH TRADER</td>\n",
       "      <td>312911</td>\n",
       "      <td>2019-01-12T17:21:00</td>\n",
       "      <td>2019-01-12T17:21:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Vehicles Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>299</td>\n",
       "      <td>146</td>\n",
       "      <td>177</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1230</td>\n",
       "      <td>0.0</td>\n",
       "      <td>RO/RO</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>258882000</td>\n",
       "      <td>HOEGH TRADER</td>\n",
       "      <td>312911</td>\n",
       "      <td>2019-01-14T16:06:00</td>\n",
       "      <td>2019-01-14T16:06:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Vehicles Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4035</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RO/RO</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>219617000</td>\n",
       "      <td>EMMA BULKER</td>\n",
       "      <td>409819</td>\n",
       "      <td>2019-01-14T18:50:00</td>\n",
       "      <td>2019-01-14T18:50:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>33152</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>355922000</td>\n",
       "      <td>GREEN GEM</td>\n",
       "      <td>5748751</td>\n",
       "      <td>2019-01-15T21:27:00</td>\n",
       "      <td>2019-01-15T21:27:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4026</td>\n",
       "      <td>111</td>\n",
       "      <td>154</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21378</td>\n",
       "      <td>4026.0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>257392000</td>\n",
       "      <td>BETTY KNUTSEN</td>\n",
       "      <td>306511</td>\n",
       "      <td>2019-01-17T16:06:00</td>\n",
       "      <td>2019-01-17T16:06:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Shuttle Tanker</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>32</td>\n",
       "      <td>51</td>\n",
       "      <td>91</td>\n",
       "      <td>21.0</td>\n",
       "      <td>397</td>\n",
       "      <td>0.0</td>\n",
       "      <td>WET BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>257392000</td>\n",
       "      <td>BETTY KNUTSEN</td>\n",
       "      <td>306511</td>\n",
       "      <td>2019-01-18T17:17:00</td>\n",
       "      <td>2019-01-18T17:17:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Shuttle Tanker</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>WET BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>355922000</td>\n",
       "      <td>GREEN GEM</td>\n",
       "      <td>5748751</td>\n",
       "      <td>2019-01-19T05:26:00</td>\n",
       "      <td>2019-01-19T05:26:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26177</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>212967000</td>\n",
       "      <td>SHEILA</td>\n",
       "      <td>3819695</td>\n",
       "      <td>2019-01-19T08:08:00</td>\n",
       "      <td>2019-01-19T08:08:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>711</td>\n",
       "      <td>122</td>\n",
       "      <td>156</td>\n",
       "      <td>11.0</td>\n",
       "      <td>3503</td>\n",
       "      <td>0.0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>212967000</td>\n",
       "      <td>SHEILA</td>\n",
       "      <td>3819695</td>\n",
       "      <td>2019-01-27T20:11:00</td>\n",
       "      <td>2019-01-27T20:11:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15746</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>244044000</td>\n",
       "      <td>PRINSENGRACHT</td>\n",
       "      <td>366252</td>\n",
       "      <td>2019-01-30T22:15:00</td>\n",
       "      <td>2019-01-30T22:15:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Heavy Load Carrier</td>\n",
       "      <td>150</td>\n",
       "      <td>TYNE</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>609</td>\n",
       "      <td>133</td>\n",
       "      <td>151</td>\n",
       "      <td>232.0</td>\n",
       "      <td>2917</td>\n",
       "      <td>0.0</td>\n",
       "      <td>DRY BREAKBULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Unnamed: 0          0              1        2                    3  \\\n",
       "17          17  209184000        IMAVERE   732904  2019-01-02T19:29:00   \n",
       "16          16  353941000   NORD PACIFIC  5202902  2019-01-04T13:24:00   \n",
       "15          15  370395000       FLORINDA   458519  2019-01-05T01:28:00   \n",
       "14          14  636009548    YEOMAN BANK   752608  2019-01-05T02:12:00   \n",
       "13          13  373774000    TEAL BULKER   465572  2019-01-05T14:49:00   \n",
       "12          12  636009548    YEOMAN BANK   752608  2019-01-07T03:03:00   \n",
       "11          11  636017904       EXPLORER   302906  2019-01-07T03:59:00   \n",
       "10          10  353941000   NORD PACIFIC  5202902  2019-01-09T18:33:00   \n",
       "9            9  636017904       EXPLORER   302906  2019-01-10T12:16:00   \n",
       "8            8  219617000    EMMA BULKER   409819  2019-01-11T05:26:00   \n",
       "7            7  258882000   HOEGH TRADER   312911  2019-01-12T17:21:00   \n",
       "6            6  258882000   HOEGH TRADER   312911  2019-01-14T16:06:00   \n",
       "5            5  219617000    EMMA BULKER   409819  2019-01-14T18:50:00   \n",
       "4            4  355922000      GREEN GEM  5748751  2019-01-15T21:27:00   \n",
       "3            3  257392000  BETTY KNUTSEN   306511  2019-01-17T16:06:00   \n",
       "2            2  257392000  BETTY KNUTSEN   306511  2019-01-18T17:17:00   \n",
       "1            1  355922000      GREEN GEM  5748751  2019-01-19T05:26:00   \n",
       "0            0  212967000         SHEILA  3819695  2019-01-19T08:08:00   \n",
       "1            1  212967000         SHEILA  3819695  2019-01-27T20:11:00   \n",
       "0            0  244044000  PRINSENGRACHT   366252  2019-01-30T22:15:00   \n",
       "\n",
       "                      4  5                              6    7     8  ... 12  \\\n",
       "17  2019-01-02T19:29:00  1                   Bulk Carrier  150  TYNE  ...  0   \n",
       "16  2019-01-04T13:24:00  0                   Bulk Carrier  150  TYNE  ...  0   \n",
       "15  2019-01-05T01:28:00  1                   Bulk Carrier  150  TYNE  ...  0   \n",
       "14  2019-01-05T02:12:00  0  Self Discharging Bulk Carrier  150  TYNE  ...  0   \n",
       "13  2019-01-05T14:49:00  1                   Bulk Carrier  150  TYNE  ...  1   \n",
       "12  2019-01-07T03:03:00  1  Self Discharging Bulk Carrier  150  TYNE  ...  2   \n",
       "11  2019-01-07T03:59:00  0                   Bulk Carrier  150  TYNE  ...  0   \n",
       "10  2019-01-09T18:33:00  1                   Bulk Carrier  150  TYNE  ...  2   \n",
       "9   2019-01-10T12:16:00  1                   Bulk Carrier  150  TYNE  ...  2   \n",
       "8   2019-01-11T05:26:00  0                   Bulk Carrier  150  TYNE  ...  0   \n",
       "7   2019-01-12T17:21:00  0               Vehicles Carrier  150  TYNE  ...  0   \n",
       "6   2019-01-14T16:06:00  1               Vehicles Carrier  150  TYNE  ...  0   \n",
       "5   2019-01-14T18:50:00  1                   Bulk Carrier  150  TYNE  ...  2   \n",
       "4   2019-01-15T21:27:00  0                   Bulk Carrier  150  TYNE  ...  0   \n",
       "3   2019-01-17T16:06:00  0                 Shuttle Tanker  150  TYNE  ...  0   \n",
       "2   2019-01-18T17:17:00  1                 Shuttle Tanker  150  TYNE  ...  4   \n",
       "1   2019-01-19T05:26:00  1                   Bulk Carrier  150  TYNE  ...  2   \n",
       "0   2019-01-19T08:08:00  0                   Bulk Carrier  150  TYNE  ...  0   \n",
       "1   2019-01-27T20:11:00  1                   Bulk Carrier  150  TYNE  ...  1   \n",
       "0   2019-01-30T22:15:00  0             Heavy Load Carrier  150  TYNE  ...  0   \n",
       "\n",
       "    13    14   15   16      17     18      19             20         21  \n",
       "17   0     0    0    0     NaN  10628     NaN       DRY BULK  HANDYSIZE  \n",
       "16   0  9747  115  152  3972.0  55352     0.0       DRY BULK    PANAMAX  \n",
       "15   0     0    0    0     NaN  40685     NaN       DRY BULK   HANDYMAX  \n",
       "14   0   479  118  150   724.0   3176     1.0       DRY BULK   HANDYMAX  \n",
       "13   0     0    0    0     NaN  10656     NaN       DRY BULK   HANDYMAX  \n",
       "12   0     0    0    0     NaN   6107     NaN       DRY BULK   HANDYMAX  \n",
       "11   0  4290  126  164   462.0  21596     0.0       DRY BULK  HANDYSIZE  \n",
       "10   0     0    0    0     NaN  62861     NaN       DRY BULK    PANAMAX  \n",
       "9    0     0    0    0     NaN  26413     NaN       DRY BULK  HANDYSIZE  \n",
       "8    0  5351  109  155   514.0  28028     0.0       DRY BULK  HANDYSIZE  \n",
       "7    0   299  146  177    19.0   1230     0.0          RO/RO       None  \n",
       "6    0     0    0    0     NaN   4035     NaN          RO/RO       None  \n",
       "5    0     0    0    0     NaN  33152     NaN       DRY BULK  HANDYSIZE  \n",
       "4    0  4026  111  154     0.0  21378  4026.0       DRY BULK  HANDYSIZE  \n",
       "3    0    32   51   91    21.0    397     0.0       WET BULK  HANDYSIZE  \n",
       "2    0     0    0    0     NaN   1908     NaN       WET BULK  HANDYSIZE  \n",
       "1    0     0    0    0     NaN  26177     NaN       DRY BULK  HANDYSIZE  \n",
       "0    0   711  122  156    11.0   3503     0.0       DRY BULK   HANDYMAX  \n",
       "1    0     0    0    0     NaN  15746     NaN       DRY BULK   HANDYMAX  \n",
       "0    0   609  133  151   232.0   2917     0.0  DRY BREAKBULK  HANDYSIZE  \n",
       "\n",
       "[20 rows x 23 columns]"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ex = ex1.append(ex2)\n",
    "ex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "f5c11a48",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>NAME</th>\n",
       "      <th>UTCTIME</th>\n",
       "      <th>MOVE</th>\n",
       "      <th>TYPE</th>\n",
       "      <th>DRAUGHT</th>\n",
       "      <th>LOAD_STATUS</th>\n",
       "      <th>PORT_OPERATION</th>\n",
       "      <th>DISTANCE_TRAVELLED</th>\n",
       "      <th>COMFLEET</th>\n",
       "      <th>SHIPCLASS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>17</td>\n",
       "      <td>IMAVERE</td>\n",
       "      <td>2019-01-02T19:29:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>62</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>16</td>\n",
       "      <td>NORD PACIFIC</td>\n",
       "      <td>2019-01-04T13:24:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>119</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>9747</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>PANAMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>15</td>\n",
       "      <td>FLORINDA</td>\n",
       "      <td>2019-01-05T01:28:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>63</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>14</td>\n",
       "      <td>YEOMAN BANK</td>\n",
       "      <td>2019-01-05T02:12:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Self Discharging Bulk Carrier</td>\n",
       "      <td>116</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>479</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>13</td>\n",
       "      <td>TEAL BULKER</td>\n",
       "      <td>2019-01-05T14:49:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>118</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>12</td>\n",
       "      <td>YEOMAN BANK</td>\n",
       "      <td>2019-01-07T03:03:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Self Discharging Bulk Carrier</td>\n",
       "      <td>68</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>11</td>\n",
       "      <td>EXPLORER</td>\n",
       "      <td>2019-01-07T03:59:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>82</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>4290</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10</td>\n",
       "      <td>NORD PACIFIC</td>\n",
       "      <td>2019-01-09T18:33:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>69</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>PANAMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>EXPLORER</td>\n",
       "      <td>2019-01-10T12:16:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>58</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>8</td>\n",
       "      <td>EMMA BULKER</td>\n",
       "      <td>2019-01-11T05:26:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>96</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>5351</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>7</td>\n",
       "      <td>HOEGH TRADER</td>\n",
       "      <td>2019-01-12T17:21:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Vehicles Carrier</td>\n",
       "      <td>89</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>299</td>\n",
       "      <td>RO/RO</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>6</td>\n",
       "      <td>HOEGH TRADER</td>\n",
       "      <td>2019-01-14T16:06:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Vehicles Carrier</td>\n",
       "      <td>81</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>RO/RO</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>5</td>\n",
       "      <td>EMMA BULKER</td>\n",
       "      <td>2019-01-14T18:50:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>63</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>4</td>\n",
       "      <td>GREEN GEM</td>\n",
       "      <td>2019-01-15T21:27:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>101</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>4026</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>3</td>\n",
       "      <td>BETTY KNUTSEN</td>\n",
       "      <td>2019-01-17T16:06:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Shuttle Tanker</td>\n",
       "      <td>52</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>32</td>\n",
       "      <td>WET BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2</td>\n",
       "      <td>BETTY KNUTSEN</td>\n",
       "      <td>2019-01-18T17:17:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Shuttle Tanker</td>\n",
       "      <td>55</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>WET BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1</td>\n",
       "      <td>GREEN GEM</td>\n",
       "      <td>2019-01-19T05:26:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>64</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0</td>\n",
       "      <td>SHEILA</td>\n",
       "      <td>2019-01-19T08:08:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>87</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>711</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1</td>\n",
       "      <td>SHEILA</td>\n",
       "      <td>2019-01-27T20:11:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>121</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0</td>\n",
       "      <td>PRINSENGRACHT</td>\n",
       "      <td>2019-01-30T22:15:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Heavy Load Carrier</td>\n",
       "      <td>75</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>609</td>\n",
       "      <td>DRY BREAKBULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    index           NAME              UTCTIME  MOVE  \\\n",
       "0      17        IMAVERE  2019-01-02T19:29:00     1   \n",
       "1      16   NORD PACIFIC  2019-01-04T13:24:00     0   \n",
       "2      15       FLORINDA  2019-01-05T01:28:00     1   \n",
       "3      14    YEOMAN BANK  2019-01-05T02:12:00     0   \n",
       "4      13    TEAL BULKER  2019-01-05T14:49:00     1   \n",
       "5      12    YEOMAN BANK  2019-01-07T03:03:00     1   \n",
       "6      11       EXPLORER  2019-01-07T03:59:00     0   \n",
       "7      10   NORD PACIFIC  2019-01-09T18:33:00     1   \n",
       "8       9       EXPLORER  2019-01-10T12:16:00     1   \n",
       "9       8    EMMA BULKER  2019-01-11T05:26:00     0   \n",
       "10      7   HOEGH TRADER  2019-01-12T17:21:00     0   \n",
       "11      6   HOEGH TRADER  2019-01-14T16:06:00     1   \n",
       "12      5    EMMA BULKER  2019-01-14T18:50:00     1   \n",
       "13      4      GREEN GEM  2019-01-15T21:27:00     0   \n",
       "14      3  BETTY KNUTSEN  2019-01-17T16:06:00     0   \n",
       "15      2  BETTY KNUTSEN  2019-01-18T17:17:00     1   \n",
       "16      1      GREEN GEM  2019-01-19T05:26:00     1   \n",
       "17      0         SHEILA  2019-01-19T08:08:00     0   \n",
       "18      1         SHEILA  2019-01-27T20:11:00     1   \n",
       "19      0  PRINSENGRACHT  2019-01-30T22:15:00     0   \n",
       "\n",
       "                             TYPE  DRAUGHT  LOAD_STATUS  PORT_OPERATION  \\\n",
       "0                    Bulk Carrier       62          0.0               0   \n",
       "1                    Bulk Carrier      119          3.0               0   \n",
       "2                    Bulk Carrier       63          0.0               0   \n",
       "3   Self Discharging Bulk Carrier      116          3.0               0   \n",
       "4                    Bulk Carrier      118          3.0               1   \n",
       "5   Self Discharging Bulk Carrier       68          1.0               2   \n",
       "6                    Bulk Carrier       82          2.0               0   \n",
       "7                    Bulk Carrier       69          1.0               2   \n",
       "8                    Bulk Carrier       58          NaN               2   \n",
       "9                    Bulk Carrier       96          3.0               0   \n",
       "10               Vehicles Carrier       89          0.0               0   \n",
       "11               Vehicles Carrier       81          0.0               0   \n",
       "12                   Bulk Carrier       63          1.0               2   \n",
       "13                   Bulk Carrier      101          3.0               0   \n",
       "14                 Shuttle Tanker       52          1.0               0   \n",
       "15                 Shuttle Tanker       55          1.0               4   \n",
       "16                   Bulk Carrier       64          1.0               2   \n",
       "17                   Bulk Carrier       87          1.0               0   \n",
       "18                   Bulk Carrier      121          3.0               1   \n",
       "19             Heavy Load Carrier       75          2.0               0   \n",
       "\n",
       "    DISTANCE_TRAVELLED       COMFLEET  SHIPCLASS  \n",
       "0                    0       DRY BULK  HANDYSIZE  \n",
       "1                 9747       DRY BULK    PANAMAX  \n",
       "2                    0       DRY BULK   HANDYMAX  \n",
       "3                  479       DRY BULK   HANDYMAX  \n",
       "4                    0       DRY BULK   HANDYMAX  \n",
       "5                    0       DRY BULK   HANDYMAX  \n",
       "6                 4290       DRY BULK  HANDYSIZE  \n",
       "7                    0       DRY BULK    PANAMAX  \n",
       "8                    0       DRY BULK  HANDYSIZE  \n",
       "9                 5351       DRY BULK  HANDYSIZE  \n",
       "10                 299          RO/RO       None  \n",
       "11                   0          RO/RO       None  \n",
       "12                   0       DRY BULK  HANDYSIZE  \n",
       "13                4026       DRY BULK  HANDYSIZE  \n",
       "14                  32       WET BULK  HANDYSIZE  \n",
       "15                   0       WET BULK  HANDYSIZE  \n",
       "16                   0       DRY BULK  HANDYSIZE  \n",
       "17                 711       DRY BULK   HANDYMAX  \n",
       "18                   0       DRY BULK   HANDYMAX  \n",
       "19                 609  DRY BREAKBULK  HANDYSIZE  "
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exJan = ex[['1','4','5','6','10','11','12','14','20','21']]\n",
    "exJan.columns = ['NAME','UTCTIME','MOVE','TYPE','DRAUGHT','LOAD_STATUS','PORT_OPERATION','DISTANCE_TRAVELLED','COMFLEET','SHIPCLASS']\n",
    "exJan = exJan.reset_index()\n",
    "exJan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "id": "fe19e0b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "exJan.to_json('190101-190131_Ex.json')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "65b7a24d",
   "metadata": {},
   "outputs": [],
   "source": [
    "os.chdir(\"E:\\\\20190923 Newcastle-M.Res\\\\OneDrive - Newcastle University\\\\21_22_autumn\\\\211018\\\\code\\\\data\\\\vesseldata\")\n",
    "dEx = pd.DataFrame(pd.read_json('190101-190131_Ex.json'))  #loading json data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2d149974",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>NAME</th>\n",
       "      <th>UTCTIME</th>\n",
       "      <th>MOVE</th>\n",
       "      <th>TYPE</th>\n",
       "      <th>DRAUGHT</th>\n",
       "      <th>LOAD_STATUS</th>\n",
       "      <th>PORT_OPERATION</th>\n",
       "      <th>DISTANCE_TRAVELLED</th>\n",
       "      <th>COMFLEET</th>\n",
       "      <th>SHIPCLASS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>17</td>\n",
       "      <td>IMAVERE</td>\n",
       "      <td>2019-01-02T19:29:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>62</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>16</td>\n",
       "      <td>NORD PACIFIC</td>\n",
       "      <td>2019-01-04T13:24:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>119</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>9747</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>PANAMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>15</td>\n",
       "      <td>FLORINDA</td>\n",
       "      <td>2019-01-05T01:28:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>63</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>14</td>\n",
       "      <td>YEOMAN BANK</td>\n",
       "      <td>2019-01-05T02:12:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Self Discharging Bulk Carrier</td>\n",
       "      <td>116</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>479</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>13</td>\n",
       "      <td>TEAL BULKER</td>\n",
       "      <td>2019-01-05T14:49:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>118</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>12</td>\n",
       "      <td>YEOMAN BANK</td>\n",
       "      <td>2019-01-07T03:03:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Self Discharging Bulk Carrier</td>\n",
       "      <td>68</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>11</td>\n",
       "      <td>EXPLORER</td>\n",
       "      <td>2019-01-07T03:59:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>82</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>4290</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10</td>\n",
       "      <td>NORD PACIFIC</td>\n",
       "      <td>2019-01-09T18:33:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>69</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>PANAMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>EXPLORER</td>\n",
       "      <td>2019-01-10T12:16:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>58</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>8</td>\n",
       "      <td>EMMA BULKER</td>\n",
       "      <td>2019-01-11T05:26:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>96</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>5351</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>7</td>\n",
       "      <td>HOEGH TRADER</td>\n",
       "      <td>2019-01-12T17:21:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Vehicles Carrier</td>\n",
       "      <td>89</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>299</td>\n",
       "      <td>RO/RO</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>6</td>\n",
       "      <td>HOEGH TRADER</td>\n",
       "      <td>2019-01-14T16:06:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Vehicles Carrier</td>\n",
       "      <td>81</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>RO/RO</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>5</td>\n",
       "      <td>EMMA BULKER</td>\n",
       "      <td>2019-01-14T18:50:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>63</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>4</td>\n",
       "      <td>GREEN GEM</td>\n",
       "      <td>2019-01-15T21:27:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>101</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>4026</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>3</td>\n",
       "      <td>BETTY KNUTSEN</td>\n",
       "      <td>2019-01-17T16:06:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Shuttle Tanker</td>\n",
       "      <td>52</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>32</td>\n",
       "      <td>WET BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2</td>\n",
       "      <td>BETTY KNUTSEN</td>\n",
       "      <td>2019-01-18T17:17:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Shuttle Tanker</td>\n",
       "      <td>55</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>WET BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1</td>\n",
       "      <td>GREEN GEM</td>\n",
       "      <td>2019-01-19T05:26:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>64</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0</td>\n",
       "      <td>SHEILA</td>\n",
       "      <td>2019-01-19T08:08:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>87</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>711</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1</td>\n",
       "      <td>SHEILA</td>\n",
       "      <td>2019-01-27T20:11:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>121</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0</td>\n",
       "      <td>PRINSENGRACHT</td>\n",
       "      <td>2019-01-30T22:15:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Heavy Load Carrier</td>\n",
       "      <td>75</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>609</td>\n",
       "      <td>DRY BREAKBULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    index           NAME              UTCTIME  MOVE  \\\n",
       "0      17        IMAVERE  2019-01-02T19:29:00     1   \n",
       "1      16   NORD PACIFIC  2019-01-04T13:24:00     0   \n",
       "2      15       FLORINDA  2019-01-05T01:28:00     1   \n",
       "3      14    YEOMAN BANK  2019-01-05T02:12:00     0   \n",
       "4      13    TEAL BULKER  2019-01-05T14:49:00     1   \n",
       "5      12    YEOMAN BANK  2019-01-07T03:03:00     1   \n",
       "6      11       EXPLORER  2019-01-07T03:59:00     0   \n",
       "7      10   NORD PACIFIC  2019-01-09T18:33:00     1   \n",
       "8       9       EXPLORER  2019-01-10T12:16:00     1   \n",
       "9       8    EMMA BULKER  2019-01-11T05:26:00     0   \n",
       "10      7   HOEGH TRADER  2019-01-12T17:21:00     0   \n",
       "11      6   HOEGH TRADER  2019-01-14T16:06:00     1   \n",
       "12      5    EMMA BULKER  2019-01-14T18:50:00     1   \n",
       "13      4      GREEN GEM  2019-01-15T21:27:00     0   \n",
       "14      3  BETTY KNUTSEN  2019-01-17T16:06:00     0   \n",
       "15      2  BETTY KNUTSEN  2019-01-18T17:17:00     1   \n",
       "16      1      GREEN GEM  2019-01-19T05:26:00     1   \n",
       "17      0         SHEILA  2019-01-19T08:08:00     0   \n",
       "18      1         SHEILA  2019-01-27T20:11:00     1   \n",
       "19      0  PRINSENGRACHT  2019-01-30T22:15:00     0   \n",
       "\n",
       "                             TYPE  DRAUGHT  LOAD_STATUS  PORT_OPERATION  \\\n",
       "0                    Bulk Carrier       62          0.0               0   \n",
       "1                    Bulk Carrier      119          3.0               0   \n",
       "2                    Bulk Carrier       63          0.0               0   \n",
       "3   Self Discharging Bulk Carrier      116          3.0               0   \n",
       "4                    Bulk Carrier      118          3.0               1   \n",
       "5   Self Discharging Bulk Carrier       68          1.0               2   \n",
       "6                    Bulk Carrier       82          2.0               0   \n",
       "7                    Bulk Carrier       69          1.0               2   \n",
       "8                    Bulk Carrier       58          NaN               2   \n",
       "9                    Bulk Carrier       96          3.0               0   \n",
       "10               Vehicles Carrier       89          0.0               0   \n",
       "11               Vehicles Carrier       81          0.0               0   \n",
       "12                   Bulk Carrier       63          1.0               2   \n",
       "13                   Bulk Carrier      101          3.0               0   \n",
       "14                 Shuttle Tanker       52          1.0               0   \n",
       "15                 Shuttle Tanker       55          1.0               4   \n",
       "16                   Bulk Carrier       64          1.0               2   \n",
       "17                   Bulk Carrier       87          1.0               0   \n",
       "18                   Bulk Carrier      121          3.0               1   \n",
       "19             Heavy Load Carrier       75          2.0               0   \n",
       "\n",
       "    DISTANCE_TRAVELLED       COMFLEET  SHIPCLASS  \n",
       "0                    0       DRY BULK  HANDYSIZE  \n",
       "1                 9747       DRY BULK    PANAMAX  \n",
       "2                    0       DRY BULK   HANDYMAX  \n",
       "3                  479       DRY BULK   HANDYMAX  \n",
       "4                    0       DRY BULK   HANDYMAX  \n",
       "5                    0       DRY BULK   HANDYMAX  \n",
       "6                 4290       DRY BULK  HANDYSIZE  \n",
       "7                    0       DRY BULK    PANAMAX  \n",
       "8                    0       DRY BULK  HANDYSIZE  \n",
       "9                 5351       DRY BULK  HANDYSIZE  \n",
       "10                 299          RO/RO       None  \n",
       "11                   0          RO/RO       None  \n",
       "12                   0       DRY BULK  HANDYSIZE  \n",
       "13                4026       DRY BULK  HANDYSIZE  \n",
       "14                  32       WET BULK  HANDYSIZE  \n",
       "15                   0       WET BULK  HANDYSIZE  \n",
       "16                   0       DRY BULK  HANDYSIZE  \n",
       "17                 711       DRY BULK   HANDYMAX  \n",
       "18                   0       DRY BULK   HANDYMAX  \n",
       "19                 609  DRY BREAKBULK  HANDYSIZE  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dEx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "f74d1415",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "ddex = dEx[(dEx['COMFLEET'] == 'DRY BULK')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "cc557026",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>17</td>\n",
       "      <td>IMAVERE</td>\n",
       "      <td>2019-01-02T19:29:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>62</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>16</td>\n",
       "      <td>NORD PACIFIC</td>\n",
       "      <td>2019-01-04T13:24:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>119</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>9747</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>PANAMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>15</td>\n",
       "      <td>FLORINDA</td>\n",
       "      <td>2019-01-05T01:28:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>63</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>14</td>\n",
       "      <td>YEOMAN BANK</td>\n",
       "      <td>2019-01-05T02:12:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Self Discharging Bulk Carrier</td>\n",
       "      <td>116</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>479</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>13</td>\n",
       "      <td>TEAL BULKER</td>\n",
       "      <td>2019-01-05T14:49:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>118</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>12</td>\n",
       "      <td>YEOMAN BANK</td>\n",
       "      <td>2019-01-07T03:03:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Self Discharging Bulk Carrier</td>\n",
       "      <td>68</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>11</td>\n",
       "      <td>EXPLORER</td>\n",
       "      <td>2019-01-07T03:59:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>82</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>4290</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10</td>\n",
       "      <td>NORD PACIFIC</td>\n",
       "      <td>2019-01-09T18:33:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>69</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>PANAMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>EXPLORER</td>\n",
       "      <td>2019-01-10T12:16:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>58</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>8</td>\n",
       "      <td>EMMA BULKER</td>\n",
       "      <td>2019-01-11T05:26:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>96</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>5351</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>5</td>\n",
       "      <td>EMMA BULKER</td>\n",
       "      <td>2019-01-14T18:50:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>63</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>4</td>\n",
       "      <td>GREEN GEM</td>\n",
       "      <td>2019-01-15T21:27:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>101</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>4026</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1</td>\n",
       "      <td>GREEN GEM</td>\n",
       "      <td>2019-01-19T05:26:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>64</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0</td>\n",
       "      <td>SHEILA</td>\n",
       "      <td>2019-01-19T08:08:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>87</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>711</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1</td>\n",
       "      <td>SHEILA</td>\n",
       "      <td>2019-01-27T20:11:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>121</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    index          NAME              UTCTIME  MOVE  \\\n",
       "0      17       IMAVERE  2019-01-02T19:29:00     1   \n",
       "1      16  NORD PACIFIC  2019-01-04T13:24:00     0   \n",
       "2      15      FLORINDA  2019-01-05T01:28:00     1   \n",
       "3      14   YEOMAN BANK  2019-01-05T02:12:00     0   \n",
       "4      13   TEAL BULKER  2019-01-05T14:49:00     1   \n",
       "5      12   YEOMAN BANK  2019-01-07T03:03:00     1   \n",
       "6      11      EXPLORER  2019-01-07T03:59:00     0   \n",
       "7      10  NORD PACIFIC  2019-01-09T18:33:00     1   \n",
       "8       9      EXPLORER  2019-01-10T12:16:00     1   \n",
       "9       8   EMMA BULKER  2019-01-11T05:26:00     0   \n",
       "12      5   EMMA BULKER  2019-01-14T18:50:00     1   \n",
       "13      4     GREEN GEM  2019-01-15T21:27:00     0   \n",
       "16      1     GREEN GEM  2019-01-19T05:26:00     1   \n",
       "17      0        SHEILA  2019-01-19T08:08:00     0   \n",
       "18      1        SHEILA  2019-01-27T20:11:00     1   \n",
       "\n",
       "                             TYPE  DRAUGHT  LOAD_STATUS  PORT_OPERATION  \\\n",
       "0                    Bulk Carrier       62          0.0               0   \n",
       "1                    Bulk Carrier      119          3.0               0   \n",
       "2                    Bulk Carrier       63          0.0               0   \n",
       "3   Self Discharging Bulk Carrier      116          3.0               0   \n",
       "4                    Bulk Carrier      118          3.0               1   \n",
       "5   Self Discharging Bulk Carrier       68          1.0               2   \n",
       "6                    Bulk Carrier       82          2.0               0   \n",
       "7                    Bulk Carrier       69          1.0               2   \n",
       "8                    Bulk Carrier       58          NaN               2   \n",
       "9                    Bulk Carrier       96          3.0               0   \n",
       "12                   Bulk Carrier       63          1.0               2   \n",
       "13                   Bulk Carrier      101          3.0               0   \n",
       "16                   Bulk Carrier       64          1.0               2   \n",
       "17                   Bulk Carrier       87          1.0               0   \n",
       "18                   Bulk Carrier      121          3.0               1   \n",
       "\n",
       "    DISTANCE_TRAVELLED  COMFLEET  SHIPCLASS  \n",
       "0                    0  DRY BULK  HANDYSIZE  \n",
       "1                 9747  DRY BULK    PANAMAX  \n",
       "2                    0  DRY BULK   HANDYMAX  \n",
       "3                  479  DRY BULK   HANDYMAX  \n",
       "4                    0  DRY BULK   HANDYMAX  \n",
       "5                    0  DRY BULK   HANDYMAX  \n",
       "6                 4290  DRY BULK  HANDYSIZE  \n",
       "7                    0  DRY BULK    PANAMAX  \n",
       "8                    0  DRY BULK  HANDYSIZE  \n",
       "9                 5351  DRY BULK  HANDYSIZE  \n",
       "12                   0  DRY BULK  HANDYSIZE  \n",
       "13                4026  DRY BULK  HANDYSIZE  \n",
       "16                   0  DRY BULK  HANDYSIZE  \n",
       "17                 711  DRY BULK   HANDYMAX  \n",
       "18                   0  DRY BULK   HANDYMAX  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ddex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "26bec9ec",
   "metadata": {},
   "outputs": [],
   "source": [
    "dddex = pd.merge(ddex,dfTon, on=['NAME'], how='left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "1a3420b9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>NAME</th>\n",
       "      <th>UTCTIME</th>\n",
       "      <th>MOVE</th>\n",
       "      <th>TYPE</th>\n",
       "      <th>DRAUGHT</th>\n",
       "      <th>LOAD_STATUS</th>\n",
       "      <th>PORT_OPERATION</th>\n",
       "      <th>DISTANCE_TRAVELLED</th>\n",
       "      <th>COMFLEET</th>\n",
       "      <th>SHIPCLASS</th>\n",
       "      <th>GT</th>\n",
       "      <th>DWT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>17</td>\n",
       "      <td>IMAVERE</td>\n",
       "      <td>2019-01-02T19:29:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>62</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "      <td>22746.0</td>\n",
       "      <td>36746.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>16</td>\n",
       "      <td>NORD PACIFIC</td>\n",
       "      <td>2019-01-04T13:24:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>119</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>9747</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>PANAMAX</td>\n",
       "      <td>35035.0</td>\n",
       "      <td>61221.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>15</td>\n",
       "      <td>FLORINDA</td>\n",
       "      <td>2019-01-05T01:28:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>63</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "      <td>32415.0</td>\n",
       "      <td>58600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>14</td>\n",
       "      <td>YEOMAN BANK</td>\n",
       "      <td>2019-01-05T02:12:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Self Discharging Bulk Carrier</td>\n",
       "      <td>116</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>479</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>13</td>\n",
       "      <td>TEAL BULKER</td>\n",
       "      <td>2019-01-05T14:49:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>118</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "      <td>32370.0</td>\n",
       "      <td>57903.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>12</td>\n",
       "      <td>YEOMAN BANK</td>\n",
       "      <td>2019-01-07T03:03:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Self Discharging Bulk Carrier</td>\n",
       "      <td>68</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>11</td>\n",
       "      <td>EXPLORER</td>\n",
       "      <td>2019-01-07T03:59:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>82</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>4290</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "      <td>26449.0</td>\n",
       "      <td>47639.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10</td>\n",
       "      <td>NORD PACIFIC</td>\n",
       "      <td>2019-01-09T18:33:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>69</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>PANAMAX</td>\n",
       "      <td>35035.0</td>\n",
       "      <td>61221.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>EXPLORER</td>\n",
       "      <td>2019-01-10T12:16:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>58</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "      <td>26449.0</td>\n",
       "      <td>47639.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>8</td>\n",
       "      <td>EMMA BULKER</td>\n",
       "      <td>2019-01-11T05:26:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>96</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>5351</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "      <td>19812.0</td>\n",
       "      <td>31887.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>5</td>\n",
       "      <td>EMMA BULKER</td>\n",
       "      <td>2019-01-14T18:50:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>63</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "      <td>19812.0</td>\n",
       "      <td>31887.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>4</td>\n",
       "      <td>GREEN GEM</td>\n",
       "      <td>2019-01-15T21:27:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>101</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>4026</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "      <td>23885.0</td>\n",
       "      <td>38503.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1</td>\n",
       "      <td>GREEN GEM</td>\n",
       "      <td>2019-01-19T05:26:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>64</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "      <td>23885.0</td>\n",
       "      <td>38503.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0</td>\n",
       "      <td>SHEILA</td>\n",
       "      <td>2019-01-19T08:08:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>87</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>711</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "      <td>41428.0</td>\n",
       "      <td>70037.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1</td>\n",
       "      <td>SHEILA</td>\n",
       "      <td>2019-01-27T20:11:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>121</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "      <td>41428.0</td>\n",
       "      <td>70037.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    index          NAME              UTCTIME  MOVE  \\\n",
       "0      17       IMAVERE  2019-01-02T19:29:00     1   \n",
       "1      16  NORD PACIFIC  2019-01-04T13:24:00     0   \n",
       "2      15      FLORINDA  2019-01-05T01:28:00     1   \n",
       "3      14   YEOMAN BANK  2019-01-05T02:12:00     0   \n",
       "4      13   TEAL BULKER  2019-01-05T14:49:00     1   \n",
       "5      12   YEOMAN BANK  2019-01-07T03:03:00     1   \n",
       "6      11      EXPLORER  2019-01-07T03:59:00     0   \n",
       "7      10  NORD PACIFIC  2019-01-09T18:33:00     1   \n",
       "8       9      EXPLORER  2019-01-10T12:16:00     1   \n",
       "9       8   EMMA BULKER  2019-01-11T05:26:00     0   \n",
       "10      5   EMMA BULKER  2019-01-14T18:50:00     1   \n",
       "11      4     GREEN GEM  2019-01-15T21:27:00     0   \n",
       "12      1     GREEN GEM  2019-01-19T05:26:00     1   \n",
       "13      0        SHEILA  2019-01-19T08:08:00     0   \n",
       "14      1        SHEILA  2019-01-27T20:11:00     1   \n",
       "\n",
       "                             TYPE  DRAUGHT  LOAD_STATUS  PORT_OPERATION  \\\n",
       "0                    Bulk Carrier       62          0.0               0   \n",
       "1                    Bulk Carrier      119          3.0               0   \n",
       "2                    Bulk Carrier       63          0.0               0   \n",
       "3   Self Discharging Bulk Carrier      116          3.0               0   \n",
       "4                    Bulk Carrier      118          3.0               1   \n",
       "5   Self Discharging Bulk Carrier       68          1.0               2   \n",
       "6                    Bulk Carrier       82          2.0               0   \n",
       "7                    Bulk Carrier       69          1.0               2   \n",
       "8                    Bulk Carrier       58          NaN               2   \n",
       "9                    Bulk Carrier       96          3.0               0   \n",
       "10                   Bulk Carrier       63          1.0               2   \n",
       "11                   Bulk Carrier      101          3.0               0   \n",
       "12                   Bulk Carrier       64          1.0               2   \n",
       "13                   Bulk Carrier       87          1.0               0   \n",
       "14                   Bulk Carrier      121          3.0               1   \n",
       "\n",
       "    DISTANCE_TRAVELLED  COMFLEET  SHIPCLASS       GT      DWT  \n",
       "0                    0  DRY BULK  HANDYSIZE  22746.0  36746.0  \n",
       "1                 9747  DRY BULK    PANAMAX  35035.0  61221.0  \n",
       "2                    0  DRY BULK   HANDYMAX  32415.0  58600.0  \n",
       "3                  479  DRY BULK   HANDYMAX      NaN      NaN  \n",
       "4                    0  DRY BULK   HANDYMAX  32370.0  57903.0  \n",
       "5                    0  DRY BULK   HANDYMAX      NaN      NaN  \n",
       "6                 4290  DRY BULK  HANDYSIZE  26449.0  47639.0  \n",
       "7                    0  DRY BULK    PANAMAX  35035.0  61221.0  \n",
       "8                    0  DRY BULK  HANDYSIZE  26449.0  47639.0  \n",
       "9                 5351  DRY BULK  HANDYSIZE  19812.0  31887.0  \n",
       "10                   0  DRY BULK  HANDYSIZE  19812.0  31887.0  \n",
       "11                4026  DRY BULK  HANDYSIZE  23885.0  38503.0  \n",
       "12                   0  DRY BULK  HANDYSIZE  23885.0  38503.0  \n",
       "13                 711  DRY BULK   HANDYMAX  41428.0  70037.0  \n",
       "14                   0  DRY BULK   HANDYMAX  41428.0  70037.0  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dddex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "552f0f8a",
   "metadata": {},
   "outputs": [],
   "source": [
    "dddex.to_json('2019JanEx.json')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "aafcb996",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>NAME</th>\n",
       "      <th>UTCTIME</th>\n",
       "      <th>MOVE</th>\n",
       "      <th>TYPE</th>\n",
       "      <th>DRAUGHT</th>\n",
       "      <th>LOAD_STATUS</th>\n",
       "      <th>PORT_OPERATION</th>\n",
       "      <th>DISTANCE_TRAVELLED</th>\n",
       "      <th>COMFLEET</th>\n",
       "      <th>SHIPCLASS</th>\n",
       "      <th>GT</th>\n",
       "      <th>DWT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>17</td>\n",
       "      <td>IMAVERE</td>\n",
       "      <td>2019-01-02T19:29:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>62</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "      <td>22746.0</td>\n",
       "      <td>36746.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>16</td>\n",
       "      <td>NORD PACIFIC</td>\n",
       "      <td>2019-01-04T13:24:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>119</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>9747</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>PANAMAX</td>\n",
       "      <td>35035.0</td>\n",
       "      <td>61221.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>15</td>\n",
       "      <td>FLORINDA</td>\n",
       "      <td>2019-01-05T01:28:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>63</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "      <td>32415.0</td>\n",
       "      <td>58600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>14</td>\n",
       "      <td>YEOMAN BANK</td>\n",
       "      <td>2019-01-05T02:12:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Self Discharging Bulk Carrier</td>\n",
       "      <td>116</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>479</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>13</td>\n",
       "      <td>TEAL BULKER</td>\n",
       "      <td>2019-01-05T14:49:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>118</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "      <td>32370.0</td>\n",
       "      <td>57903.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>12</td>\n",
       "      <td>YEOMAN BANK</td>\n",
       "      <td>2019-01-07T03:03:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Self Discharging Bulk Carrier</td>\n",
       "      <td>68</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>11</td>\n",
       "      <td>EXPLORER</td>\n",
       "      <td>2019-01-07T03:59:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>82</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>4290</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "      <td>26449.0</td>\n",
       "      <td>47639.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10</td>\n",
       "      <td>NORD PACIFIC</td>\n",
       "      <td>2019-01-09T18:33:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>69</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>PANAMAX</td>\n",
       "      <td>35035.0</td>\n",
       "      <td>61221.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>EXPLORER</td>\n",
       "      <td>2019-01-10T12:16:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>58</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "      <td>26449.0</td>\n",
       "      <td>47639.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>8</td>\n",
       "      <td>EMMA BULKER</td>\n",
       "      <td>2019-01-11T05:26:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>96</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>5351</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "      <td>19812.0</td>\n",
       "      <td>31887.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>5</td>\n",
       "      <td>EMMA BULKER</td>\n",
       "      <td>2019-01-14T18:50:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>63</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "      <td>19812.0</td>\n",
       "      <td>31887.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>4</td>\n",
       "      <td>GREEN GEM</td>\n",
       "      <td>2019-01-15T21:27:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>101</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>4026</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "      <td>23885.0</td>\n",
       "      <td>38503.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1</td>\n",
       "      <td>GREEN GEM</td>\n",
       "      <td>2019-01-19T05:26:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>64</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "      <td>23885.0</td>\n",
       "      <td>38503.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0</td>\n",
       "      <td>SHEILA</td>\n",
       "      <td>2019-01-19T08:08:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>87</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>711</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "      <td>41428.0</td>\n",
       "      <td>70037.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1</td>\n",
       "      <td>SHEILA</td>\n",
       "      <td>2019-01-27T20:11:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>121</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "      <td>41428.0</td>\n",
       "      <td>70037.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    index          NAME              UTCTIME  MOVE  \\\n",
       "0      17       IMAVERE  2019-01-02T19:29:00     1   \n",
       "1      16  NORD PACIFIC  2019-01-04T13:24:00     0   \n",
       "2      15      FLORINDA  2019-01-05T01:28:00     1   \n",
       "3      14   YEOMAN BANK  2019-01-05T02:12:00     0   \n",
       "4      13   TEAL BULKER  2019-01-05T14:49:00     1   \n",
       "5      12   YEOMAN BANK  2019-01-07T03:03:00     1   \n",
       "6      11      EXPLORER  2019-01-07T03:59:00     0   \n",
       "7      10  NORD PACIFIC  2019-01-09T18:33:00     1   \n",
       "8       9      EXPLORER  2019-01-10T12:16:00     1   \n",
       "9       8   EMMA BULKER  2019-01-11T05:26:00     0   \n",
       "10      5   EMMA BULKER  2019-01-14T18:50:00     1   \n",
       "11      4     GREEN GEM  2019-01-15T21:27:00     0   \n",
       "12      1     GREEN GEM  2019-01-19T05:26:00     1   \n",
       "13      0        SHEILA  2019-01-19T08:08:00     0   \n",
       "14      1        SHEILA  2019-01-27T20:11:00     1   \n",
       "\n",
       "                             TYPE  DRAUGHT  LOAD_STATUS  PORT_OPERATION  \\\n",
       "0                    Bulk Carrier       62          0.0               0   \n",
       "1                    Bulk Carrier      119          3.0               0   \n",
       "2                    Bulk Carrier       63          0.0               0   \n",
       "3   Self Discharging Bulk Carrier      116          3.0               0   \n",
       "4                    Bulk Carrier      118          3.0               1   \n",
       "5   Self Discharging Bulk Carrier       68          1.0               2   \n",
       "6                    Bulk Carrier       82          2.0               0   \n",
       "7                    Bulk Carrier       69          1.0               2   \n",
       "8                    Bulk Carrier       58          NaN               2   \n",
       "9                    Bulk Carrier       96          3.0               0   \n",
       "10                   Bulk Carrier       63          1.0               2   \n",
       "11                   Bulk Carrier      101          3.0               0   \n",
       "12                   Bulk Carrier       64          1.0               2   \n",
       "13                   Bulk Carrier       87          1.0               0   \n",
       "14                   Bulk Carrier      121          3.0               1   \n",
       "\n",
       "    DISTANCE_TRAVELLED  COMFLEET  SHIPCLASS       GT      DWT  \n",
       "0                    0  DRY BULK  HANDYSIZE  22746.0  36746.0  \n",
       "1                 9747  DRY BULK    PANAMAX  35035.0  61221.0  \n",
       "2                    0  DRY BULK   HANDYMAX  32415.0  58600.0  \n",
       "3                  479  DRY BULK   HANDYMAX      NaN      NaN  \n",
       "4                    0  DRY BULK   HANDYMAX  32370.0  57903.0  \n",
       "5                    0  DRY BULK   HANDYMAX      NaN      NaN  \n",
       "6                 4290  DRY BULK  HANDYSIZE  26449.0  47639.0  \n",
       "7                    0  DRY BULK    PANAMAX  35035.0  61221.0  \n",
       "8                    0  DRY BULK  HANDYSIZE  26449.0  47639.0  \n",
       "9                 5351  DRY BULK  HANDYSIZE  19812.0  31887.0  \n",
       "10                   0  DRY BULK  HANDYSIZE  19812.0  31887.0  \n",
       "11                4026  DRY BULK  HANDYSIZE  23885.0  38503.0  \n",
       "12                   0  DRY BULK  HANDYSIZE  23885.0  38503.0  \n",
       "13                 711  DRY BULK   HANDYMAX  41428.0  70037.0  \n",
       "14                   0  DRY BULK   HANDYMAX  41428.0  70037.0  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dddex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "321e1418",
   "metadata": {},
   "outputs": [],
   "source": [
    "dddex.at[5,'GT'] = 24870"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "bf4b9602",
   "metadata": {},
   "outputs": [],
   "source": [
    "dddex.at[5,'DWT'] = 38997"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "e081828b",
   "metadata": {},
   "outputs": [],
   "source": [
    "dddex.at[3,'GT'] = 24870\n",
    "dddex.at[3,'DWT'] = 38997"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "8758820f",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>NAME</th>\n",
       "      <th>UTCTIME</th>\n",
       "      <th>MOVE</th>\n",
       "      <th>TYPE</th>\n",
       "      <th>DRAUGHT</th>\n",
       "      <th>LOAD_STATUS</th>\n",
       "      <th>PORT_OPERATION</th>\n",
       "      <th>DISTANCE_TRAVELLED</th>\n",
       "      <th>COMFLEET</th>\n",
       "      <th>SHIPCLASS</th>\n",
       "      <th>GT</th>\n",
       "      <th>DWT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>17</td>\n",
       "      <td>IMAVERE</td>\n",
       "      <td>2019-01-02T19:29:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>62</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "      <td>22746.0</td>\n",
       "      <td>36746.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>16</td>\n",
       "      <td>NORD PACIFIC</td>\n",
       "      <td>2019-01-04T13:24:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>119</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>9747</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>PANAMAX</td>\n",
       "      <td>35035.0</td>\n",
       "      <td>61221.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>15</td>\n",
       "      <td>FLORINDA</td>\n",
       "      <td>2019-01-05T01:28:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>63</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "      <td>32415.0</td>\n",
       "      <td>58600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>14</td>\n",
       "      <td>YEOMAN BANK</td>\n",
       "      <td>2019-01-05T02:12:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Self Discharging Bulk Carrier</td>\n",
       "      <td>116</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>479</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "      <td>24870.0</td>\n",
       "      <td>38997.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>13</td>\n",
       "      <td>TEAL BULKER</td>\n",
       "      <td>2019-01-05T14:49:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>118</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "      <td>32370.0</td>\n",
       "      <td>57903.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>12</td>\n",
       "      <td>YEOMAN BANK</td>\n",
       "      <td>2019-01-07T03:03:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Self Discharging Bulk Carrier</td>\n",
       "      <td>68</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "      <td>24870.0</td>\n",
       "      <td>38997.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>11</td>\n",
       "      <td>EXPLORER</td>\n",
       "      <td>2019-01-07T03:59:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>82</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>4290</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "      <td>26449.0</td>\n",
       "      <td>47639.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10</td>\n",
       "      <td>NORD PACIFIC</td>\n",
       "      <td>2019-01-09T18:33:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>69</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>PANAMAX</td>\n",
       "      <td>35035.0</td>\n",
       "      <td>61221.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>EXPLORER</td>\n",
       "      <td>2019-01-10T12:16:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>58</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "      <td>26449.0</td>\n",
       "      <td>47639.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>8</td>\n",
       "      <td>EMMA BULKER</td>\n",
       "      <td>2019-01-11T05:26:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>96</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>5351</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "      <td>19812.0</td>\n",
       "      <td>31887.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>5</td>\n",
       "      <td>EMMA BULKER</td>\n",
       "      <td>2019-01-14T18:50:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>63</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "      <td>19812.0</td>\n",
       "      <td>31887.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>4</td>\n",
       "      <td>GREEN GEM</td>\n",
       "      <td>2019-01-15T21:27:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>101</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0</td>\n",
       "      <td>4026</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "      <td>23885.0</td>\n",
       "      <td>38503.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1</td>\n",
       "      <td>GREEN GEM</td>\n",
       "      <td>2019-01-19T05:26:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>64</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYSIZE</td>\n",
       "      <td>23885.0</td>\n",
       "      <td>38503.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0</td>\n",
       "      <td>SHEILA</td>\n",
       "      <td>2019-01-19T08:08:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>87</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>711</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "      <td>41428.0</td>\n",
       "      <td>70037.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1</td>\n",
       "      <td>SHEILA</td>\n",
       "      <td>2019-01-27T20:11:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>121</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>DRY BULK</td>\n",
       "      <td>HANDYMAX</td>\n",
       "      <td>41428.0</td>\n",
       "      <td>70037.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    index          NAME              UTCTIME  MOVE  \\\n",
       "0      17       IMAVERE  2019-01-02T19:29:00     1   \n",
       "1      16  NORD PACIFIC  2019-01-04T13:24:00     0   \n",
       "2      15      FLORINDA  2019-01-05T01:28:00     1   \n",
       "3      14   YEOMAN BANK  2019-01-05T02:12:00     0   \n",
       "4      13   TEAL BULKER  2019-01-05T14:49:00     1   \n",
       "5      12   YEOMAN BANK  2019-01-07T03:03:00     1   \n",
       "6      11      EXPLORER  2019-01-07T03:59:00     0   \n",
       "7      10  NORD PACIFIC  2019-01-09T18:33:00     1   \n",
       "8       9      EXPLORER  2019-01-10T12:16:00     1   \n",
       "9       8   EMMA BULKER  2019-01-11T05:26:00     0   \n",
       "10      5   EMMA BULKER  2019-01-14T18:50:00     1   \n",
       "11      4     GREEN GEM  2019-01-15T21:27:00     0   \n",
       "12      1     GREEN GEM  2019-01-19T05:26:00     1   \n",
       "13      0        SHEILA  2019-01-19T08:08:00     0   \n",
       "14      1        SHEILA  2019-01-27T20:11:00     1   \n",
       "\n",
       "                             TYPE  DRAUGHT  LOAD_STATUS  PORT_OPERATION  \\\n",
       "0                    Bulk Carrier       62          0.0               0   \n",
       "1                    Bulk Carrier      119          3.0               0   \n",
       "2                    Bulk Carrier       63          0.0               0   \n",
       "3   Self Discharging Bulk Carrier      116          3.0               0   \n",
       "4                    Bulk Carrier      118          3.0               1   \n",
       "5   Self Discharging Bulk Carrier       68          1.0               2   \n",
       "6                    Bulk Carrier       82          2.0               0   \n",
       "7                    Bulk Carrier       69          1.0               2   \n",
       "8                    Bulk Carrier       58          NaN               2   \n",
       "9                    Bulk Carrier       96          3.0               0   \n",
       "10                   Bulk Carrier       63          1.0               2   \n",
       "11                   Bulk Carrier      101          3.0               0   \n",
       "12                   Bulk Carrier       64          1.0               2   \n",
       "13                   Bulk Carrier       87          1.0               0   \n",
       "14                   Bulk Carrier      121          3.0               1   \n",
       "\n",
       "    DISTANCE_TRAVELLED  COMFLEET  SHIPCLASS       GT      DWT  \n",
       "0                    0  DRY BULK  HANDYSIZE  22746.0  36746.0  \n",
       "1                 9747  DRY BULK    PANAMAX  35035.0  61221.0  \n",
       "2                    0  DRY BULK   HANDYMAX  32415.0  58600.0  \n",
       "3                  479  DRY BULK   HANDYMAX  24870.0  38997.0  \n",
       "4                    0  DRY BULK   HANDYMAX  32370.0  57903.0  \n",
       "5                    0  DRY BULK   HANDYMAX  24870.0  38997.0  \n",
       "6                 4290  DRY BULK  HANDYSIZE  26449.0  47639.0  \n",
       "7                    0  DRY BULK    PANAMAX  35035.0  61221.0  \n",
       "8                    0  DRY BULK  HANDYSIZE  26449.0  47639.0  \n",
       "9                 5351  DRY BULK  HANDYSIZE  19812.0  31887.0  \n",
       "10                   0  DRY BULK  HANDYSIZE  19812.0  31887.0  \n",
       "11                4026  DRY BULK  HANDYSIZE  23885.0  38503.0  \n",
       "12                   0  DRY BULK  HANDYSIZE  23885.0  38503.0  \n",
       "13                 711  DRY BULK   HANDYMAX  41428.0  70037.0  \n",
       "14                   0  DRY BULK   HANDYMAX  41428.0  70037.0  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dddex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "bd24901d",
   "metadata": {},
   "outputs": [],
   "source": [
    "dddex = dddex.drop(['index'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "02afa69b",
   "metadata": {},
   "outputs": [],
   "source": [
    "dddex.to_json('2019JanEx.json')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c330a542",
   "metadata": {},
   "source": [
    "### loading and wrangling vessel data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "6795afab",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'E:\\\\20190923 Newcastle-M.Res\\\\OneDrive - Newcastle University\\\\21_22_autumn\\\\211018\\\\code\\\\data\\\\vesseldata\\\\raw'"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.chdir(\"E:\\\\20190923 Newcastle-M.Res\\\\OneDrive - Newcastle University\\\\21_22_autumn\\\\211018\\\\code\\\\data\\\\vesseldata\\\\raw\")\n",
    "os.getcwd()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "449b807f",
   "metadata": {},
   "outputs": [],
   "source": [
    "dfJan1 = (pd.DataFrame(pd.read_json('190101-190102.json'))).loc[::-1]\n",
    "dfJan2 = (pd.DataFrame(pd.read_json('190103-190104.json'))).loc[::-1]\n",
    "dfJan3 = (pd.DataFrame(pd.read_json('190105-190120.json'))).loc[::-1]\n",
    "dfJan4 = (pd.DataFrame(pd.read_json('190121-190131.json'))).loc[::-1]\n",
    "\n",
    "dfJan = (pd.concat([dfJan1,dfJan2,dfJan3,dfJan4]))[[1,3,4,5,6]]#select useful columns\n",
    "dfJan.columns = ['NAME','LOCALTIME','UTCTIME','MOVE','TYPE'] #change column names\n",
    "#dfJan = (dfJan[dfJan['TYPE'] == 'Bulk Carrier']) #select only bul carriers and reverse row number\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "067580c7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NAME</th>\n",
       "      <th>LOCALTIME</th>\n",
       "      <th>UTCTIME</th>\n",
       "      <th>MOVE</th>\n",
       "      <th>TYPE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>PRINCESS SEAWAYS</td>\n",
       "      <td>2019-01-21T08:49:00</td>\n",
       "      <td>2019-01-21T08:49:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Ro-Ro\\/Passenger Ship</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>SAND FALCON</td>\n",
       "      <td>2019-01-21T13:12:00</td>\n",
       "      <td>2019-01-21T13:12:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Hopper Dredger</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>PRINCESS SEAWAYS</td>\n",
       "      <td>2019-01-21T17:06:00</td>\n",
       "      <td>2019-01-21T17:06:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Ro-Ro\\/Passenger Ship</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>CITY OF BARCELONA</td>\n",
       "      <td>2019-01-22T05:36:00</td>\n",
       "      <td>2019-01-22T05:36:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Vehicles Carrier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>PLEIADES SPIRIT</td>\n",
       "      <td>2019-01-22T22:43:00</td>\n",
       "      <td>2019-01-22T22:43:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Vehicles Carrier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>CITY OF ROME</td>\n",
       "      <td>2019-01-22T23:17:00</td>\n",
       "      <td>2019-01-22T23:17:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Vehicles Carrier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>PRINCESS SEAWAYS</td>\n",
       "      <td>2019-01-23T08:50:00</td>\n",
       "      <td>2019-01-23T08:50:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Ro-Ro\\/Passenger Ship</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>HOEGH PUSAN</td>\n",
       "      <td>2019-01-23T09:29:00</td>\n",
       "      <td>2019-01-23T09:29:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Vehicles Carrier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>STEEN</td>\n",
       "      <td>2019-01-23T11:17:00</td>\n",
       "      <td>2019-01-23T11:17:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Container Ship</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>CITY OF ROME</td>\n",
       "      <td>2019-01-23T16:31:00</td>\n",
       "      <td>2019-01-23T16:31:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Vehicles Carrier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>PRINCESS SEAWAYS</td>\n",
       "      <td>2019-01-23T17:26:00</td>\n",
       "      <td>2019-01-23T17:26:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Ro-Ro\\/Passenger Ship</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>NORDIC ACE</td>\n",
       "      <td>2019-01-23T19:51:00</td>\n",
       "      <td>2019-01-23T19:51:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Vehicles Carrier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>SAND FALCON</td>\n",
       "      <td>2019-01-23T21:37:00</td>\n",
       "      <td>2019-01-23T21:37:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Hopper Dredger</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>COMET ACE</td>\n",
       "      <td>2019-01-24T04:25:00</td>\n",
       "      <td>2019-01-24T04:25:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Vehicles Carrier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>HOEGH PUSAN</td>\n",
       "      <td>2019-01-24T06:25:00</td>\n",
       "      <td>2019-01-24T06:25:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Vehicles Carrier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>CITY OF AMSTERDAM</td>\n",
       "      <td>2019-01-24T14:06:00</td>\n",
       "      <td>2019-01-24T14:06:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Vehicles Carrier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>NORDIC ACE</td>\n",
       "      <td>2019-01-24T17:44:00</td>\n",
       "      <td>2019-01-24T17:44:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Vehicles Carrier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>SAND FALCON</td>\n",
       "      <td>2019-01-25T03:29:00</td>\n",
       "      <td>2019-01-25T03:29:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Hopper Dredger</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>STEEN</td>\n",
       "      <td>2019-01-25T08:23:00</td>\n",
       "      <td>2019-01-25T08:23:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Container Ship</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>PRINCESS SEAWAYS</td>\n",
       "      <td>2019-01-25T08:43:00</td>\n",
       "      <td>2019-01-25T08:43:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Ro-Ro\\/Passenger Ship</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>REVER SAPPHIRE</td>\n",
       "      <td>2019-01-25T16:01:00</td>\n",
       "      <td>2019-01-25T16:01:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Offshore Supply Ship</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>SAND FALCON</td>\n",
       "      <td>2019-01-25T16:34:00</td>\n",
       "      <td>2019-01-25T16:34:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Hopper Dredger</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>PRINCESS SEAWAYS</td>\n",
       "      <td>2019-01-25T17:07:00</td>\n",
       "      <td>2019-01-25T17:07:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Ro-Ro\\/Passenger Ship</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>COMET ACE</td>\n",
       "      <td>2019-01-25T19:41:00</td>\n",
       "      <td>2019-01-25T19:41:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Vehicles Carrier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>CITY OF AMSTERDAM</td>\n",
       "      <td>2019-01-26T15:05:00</td>\n",
       "      <td>2019-01-26T15:05:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Vehicles Carrier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>PRINCESS SEAWAYS</td>\n",
       "      <td>2019-01-27T08:38:00</td>\n",
       "      <td>2019-01-27T08:38:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Ro-Ro\\/Passenger Ship</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>PRINCESS SEAWAYS</td>\n",
       "      <td>2019-01-27T17:11:00</td>\n",
       "      <td>2019-01-27T17:11:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Ro-Ro\\/Passenger Ship</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>SHEILA</td>\n",
       "      <td>2019-01-27T20:11:00</td>\n",
       "      <td>2019-01-27T20:11:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>ANDROMEDA J</td>\n",
       "      <td>2019-01-29T08:26:00</td>\n",
       "      <td>2019-01-29T08:26:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Container Ship</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>PRINCESS SEAWAYS</td>\n",
       "      <td>2019-01-29T08:54:00</td>\n",
       "      <td>2019-01-29T08:54:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Ro-Ro\\/Passenger Ship</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>PRINCESS SEAWAYS</td>\n",
       "      <td>2019-01-29T17:09:00</td>\n",
       "      <td>2019-01-29T17:09:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Ro-Ro\\/Passenger Ship</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>CITY OF ROTTERDAM</td>\n",
       "      <td>2019-01-29T17:26:00</td>\n",
       "      <td>2019-01-29T17:26:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Ro-Ro Cargo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>ANDROMEDA J</td>\n",
       "      <td>2019-01-29T18:20:00</td>\n",
       "      <td>2019-01-29T18:20:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Container Ship</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>CITY OF ROTTERDAM</td>\n",
       "      <td>2019-01-30T00:59:00</td>\n",
       "      <td>2019-01-30T00:59:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Ro-Ro Cargo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>HOEGH INCHON</td>\n",
       "      <td>2019-01-30T08:27:00</td>\n",
       "      <td>2019-01-30T08:27:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Vehicles Carrier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>PRINSENGRACHT</td>\n",
       "      <td>2019-01-30T22:15:00</td>\n",
       "      <td>2019-01-30T22:15:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Heavy Load Carrier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>HOEGH INCHON</td>\n",
       "      <td>2019-01-31T04:43:00</td>\n",
       "      <td>2019-01-31T04:43:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Vehicles Carrier</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>PRINCESS SEAWAYS</td>\n",
       "      <td>2019-01-31T08:46:00</td>\n",
       "      <td>2019-01-31T08:46:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Ro-Ro\\/Passenger Ship</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>PRINCESS SEAWAYS</td>\n",
       "      <td>2019-01-31T17:05:00</td>\n",
       "      <td>2019-01-31T17:05:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Ro-Ro\\/Passenger Ship</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CITY OF BARCELONA</td>\n",
       "      <td>2019-01-31T21:20:00</td>\n",
       "      <td>2019-01-31T21:20:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Vehicles Carrier</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 NAME            LOCALTIME              UTCTIME  MOVE  \\\n",
       "39   PRINCESS SEAWAYS  2019-01-21T08:49:00  2019-01-21T08:49:00     0   \n",
       "38        SAND FALCON  2019-01-21T13:12:00  2019-01-21T13:12:00     0   \n",
       "37   PRINCESS SEAWAYS  2019-01-21T17:06:00  2019-01-21T17:06:00     1   \n",
       "36  CITY OF BARCELONA  2019-01-22T05:36:00  2019-01-22T05:36:00     1   \n",
       "35    PLEIADES SPIRIT  2019-01-22T22:43:00  2019-01-22T22:43:00     1   \n",
       "34       CITY OF ROME  2019-01-22T23:17:00  2019-01-22T23:17:00     0   \n",
       "33   PRINCESS SEAWAYS  2019-01-23T08:50:00  2019-01-23T08:50:00     0   \n",
       "32        HOEGH PUSAN  2019-01-23T09:29:00  2019-01-23T09:29:00     0   \n",
       "31              STEEN  2019-01-23T11:17:00  2019-01-23T11:17:00     0   \n",
       "30       CITY OF ROME  2019-01-23T16:31:00  2019-01-23T16:31:00     1   \n",
       "29   PRINCESS SEAWAYS  2019-01-23T17:26:00  2019-01-23T17:26:00     1   \n",
       "28         NORDIC ACE  2019-01-23T19:51:00  2019-01-23T19:51:00     0   \n",
       "27        SAND FALCON  2019-01-23T21:37:00  2019-01-23T21:37:00     1   \n",
       "26          COMET ACE  2019-01-24T04:25:00  2019-01-24T04:25:00     0   \n",
       "25        HOEGH PUSAN  2019-01-24T06:25:00  2019-01-24T06:25:00     1   \n",
       "24  CITY OF AMSTERDAM  2019-01-24T14:06:00  2019-01-24T14:06:00     0   \n",
       "23         NORDIC ACE  2019-01-24T17:44:00  2019-01-24T17:44:00     1   \n",
       "22        SAND FALCON  2019-01-25T03:29:00  2019-01-25T03:29:00     0   \n",
       "21              STEEN  2019-01-25T08:23:00  2019-01-25T08:23:00     1   \n",
       "20   PRINCESS SEAWAYS  2019-01-25T08:43:00  2019-01-25T08:43:00     0   \n",
       "19     REVER SAPPHIRE  2019-01-25T16:01:00  2019-01-25T16:01:00     1   \n",
       "18        SAND FALCON  2019-01-25T16:34:00  2019-01-25T16:34:00     1   \n",
       "17   PRINCESS SEAWAYS  2019-01-25T17:07:00  2019-01-25T17:07:00     1   \n",
       "16          COMET ACE  2019-01-25T19:41:00  2019-01-25T19:41:00     1   \n",
       "15  CITY OF AMSTERDAM  2019-01-26T15:05:00  2019-01-26T15:05:00     1   \n",
       "14   PRINCESS SEAWAYS  2019-01-27T08:38:00  2019-01-27T08:38:00     0   \n",
       "13   PRINCESS SEAWAYS  2019-01-27T17:11:00  2019-01-27T17:11:00     1   \n",
       "12             SHEILA  2019-01-27T20:11:00  2019-01-27T20:11:00     1   \n",
       "11        ANDROMEDA J  2019-01-29T08:26:00  2019-01-29T08:26:00     0   \n",
       "10   PRINCESS SEAWAYS  2019-01-29T08:54:00  2019-01-29T08:54:00     0   \n",
       "9    PRINCESS SEAWAYS  2019-01-29T17:09:00  2019-01-29T17:09:00     1   \n",
       "8   CITY OF ROTTERDAM  2019-01-29T17:26:00  2019-01-29T17:26:00     0   \n",
       "7         ANDROMEDA J  2019-01-29T18:20:00  2019-01-29T18:20:00     1   \n",
       "6   CITY OF ROTTERDAM  2019-01-30T00:59:00  2019-01-30T00:59:00     1   \n",
       "5        HOEGH INCHON  2019-01-30T08:27:00  2019-01-30T08:27:00     0   \n",
       "4       PRINSENGRACHT  2019-01-30T22:15:00  2019-01-30T22:15:00     0   \n",
       "3        HOEGH INCHON  2019-01-31T04:43:00  2019-01-31T04:43:00     1   \n",
       "2    PRINCESS SEAWAYS  2019-01-31T08:46:00  2019-01-31T08:46:00     0   \n",
       "1    PRINCESS SEAWAYS  2019-01-31T17:05:00  2019-01-31T17:05:00     1   \n",
       "0   CITY OF BARCELONA  2019-01-31T21:20:00  2019-01-31T21:20:00     0   \n",
       "\n",
       "                     TYPE  \n",
       "39  Ro-Ro\\/Passenger Ship  \n",
       "38         Hopper Dredger  \n",
       "37  Ro-Ro\\/Passenger Ship  \n",
       "36       Vehicles Carrier  \n",
       "35       Vehicles Carrier  \n",
       "34       Vehicles Carrier  \n",
       "33  Ro-Ro\\/Passenger Ship  \n",
       "32       Vehicles Carrier  \n",
       "31         Container Ship  \n",
       "30       Vehicles Carrier  \n",
       "29  Ro-Ro\\/Passenger Ship  \n",
       "28       Vehicles Carrier  \n",
       "27         Hopper Dredger  \n",
       "26       Vehicles Carrier  \n",
       "25       Vehicles Carrier  \n",
       "24       Vehicles Carrier  \n",
       "23       Vehicles Carrier  \n",
       "22         Hopper Dredger  \n",
       "21         Container Ship  \n",
       "20  Ro-Ro\\/Passenger Ship  \n",
       "19   Offshore Supply Ship  \n",
       "18         Hopper Dredger  \n",
       "17  Ro-Ro\\/Passenger Ship  \n",
       "16       Vehicles Carrier  \n",
       "15       Vehicles Carrier  \n",
       "14  Ro-Ro\\/Passenger Ship  \n",
       "13  Ro-Ro\\/Passenger Ship  \n",
       "12           Bulk Carrier  \n",
       "11         Container Ship  \n",
       "10  Ro-Ro\\/Passenger Ship  \n",
       "9   Ro-Ro\\/Passenger Ship  \n",
       "8             Ro-Ro Cargo  \n",
       "7          Container Ship  \n",
       "6             Ro-Ro Cargo  \n",
       "5        Vehicles Carrier  \n",
       "4      Heavy Load Carrier  \n",
       "3        Vehicles Carrier  \n",
       "2   Ro-Ro\\/Passenger Ship  \n",
       "1   Ro-Ro\\/Passenger Ship  \n",
       "0        Vehicles Carrier  "
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfJan.tail(40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "bb25ad45",
   "metadata": {},
   "outputs": [],
   "source": [
    "dfFeb = pd.DataFrame(pd.read_json('190201-190228.json'))[[1,3,4,5,6]] #select useful columns\n",
    "dfFeb.columns = ['NAME','LOCALTIME','UTCTIME','MOVE','TYPE'] #change column names\n",
    "dfFeb = (dfFeb[dfFeb['TYPE'] == 'Bulk Carrier']).loc[::-1] #select only bul carriers and reverse row number\n",
    "\n",
    "dfMar = pd.DataFrame(pd.read_json('190301-190331.json'))[[1,3,4,5,6]]\n",
    "dfMar.columns = ['NAME','LOCALTIME','UTCTIME','MOVE','TYPE']\n",
    "dfMar = (dfMar[dfMar['TYPE'] == 'Bulk Carrier']).loc[::-1]\n",
    "\n",
    "dfApr = pd.DataFrame(pd.read_json('190401-190430.json'))[[1,3,4,5,6]]\n",
    "dfApr.columns = ['NAME','LOCALTIME','UTCTIME','MOVE','TYPE']\n",
    "dfApr = (dfApr[dfApr['TYPE'] == 'Bulk Carrier']).loc[::-1]\n",
    "\n",
    "dfMay = pd.DataFrame(pd.read_json('190501-190531.json'))[[1,3,4,5,6]]\n",
    "dfMay.columns = ['NAME','LOCALTIME','UTCTIME','MOVE','TYPE']\n",
    "dfMay = (dfMay[dfMay['TYPE'] == 'Bulk Carrier']).loc[::-1]\n",
    "\n",
    "dfJun = pd.DataFrame(pd.read_json('190601-190630.json'))[[1,3,4,5,6]]\n",
    "dfJun.columns = ['NAME','LOCALTIME','UTCTIME','MOVE','TYPE']\n",
    "dfJun = (dfJun[dfJun['TYPE'] == 'Bulk Carrier']).loc[::-1]\n",
    "\n",
    "dfJul = pd.DataFrame(pd.read_json('190701-190731.json'))[[1,3,4,5,6]]\n",
    "dfJul.columns = ['NAME','LOCALTIME','UTCTIME','MOVE','TYPE']\n",
    "dfJul = (dfJul[dfJul['TYPE'] == 'Bulk Carrier']).loc[::-1]\n",
    "\n",
    "dfAug = pd.DataFrame(pd.read_json('190801-190831.json'))[[1,3,4,5,6]]\n",
    "dfAug.columns = ['NAME','LOCALTIME','UTCTIME','MOVE','TYPE']\n",
    "dfAug = (dfAug[dfAug['TYPE'] == 'Bulk Carrier']).loc[::-1]\n",
    "\n",
    "dfSep = pd.DataFrame(pd.read_json('190901-190930.json'))[[1,3,4,5,6]]\n",
    "dfSep.columns = ['NAME','LOCALTIME','UTCTIME','MOVE','TYPE']\n",
    "dfSep = (dfSep[dfSep['TYPE'] == 'Bulk Carrier']).loc[::-1]\n",
    "\n",
    "dfOct = pd.DataFrame(pd.read_json('191001-191031.json'))[[1,3,4,5,6]]\n",
    "dfOct.columns = ['NAME','LOCALTIME','UTCTIME','MOVE','TYPE']\n",
    "dfOct = (dfOct[dfOct['TYPE'] == 'Bulk Carrier']).loc[::-1]\n",
    "\n",
    "dfNov = pd.DataFrame(pd.read_json('191101-191130.json'))[[1,3,4,5,6]]\n",
    "dfNov.columns = ['NAME','LOCALTIME','UTCTIME','MOVE','TYPE']\n",
    "dfNov = (dfNov[dfNov['TYPE'] == 'Bulk Carrier']).loc[::-1]\n",
    "\n",
    "dfDec = pd.DataFrame(pd.read_json('191201-191231.json'))[[1,3,4,5,6]]\n",
    "dfDec.columns = ['NAME','LOCALTIME','UTCTIME','MOVE','TYPE']\n",
    "dfDec = (dfDec[dfDec['TYPE'] == 'Bulk Carrier']).loc[::-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2d407dce",
   "metadata": {},
   "outputs": [],
   "source": [
    "df2019 = pd.concat([dfJan,dfFeb,dfMar,dfApr,dfMay,dfJun,dfJul,dfAug,dfSep,dfOct,dfNov,dfDec],ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "865d03a6",
   "metadata": {},
   "outputs": [],
   "source": [
    "df2019.to_json('E:\\\\20190923 Newcastle-M.Res\\\\OneDrive - Newcastle University\\\\21_22_autumn\\\\211018\\\\code\\\\data\\\\vesseldata\\\\vessel2019.json')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3469faa6",
   "metadata": {},
   "source": [
    "### loading processed vessel2019 data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d5a40425",
   "metadata": {},
   "outputs": [],
   "source": [
    "df2019 = pd.DataFrame(pd.read_json('2019Sim.json'))  #loading json data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c5017ea8",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['IMAVERE', 'NORD PACIFIC', 'FLORINDA', 'TEAL BULKER', 'EXPLORER',\n",
       "       'EMMA BULKER', 'GREEN GEM', 'SHEILA', 'STAMFORD PIONEER',\n",
       "       'NORD SAVANNAH', 'YULIA', 'FEDERAL SKYE', 'SPAR OCTANS',\n",
       "       'SWAN RIVER', 'PU LAN HAI', 'ISADORA', 'VENTURE LUCK', 'EL COMINO',\n",
       "       'FEDERAL DANUBE', 'NY TRADER II', 'GOODWYN ISLAND',\n",
       "       'SANTA KATARINA', 'NORD BOSPORUS', 'ND THELXIS', 'KUJAWY',\n",
       "       'APOLLO', 'CLIPPER SELO', 'BUNUN FORTUNE', 'OLGA', 'CHILOE ISLAND',\n",
       "       'AKOUR II', 'FITNES', 'SPAR PAVO', 'LIFE PASSION', 'LISSA TOPIC',\n",
       "       'IKAN LEBAN', 'TASMAN SEA', 'AEGEAN SPIRE', 'GH SKY BEAUTY',\n",
       "       'TCZEW', 'WL PALEKH', 'IJSSEL CONFIDENCE', 'POMORZE', 'NM SAKURA',\n",
       "       'JIA LONG SHAN', 'YANGZHOU CONFIDENCE', 'TAMPA BAY', 'SANDNES',\n",
       "       'AGGELOS B', 'BONNY ISLAND', 'BULK VENUS', 'CARLOTA BOLTEN',\n",
       "       'STH NEW YORK', 'WU GUI SHAN', 'TOMINI DESTINY', 'PRT ACE',\n",
       "       'VALKYRIE', 'ROSINA TOPIC', 'STAR EOS', 'JIAN GUO HAI'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2019.NAME.unique()    #Get vessel name"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d1db58d",
   "metadata": {},
   "source": [
    " #### Get Gross Tonnage and DWT data based on Vessel names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c379c1fb",
   "metadata": {},
   "outputs": [],
   "source": [
    "dfTon = pd.DataFrame(\n",
    "    {\n",
    "        'GT':[22746, 35035, 32415, 32370, 26449, 19812, 23885, 41428, 20954, \n",
    "              22866, 19814, 24196, 36313, 31360, 33044, 21387, 26411, 34794, \n",
    "              22734, 22856, 35684, 32287, 34589, 32714, 24109, 40219, 20924, \n",
    "              23281, 11121, 32377, 33096, 20312, 36313, 24198, 30363, 22852, \n",
    "              16407, 21211, 36367, 25278, 24199, 23264, 24109, 34349, 32962, \n",
    "              35851, 17979, 17434, 34374, 32377, 35832, 24198, 34321, 32962, \n",
    "              36415, 34815, 34618, 26216, 35873, 25622 ],\n",
    "        'DWT':[36746, 61221, 58600, 57903, 47639, 31887, 38503, 70037, 32211, \n",
    "               37067, 30878, 37169, 63800, 55947, 56897, 34948, 43413, 61465, \n",
    "               38289, 37054, 63963, 58096, 60457, 58223, 38890, 77326, 32389, \n",
    "               37790, 18319, 58044, 58831, 33169, 63800, 37332, 52089, 37000, \n",
    "               26214, 33401, 63398, 39072, 37500, 38243, 38981, 60948, 56603, \n",
    "               63165, 29671, 27711, 58480, 58044, 63371, 37489, 60309, 56625, \n",
    "               63590, 61290, 61230, 45251, 63500, 38767 ]\n",
    "    \n",
    "}) #create dataframe of GT and DWT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "01827fc1",
   "metadata": {},
   "outputs": [],
   "source": [
    "dfTon['NAME'] = df2019.NAME.unique() #Create name column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "ec4ae4f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>GT</th>\n",
       "      <th>DWT</th>\n",
       "      <th>NAME</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>22746</td>\n",
       "      <td>36746</td>\n",
       "      <td>IMAVERE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>35035</td>\n",
       "      <td>61221</td>\n",
       "      <td>NORD PACIFIC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>32415</td>\n",
       "      <td>58600</td>\n",
       "      <td>FLORINDA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>32370</td>\n",
       "      <td>57903</td>\n",
       "      <td>TEAL BULKER</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>26449</td>\n",
       "      <td>47639</td>\n",
       "      <td>EXPLORER</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>19812</td>\n",
       "      <td>31887</td>\n",
       "      <td>EMMA BULKER</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>23885</td>\n",
       "      <td>38503</td>\n",
       "      <td>GREEN GEM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>41428</td>\n",
       "      <td>70037</td>\n",
       "      <td>SHEILA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>20954</td>\n",
       "      <td>32211</td>\n",
       "      <td>STAMFORD PIONEER</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>22866</td>\n",
       "      <td>37067</td>\n",
       "      <td>NORD SAVANNAH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>19814</td>\n",
       "      <td>30878</td>\n",
       "      <td>YULIA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>24196</td>\n",
       "      <td>37169</td>\n",
       "      <td>FEDERAL SKYE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>36313</td>\n",
       "      <td>63800</td>\n",
       "      <td>SPAR OCTANS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>31360</td>\n",
       "      <td>55947</td>\n",
       "      <td>SWAN RIVER</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>33044</td>\n",
       "      <td>56897</td>\n",
       "      <td>PU LAN HAI</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>21387</td>\n",
       "      <td>34948</td>\n",
       "      <td>ISADORA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>26411</td>\n",
       "      <td>43413</td>\n",
       "      <td>VENTURE LUCK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>34794</td>\n",
       "      <td>61465</td>\n",
       "      <td>EL COMINO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>22734</td>\n",
       "      <td>38289</td>\n",
       "      <td>FEDERAL DANUBE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>22856</td>\n",
       "      <td>37054</td>\n",
       "      <td>NY TRADER II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>35684</td>\n",
       "      <td>63963</td>\n",
       "      <td>GOODWYN ISLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>32287</td>\n",
       "      <td>58096</td>\n",
       "      <td>SANTA KATARINA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>34589</td>\n",
       "      <td>60457</td>\n",
       "      <td>NORD BOSPORUS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>32714</td>\n",
       "      <td>58223</td>\n",
       "      <td>ND THELXIS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>24109</td>\n",
       "      <td>38890</td>\n",
       "      <td>KUJAWY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>40219</td>\n",
       "      <td>77326</td>\n",
       "      <td>APOLLO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>20924</td>\n",
       "      <td>32389</td>\n",
       "      <td>CLIPPER SELO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>23281</td>\n",
       "      <td>37790</td>\n",
       "      <td>BUNUN FORTUNE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>11121</td>\n",
       "      <td>18319</td>\n",
       "      <td>OLGA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>32377</td>\n",
       "      <td>58044</td>\n",
       "      <td>CHILOE ISLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>33096</td>\n",
       "      <td>58831</td>\n",
       "      <td>AKOUR II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>20312</td>\n",
       "      <td>33169</td>\n",
       "      <td>FITNES</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>36313</td>\n",
       "      <td>63800</td>\n",
       "      <td>SPAR PAVO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>24198</td>\n",
       "      <td>37332</td>\n",
       "      <td>LIFE PASSION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>30363</td>\n",
       "      <td>52089</td>\n",
       "      <td>LISSA TOPIC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>22852</td>\n",
       "      <td>37000</td>\n",
       "      <td>IKAN LEBAN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>16407</td>\n",
       "      <td>26214</td>\n",
       "      <td>TASMAN SEA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>21211</td>\n",
       "      <td>33401</td>\n",
       "      <td>AEGEAN SPIRE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>36367</td>\n",
       "      <td>63398</td>\n",
       "      <td>GH SKY BEAUTY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>25278</td>\n",
       "      <td>39072</td>\n",
       "      <td>TCZEW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>24199</td>\n",
       "      <td>37500</td>\n",
       "      <td>WL PALEKH</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>23264</td>\n",
       "      <td>38243</td>\n",
       "      <td>IJSSEL CONFIDENCE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>24109</td>\n",
       "      <td>38981</td>\n",
       "      <td>POMORZE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>34349</td>\n",
       "      <td>60948</td>\n",
       "      <td>NM SAKURA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>32962</td>\n",
       "      <td>56603</td>\n",
       "      <td>JIA LONG SHAN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>35851</td>\n",
       "      <td>63165</td>\n",
       "      <td>YANGZHOU CONFIDENCE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>17979</td>\n",
       "      <td>29671</td>\n",
       "      <td>TAMPA BAY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>17434</td>\n",
       "      <td>27711</td>\n",
       "      <td>SANDNES</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>34374</td>\n",
       "      <td>58480</td>\n",
       "      <td>AGGELOS B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>32377</td>\n",
       "      <td>58044</td>\n",
       "      <td>BONNY ISLAND</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>35832</td>\n",
       "      <td>63371</td>\n",
       "      <td>BULK VENUS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>24198</td>\n",
       "      <td>37489</td>\n",
       "      <td>CARLOTA BOLTEN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>34321</td>\n",
       "      <td>60309</td>\n",
       "      <td>STH NEW YORK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>32962</td>\n",
       "      <td>56625</td>\n",
       "      <td>WU GUI SHAN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>36415</td>\n",
       "      <td>63590</td>\n",
       "      <td>TOMINI DESTINY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>34815</td>\n",
       "      <td>61290</td>\n",
       "      <td>PRT ACE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>34618</td>\n",
       "      <td>61230</td>\n",
       "      <td>VALKYRIE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>26216</td>\n",
       "      <td>45251</td>\n",
       "      <td>ROSINA TOPIC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>35873</td>\n",
       "      <td>63500</td>\n",
       "      <td>STAR EOS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>25622</td>\n",
       "      <td>38767</td>\n",
       "      <td>JIAN GUO HAI</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       GT    DWT                 NAME\n",
       "0   22746  36746              IMAVERE\n",
       "1   35035  61221         NORD PACIFIC\n",
       "2   32415  58600             FLORINDA\n",
       "3   32370  57903          TEAL BULKER\n",
       "4   26449  47639             EXPLORER\n",
       "5   19812  31887          EMMA BULKER\n",
       "6   23885  38503            GREEN GEM\n",
       "7   41428  70037               SHEILA\n",
       "8   20954  32211     STAMFORD PIONEER\n",
       "9   22866  37067        NORD SAVANNAH\n",
       "10  19814  30878                YULIA\n",
       "11  24196  37169         FEDERAL SKYE\n",
       "12  36313  63800          SPAR OCTANS\n",
       "13  31360  55947           SWAN RIVER\n",
       "14  33044  56897           PU LAN HAI\n",
       "15  21387  34948              ISADORA\n",
       "16  26411  43413         VENTURE LUCK\n",
       "17  34794  61465            EL COMINO\n",
       "18  22734  38289       FEDERAL DANUBE\n",
       "19  22856  37054         NY TRADER II\n",
       "20  35684  63963       GOODWYN ISLAND\n",
       "21  32287  58096       SANTA KATARINA\n",
       "22  34589  60457        NORD BOSPORUS\n",
       "23  32714  58223           ND THELXIS\n",
       "24  24109  38890               KUJAWY\n",
       "25  40219  77326               APOLLO\n",
       "26  20924  32389         CLIPPER SELO\n",
       "27  23281  37790        BUNUN FORTUNE\n",
       "28  11121  18319                 OLGA\n",
       "29  32377  58044        CHILOE ISLAND\n",
       "30  33096  58831             AKOUR II\n",
       "31  20312  33169               FITNES\n",
       "32  36313  63800            SPAR PAVO\n",
       "33  24198  37332         LIFE PASSION\n",
       "34  30363  52089          LISSA TOPIC\n",
       "35  22852  37000           IKAN LEBAN\n",
       "36  16407  26214           TASMAN SEA\n",
       "37  21211  33401         AEGEAN SPIRE\n",
       "38  36367  63398        GH SKY BEAUTY\n",
       "39  25278  39072                TCZEW\n",
       "40  24199  37500            WL PALEKH\n",
       "41  23264  38243    IJSSEL CONFIDENCE\n",
       "42  24109  38981              POMORZE\n",
       "43  34349  60948            NM SAKURA\n",
       "44  32962  56603        JIA LONG SHAN\n",
       "45  35851  63165  YANGZHOU CONFIDENCE\n",
       "46  17979  29671            TAMPA BAY\n",
       "47  17434  27711              SANDNES\n",
       "48  34374  58480            AGGELOS B\n",
       "49  32377  58044         BONNY ISLAND\n",
       "50  35832  63371           BULK VENUS\n",
       "51  24198  37489       CARLOTA BOLTEN\n",
       "52  34321  60309         STH NEW YORK\n",
       "53  32962  56625          WU GUI SHAN\n",
       "54  36415  63590       TOMINI DESTINY\n",
       "55  34815  61290              PRT ACE\n",
       "56  34618  61230             VALKYRIE\n",
       "57  26216  45251         ROSINA TOPIC\n",
       "58  35873  63500             STAR EOS\n",
       "59  25622  38767         JIAN GUO HAI"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfTon"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "4aa07d8e",
   "metadata": {},
   "outputs": [],
   "source": [
    "dfTon.to_json('TonInfo.json')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "a652770a",
   "metadata": {},
   "outputs": [],
   "source": [
    "df2019 = pd.merge(df2019,dfTon, on=['NAME'], how='left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "3ae30a4c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NAME</th>\n",
       "      <th>LOCALTIME</th>\n",
       "      <th>UTCTIME</th>\n",
       "      <th>MOVE</th>\n",
       "      <th>TYPE</th>\n",
       "      <th>GT</th>\n",
       "      <th>DWT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>IMAVERE</td>\n",
       "      <td>2019-01-02T19:29:00</td>\n",
       "      <td>2019-01-02T19:29:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>22746</td>\n",
       "      <td>36746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NORD PACIFIC</td>\n",
       "      <td>2019-01-04T13:24:00</td>\n",
       "      <td>2019-01-04T13:24:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>35035</td>\n",
       "      <td>61221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>FLORINDA</td>\n",
       "      <td>2019-01-05T01:28:00</td>\n",
       "      <td>2019-01-05T01:28:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>32415</td>\n",
       "      <td>58600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>TEAL BULKER</td>\n",
       "      <td>2019-01-05T14:49:00</td>\n",
       "      <td>2019-01-05T14:49:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>32370</td>\n",
       "      <td>57903</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>EXPLORER</td>\n",
       "      <td>2019-01-07T03:59:00</td>\n",
       "      <td>2019-01-07T03:59:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>26449</td>\n",
       "      <td>47639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>VALKYRIE</td>\n",
       "      <td>2019-12-22T04:48:00</td>\n",
       "      <td>2019-12-22T04:48:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>34618</td>\n",
       "      <td>61230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>STAR EOS</td>\n",
       "      <td>2019-12-23T12:17:00</td>\n",
       "      <td>2019-12-23T12:17:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>35873</td>\n",
       "      <td>63500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>JIAN GUO HAI</td>\n",
       "      <td>2019-12-27T12:19:00</td>\n",
       "      <td>2019-12-27T12:19:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>25622</td>\n",
       "      <td>38767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>STAR EOS</td>\n",
       "      <td>2019-12-31T00:30:00</td>\n",
       "      <td>2019-12-31T00:30:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>35873</td>\n",
       "      <td>63500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>JIAN GUO HAI</td>\n",
       "      <td>2019-12-31T19:37:00</td>\n",
       "      <td>2019-12-31T19:37:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>25622</td>\n",
       "      <td>38767</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>139 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             NAME            LOCALTIME              UTCTIME  MOVE  \\\n",
       "0         IMAVERE  2019-01-02T19:29:00  2019-01-02T19:29:00     1   \n",
       "1    NORD PACIFIC  2019-01-04T13:24:00  2019-01-04T13:24:00     0   \n",
       "2        FLORINDA  2019-01-05T01:28:00  2019-01-05T01:28:00     1   \n",
       "3     TEAL BULKER  2019-01-05T14:49:00  2019-01-05T14:49:00     1   \n",
       "4        EXPLORER  2019-01-07T03:59:00  2019-01-07T03:59:00     0   \n",
       "..            ...                  ...                  ...   ...   \n",
       "134      VALKYRIE  2019-12-22T04:48:00  2019-12-22T04:48:00     1   \n",
       "135      STAR EOS  2019-12-23T12:17:00  2019-12-23T12:17:00     0   \n",
       "136  JIAN GUO HAI  2019-12-27T12:19:00  2019-12-27T12:19:00     0   \n",
       "137      STAR EOS  2019-12-31T00:30:00  2019-12-31T00:30:00     1   \n",
       "138  JIAN GUO HAI  2019-12-31T19:37:00  2019-12-31T19:37:00     1   \n",
       "\n",
       "             TYPE     GT    DWT  \n",
       "0    Bulk Carrier  22746  36746  \n",
       "1    Bulk Carrier  35035  61221  \n",
       "2    Bulk Carrier  32415  58600  \n",
       "3    Bulk Carrier  32370  57903  \n",
       "4    Bulk Carrier  26449  47639  \n",
       "..            ...    ...    ...  \n",
       "134  Bulk Carrier  34618  61230  \n",
       "135  Bulk Carrier  35873  63500  \n",
       "136  Bulk Carrier  25622  38767  \n",
       "137  Bulk Carrier  35873  63500  \n",
       "138  Bulk Carrier  25622  38767  \n",
       "\n",
       "[139 rows x 7 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2019"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "21aed376",
   "metadata": {},
   "outputs": [],
   "source": [
    "df2019[['DATE','TIME']] = df2019['UTCTIME'].str.split('T', expand= True) #split date and time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "cb60fda8",
   "metadata": {},
   "outputs": [],
   "source": [
    "df2019['DATE'] = pd.to_datetime(df2019['DATE'],format='%Y-%m-%d')  #change date format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "dbd2bd6f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df2019['year']= df2019['DATE'].dt.year # split date into year/month/day\n",
    "df2019['month']= df2019['DATE'].dt.month\n",
    "df2019['day']= df2019['DATE'].dt.day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "05f8ee7f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df2019.to_json(\n",
    "    'E:\\\\20190923 Newcastle-M.Res\\\\OneDrive - Newcastle University\\\\21_22_autumn\\\\211018\\\\code\\\\data\\\\vesseldata\\\\vessel2019.json')\n",
    "# save full vessel data as local json"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a102a9a",
   "metadata": {},
   "source": [
    "### Loading energy and volume record from port"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "1f27703f",
   "metadata": {},
   "outputs": [],
   "source": [
    "os.chdir(\"E:\\\\20190923 Newcastle-M.Res\\\\OneDrive - Newcastle University\\\\21_22_autumn\\\\211018\\\\code\\\\data\\\\weather\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "941d77a7",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "#dfPort = pd.read_csv('WeaEne.csv')   #loading port energy and volume record + windspeed and humidity\n",
    "#dfPort['Date'] = pd.to_datetime(dfPort['Date'],format='%d/%m/%Y')  #change date format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "aba0a832",
   "metadata": {},
   "outputs": [],
   "source": [
    "#dfPort['year']= dfPort['Date'].dt.year # split date into year/month/day\n",
    "#dfPort['month']= dfPort['Date'].dt.month\n",
    "#dfPort['day']= dfPort['Date'].dt.day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "c1c7347f",
   "metadata": {},
   "outputs": [],
   "source": [
    "#dfPort.to_json(\n",
    "    'E:\\\\20190923 Newcastle-M.Res\\\\OneDrive - Newcastle University\\\\21_22_autumn\\\\211018\\\\code\\\\data\\\\weather\\\\PortEneWea.json')\n",
    "# save full port record data as local json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ff8c1c4e",
   "metadata": {},
   "outputs": [],
   "source": [
    "os.chdir(\"E:\\\\20190923 Newcastle-M.Res\\\\OneDrive - Newcastle University\\\\21_22_autumn\\\\211018\\\\code\\\\data\\\\weather\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e066e384",
   "metadata": {},
   "outputs": [],
   "source": [
    "dfPort = pd.DataFrame(pd.read_json('PortEneWea.json'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "647dbfee",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>WindSpeed</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>Tonnes</th>\n",
       "      <th>Energy</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>21</td>\n",
       "      <td>74</td>\n",
       "      <td>NaN</td>\n",
       "      <td>646.92</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>20</td>\n",
       "      <td>81</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1391.50</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-01-03</td>\n",
       "      <td>34</td>\n",
       "      <td>72</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1660.89</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-01-04</td>\n",
       "      <td>16</td>\n",
       "      <td>86</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1046.34</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-01-05</td>\n",
       "      <td>17</td>\n",
       "      <td>83</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1739.67</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1091</th>\n",
       "      <td>2020-12-27</td>\n",
       "      <td>22</td>\n",
       "      <td>76</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3380.46</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1092</th>\n",
       "      <td>2020-12-28</td>\n",
       "      <td>20</td>\n",
       "      <td>77</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4634.58</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1093</th>\n",
       "      <td>2020-12-29</td>\n",
       "      <td>18</td>\n",
       "      <td>74</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6115.43</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1094</th>\n",
       "      <td>2020-12-30</td>\n",
       "      <td>18</td>\n",
       "      <td>76</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5472.71</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1095</th>\n",
       "      <td>2020-12-31</td>\n",
       "      <td>21</td>\n",
       "      <td>83</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3659.57</td>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1096 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Date  WindSpeed  Humidity  Tonnes   Energy  year  month  day\n",
       "0    2018-01-01         21        74     NaN   646.92  2018      1    1\n",
       "1    2018-01-02         20        81     NaN  1391.50  2018      1    2\n",
       "2    2018-01-03         34        72     NaN  1660.89  2018      1    3\n",
       "3    2018-01-04         16        86     NaN  1046.34  2018      1    4\n",
       "4    2018-01-05         17        83     NaN  1739.67  2018      1    5\n",
       "...         ...        ...       ...     ...      ...   ...    ...  ...\n",
       "1091 2020-12-27         22        76     NaN  3380.46  2020     12   27\n",
       "1092 2020-12-28         20        77     NaN  4634.58  2020     12   28\n",
       "1093 2020-12-29         18        74     NaN  6115.43  2020     12   29\n",
       "1094 2020-12-30         18        76     NaN  5472.71  2020     12   30\n",
       "1095 2020-12-31         21        83     NaN  3659.57  2020     12   31\n",
       "\n",
       "[1096 rows x 8 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfPort"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "86987eca",
   "metadata": {},
   "source": [
    "### Loading Local Vessel data "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "372ca7c2",
   "metadata": {},
   "outputs": [],
   "source": [
    "os.chdir(\"E:\\\\20190923 Newcastle-M.Res\\\\OneDrive - Newcastle University\\\\21_22_autumn\\\\211018\\\\code\\\\data\\\\vesseldata\")\n",
    "df2019 = pd.DataFrame(pd.read_json('vessel2019.json'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "72ce8a20",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NAME</th>\n",
       "      <th>LOCALTIME</th>\n",
       "      <th>UTCTIME</th>\n",
       "      <th>MOVE</th>\n",
       "      <th>TYPE</th>\n",
       "      <th>GT</th>\n",
       "      <th>DWT</th>\n",
       "      <th>TIME</th>\n",
       "      <th>DATE</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>IMAVERE</td>\n",
       "      <td>2019-01-02T19:29:00</td>\n",
       "      <td>2019-01-02T19:29:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>22746</td>\n",
       "      <td>36746</td>\n",
       "      <td>19:29:00</td>\n",
       "      <td>2019-01-02</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NORD PACIFIC</td>\n",
       "      <td>2019-01-04T13:24:00</td>\n",
       "      <td>2019-01-04T13:24:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>35035</td>\n",
       "      <td>61221</td>\n",
       "      <td>13:24:00</td>\n",
       "      <td>2019-01-04</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>FLORINDA</td>\n",
       "      <td>2019-01-05T01:28:00</td>\n",
       "      <td>2019-01-05T01:28:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>32415</td>\n",
       "      <td>58600</td>\n",
       "      <td>01:28:00</td>\n",
       "      <td>2019-01-05</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>TEAL BULKER</td>\n",
       "      <td>2019-01-05T14:49:00</td>\n",
       "      <td>2019-01-05T14:49:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>32370</td>\n",
       "      <td>57903</td>\n",
       "      <td>14:49:00</td>\n",
       "      <td>2019-01-05</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>EXPLORER</td>\n",
       "      <td>2019-01-07T03:59:00</td>\n",
       "      <td>2019-01-07T03:59:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>26449</td>\n",
       "      <td>47639</td>\n",
       "      <td>03:59:00</td>\n",
       "      <td>2019-01-07</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>VALKYRIE</td>\n",
       "      <td>2019-12-22T04:48:00</td>\n",
       "      <td>2019-12-22T04:48:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>34618</td>\n",
       "      <td>61230</td>\n",
       "      <td>04:48:00</td>\n",
       "      <td>2019-12-22</td>\n",
       "      <td>2019</td>\n",
       "      <td>12</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>STAR EOS</td>\n",
       "      <td>2019-12-23T12:17:00</td>\n",
       "      <td>2019-12-23T12:17:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>35873</td>\n",
       "      <td>63500</td>\n",
       "      <td>12:17:00</td>\n",
       "      <td>2019-12-23</td>\n",
       "      <td>2019</td>\n",
       "      <td>12</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>JIAN GUO HAI</td>\n",
       "      <td>2019-12-27T12:19:00</td>\n",
       "      <td>2019-12-27T12:19:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>25622</td>\n",
       "      <td>38767</td>\n",
       "      <td>12:19:00</td>\n",
       "      <td>2019-12-27</td>\n",
       "      <td>2019</td>\n",
       "      <td>12</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>STAR EOS</td>\n",
       "      <td>2019-12-31T00:30:00</td>\n",
       "      <td>2019-12-31T00:30:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>35873</td>\n",
       "      <td>63500</td>\n",
       "      <td>00:30:00</td>\n",
       "      <td>2019-12-31</td>\n",
       "      <td>2019</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>JIAN GUO HAI</td>\n",
       "      <td>2019-12-31T19:37:00</td>\n",
       "      <td>2019-12-31T19:37:00</td>\n",
       "      <td>1</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>25622</td>\n",
       "      <td>38767</td>\n",
       "      <td>19:37:00</td>\n",
       "      <td>2019-12-31</td>\n",
       "      <td>2019</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>139 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             NAME            LOCALTIME              UTCTIME  MOVE  \\\n",
       "0         IMAVERE  2019-01-02T19:29:00  2019-01-02T19:29:00     1   \n",
       "1    NORD PACIFIC  2019-01-04T13:24:00  2019-01-04T13:24:00     0   \n",
       "2        FLORINDA  2019-01-05T01:28:00  2019-01-05T01:28:00     1   \n",
       "3     TEAL BULKER  2019-01-05T14:49:00  2019-01-05T14:49:00     1   \n",
       "4        EXPLORER  2019-01-07T03:59:00  2019-01-07T03:59:00     0   \n",
       "..            ...                  ...                  ...   ...   \n",
       "134      VALKYRIE  2019-12-22T04:48:00  2019-12-22T04:48:00     1   \n",
       "135      STAR EOS  2019-12-23T12:17:00  2019-12-23T12:17:00     0   \n",
       "136  JIAN GUO HAI  2019-12-27T12:19:00  2019-12-27T12:19:00     0   \n",
       "137      STAR EOS  2019-12-31T00:30:00  2019-12-31T00:30:00     1   \n",
       "138  JIAN GUO HAI  2019-12-31T19:37:00  2019-12-31T19:37:00     1   \n",
       "\n",
       "             TYPE     GT    DWT      TIME       DATE  year  month  day  \n",
       "0    Bulk Carrier  22746  36746  19:29:00 2019-01-02  2019      1    2  \n",
       "1    Bulk Carrier  35035  61221  13:24:00 2019-01-04  2019      1    4  \n",
       "2    Bulk Carrier  32415  58600  01:28:00 2019-01-05  2019      1    5  \n",
       "3    Bulk Carrier  32370  57903  14:49:00 2019-01-05  2019      1    5  \n",
       "4    Bulk Carrier  26449  47639  03:59:00 2019-01-07  2019      1    7  \n",
       "..            ...    ...    ...       ...        ...   ...    ...  ...  \n",
       "134  Bulk Carrier  34618  61230  04:48:00 2019-12-22  2019     12   22  \n",
       "135  Bulk Carrier  35873  63500  12:17:00 2019-12-23  2019     12   23  \n",
       "136  Bulk Carrier  25622  38767  12:19:00 2019-12-27  2019     12   27  \n",
       "137  Bulk Carrier  35873  63500  00:30:00 2019-12-31  2019     12   31  \n",
       "138  Bulk Carrier  25622  38767  19:37:00 2019-12-31  2019     12   31  \n",
       "\n",
       "[139 rows x 12 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2019"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "7dca5ff0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([36746, 61221, 58600, 57903, 47639, 31887, 38503, 70037, 32211,\n",
       "       37067, 30878, 37169, 63800, 55947, 56897, 34948, 43413, 61465,\n",
       "       38289, 37054, 63963, 58096, 60457, 58223, 38890, 77326, 32389,\n",
       "       37790, 18319, 58044, 58831, 33169, 37332, 52089, 37000, 26214,\n",
       "       33401, 63398, 39072, 37500, 38243, 38981, 60948, 56603, 63165,\n",
       "       29671, 27711, 58480, 63371, 37489, 60309, 56625, 63590, 61290,\n",
       "       61230, 45251, 63500, 38767], dtype=int64)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2019['DWT'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d5309863",
   "metadata": {},
   "source": [
    "### Analysing Port record and Vessel record"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "a005f899",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "    .dataframe tbody tr th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>WindSpeed</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>Tonnes</th>\n",
       "      <th>Energy</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>365</th>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>23</td>\n",
       "      <td>71</td>\n",
       "      <td>5847.1</td>\n",
       "      <td>4310.03</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>366</th>\n",
       "      <td>2019-01-02</td>\n",
       "      <td>13</td>\n",
       "      <td>72</td>\n",
       "      <td>3671.7</td>\n",
       "      <td>3746.93</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>367</th>\n",
       "      <td>2019-01-03</td>\n",
       "      <td>8</td>\n",
       "      <td>78</td>\n",
       "      <td>3022.4</td>\n",
       "      <td>3301.43</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>368</th>\n",
       "      <td>2019-01-04</td>\n",
       "      <td>17</td>\n",
       "      <td>84</td>\n",
       "      <td>4316.3</td>\n",
       "      <td>3900.80</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>369</th>\n",
       "      <td>2019-01-05</td>\n",
       "      <td>15</td>\n",
       "      <td>84</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1637.28</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>370</th>\n",
       "      <td>2019-01-06</td>\n",
       "      <td>13</td>\n",
       "      <td>90</td>\n",
       "      <td>4163.3</td>\n",
       "      <td>3364.49</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>371</th>\n",
       "      <td>2019-01-07</td>\n",
       "      <td>26</td>\n",
       "      <td>80</td>\n",
       "      <td>5188.0</td>\n",
       "      <td>4779.89</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>372</th>\n",
       "      <td>2019-01-08</td>\n",
       "      <td>33</td>\n",
       "      <td>67</td>\n",
       "      <td>5628.9</td>\n",
       "      <td>5433.31</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>373</th>\n",
       "      <td>2019-01-09</td>\n",
       "      <td>21</td>\n",
       "      <td>70</td>\n",
       "      <td>5541.8</td>\n",
       "      <td>4759.37</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>374</th>\n",
       "      <td>2019-01-10</td>\n",
       "      <td>15</td>\n",
       "      <td>83</td>\n",
       "      <td>5509.8</td>\n",
       "      <td>4677.21</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>375</th>\n",
       "      <td>2019-01-11</td>\n",
       "      <td>18</td>\n",
       "      <td>83</td>\n",
       "      <td>5773.9</td>\n",
       "      <td>4490.16</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>376</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>26</td>\n",
       "      <td>78</td>\n",
       "      <td>1374.9</td>\n",
       "      <td>2126.08</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>377</th>\n",
       "      <td>2019-01-13</td>\n",
       "      <td>36</td>\n",
       "      <td>69</td>\n",
       "      <td>3525.8</td>\n",
       "      <td>2411.46</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>378</th>\n",
       "      <td>2019-01-14</td>\n",
       "      <td>18</td>\n",
       "      <td>75</td>\n",
       "      <td>2128.0</td>\n",
       "      <td>3134.44</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>379</th>\n",
       "      <td>2019-01-15</td>\n",
       "      <td>28</td>\n",
       "      <td>77</td>\n",
       "      <td>3446.3</td>\n",
       "      <td>4021.09</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>380</th>\n",
       "      <td>2019-01-16</td>\n",
       "      <td>26</td>\n",
       "      <td>72</td>\n",
       "      <td>2169.5</td>\n",
       "      <td>3642.33</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>381</th>\n",
       "      <td>2019-01-17</td>\n",
       "      <td>32</td>\n",
       "      <td>64</td>\n",
       "      <td>4495.3</td>\n",
       "      <td>4545.82</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>382</th>\n",
       "      <td>2019-01-18</td>\n",
       "      <td>19</td>\n",
       "      <td>72</td>\n",
       "      <td>2686.3</td>\n",
       "      <td>4056.31</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>383</th>\n",
       "      <td>2019-01-19</td>\n",
       "      <td>20</td>\n",
       "      <td>83</td>\n",
       "      <td>414.5</td>\n",
       "      <td>1389.06</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>384</th>\n",
       "      <td>2019-01-20</td>\n",
       "      <td>13</td>\n",
       "      <td>82</td>\n",
       "      <td>3187.5</td>\n",
       "      <td>2813.02</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>385</th>\n",
       "      <td>2019-01-21</td>\n",
       "      <td>18</td>\n",
       "      <td>75</td>\n",
       "      <td>3183.6</td>\n",
       "      <td>3199.09</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>386</th>\n",
       "      <td>2019-01-22</td>\n",
       "      <td>21</td>\n",
       "      <td>75</td>\n",
       "      <td>3121.6</td>\n",
       "      <td>3343.74</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>387</th>\n",
       "      <td>2019-01-23</td>\n",
       "      <td>14</td>\n",
       "      <td>70</td>\n",
       "      <td>3278.9</td>\n",
       "      <td>3573.66</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>388</th>\n",
       "      <td>2019-01-24</td>\n",
       "      <td>8</td>\n",
       "      <td>84</td>\n",
       "      <td>2461.5</td>\n",
       "      <td>3262.75</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>389</th>\n",
       "      <td>2019-01-25</td>\n",
       "      <td>25</td>\n",
       "      <td>85</td>\n",
       "      <td>3212.2</td>\n",
       "      <td>3026.96</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>390</th>\n",
       "      <td>2019-01-26</td>\n",
       "      <td>26</td>\n",
       "      <td>80</td>\n",
       "      <td>543.0</td>\n",
       "      <td>1421.43</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>391</th>\n",
       "      <td>2019-01-27</td>\n",
       "      <td>45</td>\n",
       "      <td>70</td>\n",
       "      <td>3200.4</td>\n",
       "      <td>2830.65</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>392</th>\n",
       "      <td>2019-01-28</td>\n",
       "      <td>26</td>\n",
       "      <td>67</td>\n",
       "      <td>2055.0</td>\n",
       "      <td>3308.91</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>393</th>\n",
       "      <td>2019-01-29</td>\n",
       "      <td>23</td>\n",
       "      <td>77</td>\n",
       "      <td>3307.5</td>\n",
       "      <td>3681.00</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>394</th>\n",
       "      <td>2019-01-30</td>\n",
       "      <td>14</td>\n",
       "      <td>69</td>\n",
       "      <td>4231.8</td>\n",
       "      <td>3636.98</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>395</th>\n",
       "      <td>2019-01-31</td>\n",
       "      <td>10</td>\n",
       "      <td>71</td>\n",
       "      <td>1236.0</td>\n",
       "      <td>2587.00</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date  WindSpeed  Humidity  Tonnes   Energy  year  month  day\n",
       "365 2019-01-01         23        71  5847.1  4310.03  2019      1    1\n",
       "366 2019-01-02         13        72  3671.7  3746.93  2019      1    2\n",
       "367 2019-01-03          8        78  3022.4  3301.43  2019      1    3\n",
       "368 2019-01-04         17        84  4316.3  3900.80  2019      1    4\n",
       "369 2019-01-05         15        84     0.0  1637.28  2019      1    5\n",
       "370 2019-01-06         13        90  4163.3  3364.49  2019      1    6\n",
       "371 2019-01-07         26        80  5188.0  4779.89  2019      1    7\n",
       "372 2019-01-08         33        67  5628.9  5433.31  2019      1    8\n",
       "373 2019-01-09         21        70  5541.8  4759.37  2019      1    9\n",
       "374 2019-01-10         15        83  5509.8  4677.21  2019      1   10\n",
       "375 2019-01-11         18        83  5773.9  4490.16  2019      1   11\n",
       "376 2019-01-12         26        78  1374.9  2126.08  2019      1   12\n",
       "377 2019-01-13         36        69  3525.8  2411.46  2019      1   13\n",
       "378 2019-01-14         18        75  2128.0  3134.44  2019      1   14\n",
       "379 2019-01-15         28        77  3446.3  4021.09  2019      1   15\n",
       "380 2019-01-16         26        72  2169.5  3642.33  2019      1   16\n",
       "381 2019-01-17         32        64  4495.3  4545.82  2019      1   17\n",
       "382 2019-01-18         19        72  2686.3  4056.31  2019      1   18\n",
       "383 2019-01-19         20        83   414.5  1389.06  2019      1   19\n",
       "384 2019-01-20         13        82  3187.5  2813.02  2019      1   20\n",
       "385 2019-01-21         18        75  3183.6  3199.09  2019      1   21\n",
       "386 2019-01-22         21        75  3121.6  3343.74  2019      1   22\n",
       "387 2019-01-23         14        70  3278.9  3573.66  2019      1   23\n",
       "388 2019-01-24          8        84  2461.5  3262.75  2019      1   24\n",
       "389 2019-01-25         25        85  3212.2  3026.96  2019      1   25\n",
       "390 2019-01-26         26        80   543.0  1421.43  2019      1   26\n",
       "391 2019-01-27         45        70  3200.4  2830.65  2019      1   27\n",
       "392 2019-01-28         26        67  2055.0  3308.91  2019      1   28\n",
       "393 2019-01-29         23        77  3307.5  3681.00  2019      1   29\n",
       "394 2019-01-30         14        69  4231.8  3636.98  2019      1   30\n",
       "395 2019-01-31         10        71  1236.0  2587.00  2019      1   31"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = dfPort.loc[(dfPort['year'] == 2019)&(dfPort['month'] == 1)]\n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "4a7cc88c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "101922.79999999999"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a['Tonnes'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "42698bea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NAME</th>\n",
       "      <th>LOCALTIME</th>\n",
       "      <th>UTCTIME</th>\n",
       "      <th>MOVE</th>\n",
       "      <th>TYPE</th>\n",
       "      <th>GT</th>\n",
       "      <th>DWT</th>\n",
       "      <th>TIME</th>\n",
       "      <th>DATE</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NORD PACIFIC</td>\n",
       "      <td>2019-01-04T13:24:00</td>\n",
       "      <td>2019-01-04T13:24:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>35035</td>\n",
       "      <td>61221</td>\n",
       "      <td>13:24:00</td>\n",
       "      <td>2019-01-04</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>EXPLORER</td>\n",
       "      <td>2019-01-07T03:59:00</td>\n",
       "      <td>2019-01-07T03:59:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>26449</td>\n",
       "      <td>47639</td>\n",
       "      <td>03:59:00</td>\n",
       "      <td>2019-01-07</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>EMMA BULKER</td>\n",
       "      <td>2019-01-11T05:26:00</td>\n",
       "      <td>2019-01-11T05:26:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>19812</td>\n",
       "      <td>31887</td>\n",
       "      <td>05:26:00</td>\n",
       "      <td>2019-01-11</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>GREEN GEM</td>\n",
       "      <td>2019-01-15T21:27:00</td>\n",
       "      <td>2019-01-15T21:27:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>23885</td>\n",
       "      <td>38503</td>\n",
       "      <td>21:27:00</td>\n",
       "      <td>2019-01-15</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>SHEILA</td>\n",
       "      <td>2019-01-19T08:08:00</td>\n",
       "      <td>2019-01-19T08:08:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>41428</td>\n",
       "      <td>70037</td>\n",
       "      <td>08:08:00</td>\n",
       "      <td>2019-01-19</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            NAME            LOCALTIME              UTCTIME  MOVE  \\\n",
       "1   NORD PACIFIC  2019-01-04T13:24:00  2019-01-04T13:24:00     0   \n",
       "4       EXPLORER  2019-01-07T03:59:00  2019-01-07T03:59:00     0   \n",
       "7    EMMA BULKER  2019-01-11T05:26:00  2019-01-11T05:26:00     0   \n",
       "9      GREEN GEM  2019-01-15T21:27:00  2019-01-15T21:27:00     0   \n",
       "11        SHEILA  2019-01-19T08:08:00  2019-01-19T08:08:00     0   \n",
       "\n",
       "            TYPE     GT    DWT      TIME       DATE  year  month  day  \n",
       "1   Bulk Carrier  35035  61221  13:24:00 2019-01-04  2019      1    4  \n",
       "4   Bulk Carrier  26449  47639  03:59:00 2019-01-07  2019      1    7  \n",
       "7   Bulk Carrier  19812  31887  05:26:00 2019-01-11  2019      1   11  \n",
       "9   Bulk Carrier  23885  38503  21:27:00 2019-01-15  2019      1   15  \n",
       "11  Bulk Carrier  41428  70037  08:08:00 2019-01-19  2019      1   19  "
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b = df2019.loc[(df2019['month'] == 1)&(df2019['MOVE'] == 0)]\n",
    "b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "781ffe4f",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "249287"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b['DWT'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c069aa37",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "37d37674",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>WindSpeed</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>Tonnes</th>\n",
       "      <th>Energy</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>396</th>\n",
       "      <td>2019-02-01</td>\n",
       "      <td>17</td>\n",
       "      <td>70</td>\n",
       "      <td>220.2</td>\n",
       "      <td>2122.04</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>397</th>\n",
       "      <td>2019-02-02</td>\n",
       "      <td>23</td>\n",
       "      <td>74</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1676.51</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>398</th>\n",
       "      <td>2019-02-03</td>\n",
       "      <td>20</td>\n",
       "      <td>78</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1652.67</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>399</th>\n",
       "      <td>2019-02-04</td>\n",
       "      <td>24</td>\n",
       "      <td>78</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2054.34</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>400</th>\n",
       "      <td>2019-02-05</td>\n",
       "      <td>19</td>\n",
       "      <td>84</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1742.19</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>401</th>\n",
       "      <td>2019-02-06</td>\n",
       "      <td>21</td>\n",
       "      <td>80</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1526.33</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>402</th>\n",
       "      <td>2019-02-07</td>\n",
       "      <td>32</td>\n",
       "      <td>81</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1846.30</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>403</th>\n",
       "      <td>2019-02-08</td>\n",
       "      <td>30</td>\n",
       "      <td>75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2075.24</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>404</th>\n",
       "      <td>2019-02-09</td>\n",
       "      <td>40</td>\n",
       "      <td>67</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1296.31</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>405</th>\n",
       "      <td>2019-02-10</td>\n",
       "      <td>18</td>\n",
       "      <td>75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>737.04</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>406</th>\n",
       "      <td>2019-02-11</td>\n",
       "      <td>14</td>\n",
       "      <td>74</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1576.83</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>407</th>\n",
       "      <td>2019-02-12</td>\n",
       "      <td>20</td>\n",
       "      <td>81</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1827.15</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>408</th>\n",
       "      <td>2019-02-13</td>\n",
       "      <td>20</td>\n",
       "      <td>79</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1635.30</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>409</th>\n",
       "      <td>2019-02-14</td>\n",
       "      <td>15</td>\n",
       "      <td>75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1792.05</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>410</th>\n",
       "      <td>2019-02-15</td>\n",
       "      <td>20</td>\n",
       "      <td>64</td>\n",
       "      <td>4.2</td>\n",
       "      <td>2292.37</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>411</th>\n",
       "      <td>2019-02-16</td>\n",
       "      <td>20</td>\n",
       "      <td>74</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1366.17</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>412</th>\n",
       "      <td>2019-02-17</td>\n",
       "      <td>26</td>\n",
       "      <td>72</td>\n",
       "      <td>0.0</td>\n",
       "      <td>623.32</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>413</th>\n",
       "      <td>2019-02-18</td>\n",
       "      <td>28</td>\n",
       "      <td>70</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1484.47</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>414</th>\n",
       "      <td>2019-02-19</td>\n",
       "      <td>19</td>\n",
       "      <td>74</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1402.08</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>415</th>\n",
       "      <td>2019-02-20</td>\n",
       "      <td>26</td>\n",
       "      <td>78</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1492.60</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>416</th>\n",
       "      <td>2019-02-21</td>\n",
       "      <td>14</td>\n",
       "      <td>81</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1557.07</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>417</th>\n",
       "      <td>2019-02-22</td>\n",
       "      <td>17</td>\n",
       "      <td>72</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1674.13</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>418</th>\n",
       "      <td>2019-02-23</td>\n",
       "      <td>21</td>\n",
       "      <td>65</td>\n",
       "      <td>1401.6</td>\n",
       "      <td>1608.91</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>419</th>\n",
       "      <td>2019-02-24</td>\n",
       "      <td>7</td>\n",
       "      <td>85</td>\n",
       "      <td>968.6</td>\n",
       "      <td>1736.04</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>420</th>\n",
       "      <td>2019-02-25</td>\n",
       "      <td>11</td>\n",
       "      <td>69</td>\n",
       "      <td>8146.0</td>\n",
       "      <td>7294.79</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>421</th>\n",
       "      <td>2019-02-26</td>\n",
       "      <td>8</td>\n",
       "      <td>62</td>\n",
       "      <td>7566.5</td>\n",
       "      <td>5888.01</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422</th>\n",
       "      <td>2019-02-27</td>\n",
       "      <td>10</td>\n",
       "      <td>70</td>\n",
       "      <td>7237.7</td>\n",
       "      <td>5532.48</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>423</th>\n",
       "      <td>2019-02-28</td>\n",
       "      <td>6</td>\n",
       "      <td>85</td>\n",
       "      <td>6424.0</td>\n",
       "      <td>4885.96</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date  WindSpeed  Humidity  Tonnes   Energy  year  month  day\n",
       "396 2019-02-01         17        70   220.2  2122.04  2019      2    1\n",
       "397 2019-02-02         23        74     0.0  1676.51  2019      2    2\n",
       "398 2019-02-03         20        78     0.0  1652.67  2019      2    3\n",
       "399 2019-02-04         24        78     0.0  2054.34  2019      2    4\n",
       "400 2019-02-05         19        84     0.0  1742.19  2019      2    5\n",
       "401 2019-02-06         21        80     0.0  1526.33  2019      2    6\n",
       "402 2019-02-07         32        81     0.0  1846.30  2019      2    7\n",
       "403 2019-02-08         30        75     0.0  2075.24  2019      2    8\n",
       "404 2019-02-09         40        67     0.0  1296.31  2019      2    9\n",
       "405 2019-02-10         18        75     0.0   737.04  2019      2   10\n",
       "406 2019-02-11         14        74     0.0  1576.83  2019      2   11\n",
       "407 2019-02-12         20        81     0.0  1827.15  2019      2   12\n",
       "408 2019-02-13         20        79     0.0  1635.30  2019      2   13\n",
       "409 2019-02-14         15        75     0.0  1792.05  2019      2   14\n",
       "410 2019-02-15         20        64     4.2  2292.37  2019      2   15\n",
       "411 2019-02-16         20        74     0.0  1366.17  2019      2   16\n",
       "412 2019-02-17         26        72     0.0   623.32  2019      2   17\n",
       "413 2019-02-18         28        70     0.0  1484.47  2019      2   18\n",
       "414 2019-02-19         19        74     0.0  1402.08  2019      2   19\n",
       "415 2019-02-20         26        78     0.0  1492.60  2019      2   20\n",
       "416 2019-02-21         14        81     0.0  1557.07  2019      2   21\n",
       "417 2019-02-22         17        72     0.0  1674.13  2019      2   22\n",
       "418 2019-02-23         21        65  1401.6  1608.91  2019      2   23\n",
       "419 2019-02-24          7        85   968.6  1736.04  2019      2   24\n",
       "420 2019-02-25         11        69  8146.0  7294.79  2019      2   25\n",
       "421 2019-02-26          8        62  7566.5  5888.01  2019      2   26\n",
       "422 2019-02-27         10        70  7237.7  5532.48  2019      2   27\n",
       "423 2019-02-28          6        85  6424.0  4885.96  2019      2   28"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aa = dfPort.loc[(dfPort['year'] == 2019)&(dfPort['month'] == 2)]\n",
    "aa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "7ce3231d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "31968.8"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aa['Tonnes'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "03c9ebad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>WindSpeed</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>Tonnes</th>\n",
       "      <th>Energy</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>424</th>\n",
       "      <td>2019-03-01</td>\n",
       "      <td>8</td>\n",
       "      <td>82</td>\n",
       "      <td>5819.8</td>\n",
       "      <td>4507.98</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>425</th>\n",
       "      <td>2019-03-02</td>\n",
       "      <td>23</td>\n",
       "      <td>76</td>\n",
       "      <td>2363.3</td>\n",
       "      <td>1961.39</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>426</th>\n",
       "      <td>2019-03-03</td>\n",
       "      <td>25</td>\n",
       "      <td>70</td>\n",
       "      <td>3250.6</td>\n",
       "      <td>2659.19</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>427</th>\n",
       "      <td>2019-03-04</td>\n",
       "      <td>31</td>\n",
       "      <td>72</td>\n",
       "      <td>5724.4</td>\n",
       "      <td>4729.89</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>428</th>\n",
       "      <td>2019-03-05</td>\n",
       "      <td>21</td>\n",
       "      <td>71</td>\n",
       "      <td>5931.6</td>\n",
       "      <td>5291.03</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>429</th>\n",
       "      <td>2019-03-06</td>\n",
       "      <td>24</td>\n",
       "      <td>85</td>\n",
       "      <td>6284.9</td>\n",
       "      <td>5373.53</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>430</th>\n",
       "      <td>2019-03-07</td>\n",
       "      <td>27</td>\n",
       "      <td>77</td>\n",
       "      <td>6116.8</td>\n",
       "      <td>5741.23</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>431</th>\n",
       "      <td>2019-03-08</td>\n",
       "      <td>23</td>\n",
       "      <td>72</td>\n",
       "      <td>6227.9</td>\n",
       "      <td>5168.02</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>432</th>\n",
       "      <td>2019-03-09</td>\n",
       "      <td>32</td>\n",
       "      <td>64</td>\n",
       "      <td>2200.5</td>\n",
       "      <td>2766.91</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>433</th>\n",
       "      <td>2019-03-10</td>\n",
       "      <td>21</td>\n",
       "      <td>69</td>\n",
       "      <td>1831.0</td>\n",
       "      <td>2128.11</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>434</th>\n",
       "      <td>2019-03-11</td>\n",
       "      <td>32</td>\n",
       "      <td>62</td>\n",
       "      <td>1258.3</td>\n",
       "      <td>2332.19</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>435</th>\n",
       "      <td>2019-03-12</td>\n",
       "      <td>36</td>\n",
       "      <td>69</td>\n",
       "      <td>3279.0</td>\n",
       "      <td>3457.54</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>2019-03-13</td>\n",
       "      <td>40</td>\n",
       "      <td>62</td>\n",
       "      <td>3307.3</td>\n",
       "      <td>3441.14</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>437</th>\n",
       "      <td>2019-03-14</td>\n",
       "      <td>33</td>\n",
       "      <td>66</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1457.58</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>438</th>\n",
       "      <td>2019-03-15</td>\n",
       "      <td>30</td>\n",
       "      <td>65</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1411.41</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>2019-03-16</td>\n",
       "      <td>26</td>\n",
       "      <td>77</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1067.91</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440</th>\n",
       "      <td>2019-03-17</td>\n",
       "      <td>29</td>\n",
       "      <td>66</td>\n",
       "      <td>0.0</td>\n",
       "      <td>729.73</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>441</th>\n",
       "      <td>2019-03-18</td>\n",
       "      <td>17</td>\n",
       "      <td>69</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1295.89</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>442</th>\n",
       "      <td>2019-03-19</td>\n",
       "      <td>14</td>\n",
       "      <td>81</td>\n",
       "      <td>2182.2</td>\n",
       "      <td>3342.30</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>443</th>\n",
       "      <td>2019-03-20</td>\n",
       "      <td>15</td>\n",
       "      <td>82</td>\n",
       "      <td>5080.7</td>\n",
       "      <td>5535.43</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>444</th>\n",
       "      <td>2019-03-21</td>\n",
       "      <td>13</td>\n",
       "      <td>79</td>\n",
       "      <td>4917.3</td>\n",
       "      <td>5210.12</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>445</th>\n",
       "      <td>2019-03-22</td>\n",
       "      <td>23</td>\n",
       "      <td>75</td>\n",
       "      <td>4652.5</td>\n",
       "      <td>4885.77</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>446</th>\n",
       "      <td>2019-03-23</td>\n",
       "      <td>16</td>\n",
       "      <td>60</td>\n",
       "      <td>1390.1</td>\n",
       "      <td>3028.98</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>447</th>\n",
       "      <td>2019-03-24</td>\n",
       "      <td>25</td>\n",
       "      <td>66</td>\n",
       "      <td>3327.5</td>\n",
       "      <td>4346.87</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>448</th>\n",
       "      <td>2019-03-25</td>\n",
       "      <td>22</td>\n",
       "      <td>63</td>\n",
       "      <td>3856.5</td>\n",
       "      <td>5098.27</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>449</th>\n",
       "      <td>2019-03-26</td>\n",
       "      <td>19</td>\n",
       "      <td>73</td>\n",
       "      <td>6146.1</td>\n",
       "      <td>6248.88</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>450</th>\n",
       "      <td>2019-03-27</td>\n",
       "      <td>18</td>\n",
       "      <td>76</td>\n",
       "      <td>5976.9</td>\n",
       "      <td>6620.72</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>451</th>\n",
       "      <td>2019-03-28</td>\n",
       "      <td>14</td>\n",
       "      <td>74</td>\n",
       "      <td>6063.7</td>\n",
       "      <td>5924.66</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>452</th>\n",
       "      <td>2019-03-29</td>\n",
       "      <td>14</td>\n",
       "      <td>69</td>\n",
       "      <td>5321.9</td>\n",
       "      <td>4887.44</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>453</th>\n",
       "      <td>2019-03-30</td>\n",
       "      <td>13</td>\n",
       "      <td>75</td>\n",
       "      <td>1961.9</td>\n",
       "      <td>2303.76</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>454</th>\n",
       "      <td>2019-03-31</td>\n",
       "      <td>12</td>\n",
       "      <td>66</td>\n",
       "      <td>0.0</td>\n",
       "      <td>543.98</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date  WindSpeed  Humidity  Tonnes   Energy  year  month  day\n",
       "424 2019-03-01          8        82  5819.8  4507.98  2019      3    1\n",
       "425 2019-03-02         23        76  2363.3  1961.39  2019      3    2\n",
       "426 2019-03-03         25        70  3250.6  2659.19  2019      3    3\n",
       "427 2019-03-04         31        72  5724.4  4729.89  2019      3    4\n",
       "428 2019-03-05         21        71  5931.6  5291.03  2019      3    5\n",
       "429 2019-03-06         24        85  6284.9  5373.53  2019      3    6\n",
       "430 2019-03-07         27        77  6116.8  5741.23  2019      3    7\n",
       "431 2019-03-08         23        72  6227.9  5168.02  2019      3    8\n",
       "432 2019-03-09         32        64  2200.5  2766.91  2019      3    9\n",
       "433 2019-03-10         21        69  1831.0  2128.11  2019      3   10\n",
       "434 2019-03-11         32        62  1258.3  2332.19  2019      3   11\n",
       "435 2019-03-12         36        69  3279.0  3457.54  2019      3   12\n",
       "436 2019-03-13         40        62  3307.3  3441.14  2019      3   13\n",
       "437 2019-03-14         33        66     0.0  1457.58  2019      3   14\n",
       "438 2019-03-15         30        65     0.0  1411.41  2019      3   15\n",
       "439 2019-03-16         26        77     0.0  1067.91  2019      3   16\n",
       "440 2019-03-17         29        66     0.0   729.73  2019      3   17\n",
       "441 2019-03-18         17        69     0.0  1295.89  2019      3   18\n",
       "442 2019-03-19         14        81  2182.2  3342.30  2019      3   19\n",
       "443 2019-03-20         15        82  5080.7  5535.43  2019      3   20\n",
       "444 2019-03-21         13        79  4917.3  5210.12  2019      3   21\n",
       "445 2019-03-22         23        75  4652.5  4885.77  2019      3   22\n",
       "446 2019-03-23         16        60  1390.1  3028.98  2019      3   23\n",
       "447 2019-03-24         25        66  3327.5  4346.87  2019      3   24\n",
       "448 2019-03-25         22        63  3856.5  5098.27  2019      3   25\n",
       "449 2019-03-26         19        73  6146.1  6248.88  2019      3   26\n",
       "450 2019-03-27         18        76  5976.9  6620.72  2019      3   27\n",
       "451 2019-03-28         14        74  6063.7  5924.66  2019      3   28\n",
       "452 2019-03-29         14        69  5321.9  4887.44  2019      3   29\n",
       "453 2019-03-30         13        75  1961.9  2303.76  2019      3   30\n",
       "454 2019-03-31         12        66     0.0   543.98  2019      3   31"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aa3 = dfPort.loc[(dfPort['year'] == 2019)&(dfPort['month'] == 3)]\n",
    "aa3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "f2c4f020",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "104472.69999999997"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aa3['Tonnes'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "4f5fd368",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NAME</th>\n",
       "      <th>LOCALTIME</th>\n",
       "      <th>UTCTIME</th>\n",
       "      <th>MOVE</th>\n",
       "      <th>TYPE</th>\n",
       "      <th>GT</th>\n",
       "      <th>DWT</th>\n",
       "      <th>TIME</th>\n",
       "      <th>DATE</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>IMAVERE</td>\n",
       "      <td>2019-03-03T01:17:00</td>\n",
       "      <td>2019-03-03T01:17:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>22746</td>\n",
       "      <td>36746</td>\n",
       "      <td>01:17:00</td>\n",
       "      <td>2019-03-03</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>PU LAN HAI</td>\n",
       "      <td>2019-03-05T18:08:00</td>\n",
       "      <td>2019-03-05T18:08:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>33044</td>\n",
       "      <td>56897</td>\n",
       "      <td>18:08:00</td>\n",
       "      <td>2019-03-05</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>ISADORA</td>\n",
       "      <td>2019-03-14T13:58:00</td>\n",
       "      <td>2019-03-14T13:58:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>21387</td>\n",
       "      <td>34948</td>\n",
       "      <td>13:58:00</td>\n",
       "      <td>2019-03-14</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>VENTURE LUCK</td>\n",
       "      <td>2019-03-19T10:26:00</td>\n",
       "      <td>2019-03-19T10:26:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>26411</td>\n",
       "      <td>43413</td>\n",
       "      <td>10:26:00</td>\n",
       "      <td>2019-03-19</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>EL COMINO</td>\n",
       "      <td>2019-03-20T01:28:00</td>\n",
       "      <td>2019-03-20T01:28:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>34794</td>\n",
       "      <td>61465</td>\n",
       "      <td>01:28:00</td>\n",
       "      <td>2019-03-20</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>FEDERAL DANUBE</td>\n",
       "      <td>2019-03-23T04:13:00</td>\n",
       "      <td>2019-03-23T04:13:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>22734</td>\n",
       "      <td>38289</td>\n",
       "      <td>04:13:00</td>\n",
       "      <td>2019-03-23</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>ISADORA</td>\n",
       "      <td>2019-03-30T03:24:00</td>\n",
       "      <td>2019-03-30T03:24:00</td>\n",
       "      <td>0</td>\n",
       "      <td>Bulk Carrier</td>\n",
       "      <td>21387</td>\n",
       "      <td>34948</td>\n",
       "      <td>03:24:00</td>\n",
       "      <td>2019-03-30</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              NAME            LOCALTIME              UTCTIME  MOVE  \\\n",
       "24         IMAVERE  2019-03-03T01:17:00  2019-03-03T01:17:00     0   \n",
       "26      PU LAN HAI  2019-03-05T18:08:00  2019-03-05T18:08:00     0   \n",
       "29         ISADORA  2019-03-14T13:58:00  2019-03-14T13:58:00     0   \n",
       "31    VENTURE LUCK  2019-03-19T10:26:00  2019-03-19T10:26:00     0   \n",
       "32       EL COMINO  2019-03-20T01:28:00  2019-03-20T01:28:00     0   \n",
       "34  FEDERAL DANUBE  2019-03-23T04:13:00  2019-03-23T04:13:00     0   \n",
       "37         ISADORA  2019-03-30T03:24:00  2019-03-30T03:24:00     0   \n",
       "\n",
       "            TYPE     GT    DWT      TIME       DATE  year  month  day  \n",
       "24  Bulk Carrier  22746  36746  01:17:00 2019-03-03  2019      3    3  \n",
       "26  Bulk Carrier  33044  56897  18:08:00 2019-03-05  2019      3    5  \n",
       "29  Bulk Carrier  21387  34948  13:58:00 2019-03-14  2019      3   14  \n",
       "31  Bulk Carrier  26411  43413  10:26:00 2019-03-19  2019      3   19  \n",
       "32  Bulk Carrier  34794  61465  01:28:00 2019-03-20  2019      3   20  \n",
       "34  Bulk Carrier  22734  38289  04:13:00 2019-03-23  2019      3   23  \n",
       "37  Bulk Carrier  21387  34948  03:24:00 2019-03-30  2019      3   30  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bb3 = df2019.loc[(df2019['month'] == 3)&(df2019['MOVE'] == 0)]\n",
    "bb3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "51b8abc2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "306706"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bb3['DWT'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "08626a0a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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