lectura-ficheros-datos.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<!--Header-->\n",
    "<div>\n",
    "    <div class=\"row\" style=\"color: #4D4D4D;font-size: 15px;padding-bottom: 20px\">\n",
    "        <div class=\"col-md-8\">\n",
    "            <h1 style=\"margin:15px 0px 0px;font-size: 40px;\">Manipulación de datos con la librería pandas</h1>\n",
    "            <div style=\"text-align:left;margin-top: 5px;\"></div>\n",
    "        </div>\n",
    "    </div>\n",
    "    <div class=\"row\" style=\"background: #FCB517;padding: 10px 20px;\"></div>\n",
    "\n",
    "\n",
    "</div>\n",
    "<!--/Header-->"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introducción\n",
    "\n",
    "La exporación, manipulación, visualización y análisis de datos empieza con la carga de los datos desde diferentes formatos de ficheros. En esta actividad veremos cómo leer ficheros de tipo `CSV`, `Excel`, `TXT`, `JSON` i `ZIP`, cargarlos en un `DataFrame` y volverlos a guardar en otro fichero."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![Pandas](pandas_logo.svg)\n",
    "\n",
    "Usaremos un paquete de `Python` llamado `pandas`, que facilita la manipulación y el análisis de datos. `Pandas` incorpora estructuras de datos rápidas y flexibles diseñadas para trabajar de una manera intuitiva con datos relacionales o etiquetados."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lo primero que haremos será importar la librería `pandas`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Ficheros CSV\n",
    "\n",
    "El acrónimo `CSV` corresponde a _Comma Separated Values_, es decir, ficheros separados por comas. De hecho, veremos que la función de `pandas` que usaremos para leer este tipo de ficheros también sirve para leer ficheros separados por otros caracteres, como los `TSV` o _Tab-Separated Values_, o los ficheros separados por punto y coma."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "El fichero `CSV` que leeremos corresponde al dataset de la competición [Titanic: Machine Learning from Disaster](https://www.kaggle.com/c/titanic) de [Kaggle](https://www.kaggle.com/)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Para leer un fichero `CSV` usaremos la función [`read_csv`](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html) de `pandas`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": false
   },
   "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>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass  \\\n",
       "0            1         0       3   \n",
       "1            2         1       1   \n",
       "2            3         1       3   \n",
       "3            4         1       1   \n",
       "4            5         0       3   \n",
       "\n",
       "                                                Name     Sex   Age  SibSp  \\\n",
       "0                            Braund, Mr. Owen Harris    male  22.0      1   \n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
       "2                             Heikkinen, Miss. Laina  female  26.0      0   \n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
       "4                           Allen, Mr. William Henry    male  35.0      0   \n",
       "\n",
       "   Parch            Ticket     Fare Cabin Embarked  \n",
       "0      0         A/5 21171   7.2500   NaN        S  \n",
       "1      0          PC 17599  71.2833   C85        C  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3      0            113803  53.1000  C123        S  \n",
       "4      0            373450   8.0500   NaN        S  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"titanic.csv\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Si el fichero no tiene cabecera, especificaremos el parámetro `header=None` y opcionalmente, el nombre de las columnas."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "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>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass  \\\n",
       "0            1         0       3   \n",
       "1            2         1       1   \n",
       "2            3         1       3   \n",
       "3            4         1       1   \n",
       "4            5         0       3   \n",
       "\n",
       "                                                Name     Sex   Age  SibSp  \\\n",
       "0                            Braund, Mr. Owen Harris    male  22.0      1   \n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
       "2                             Heikkinen, Miss. Laina  female  26.0      0   \n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
       "4                           Allen, Mr. William Henry    male  35.0      0   \n",
       "\n",
       "   Parch            Ticket     Fare Cabin Embarked  \n",
       "0      0         A/5 21171   7.2500   NaN        S  \n",
       "1      0          PC 17599  71.2833   C85        C  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3      0            113803  53.1000  C123        S  \n",
       "4      0            373450   8.0500   NaN        S  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"resources/titanic_no_header.csv\", header = None,\n",
    "                 names = [\"PassengerId\", \"Survived\", \"Pclass\", \"Name\",\n",
    "                          \"Sex\", \"Age\", \"SibSp\", \"Parch\", \"Ticket\", \"Fare\", \"Cabin\", \"Embarked\"\n",
    "                         ])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Com podemos ver, el resultado es exactamente el mismo, y la única diferencia es que le hemos tenido que especificar explícitament el nombre de las columnas."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Si queremos leer un fichero que no está separado por comas, especificaremos el separador con el parámetro `sep`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass  \\\n",
       "0            1         0       3   \n",
       "1            2         1       1   \n",
       "2            3         1       3   \n",
       "3            4         1       1   \n",
       "4            5         0       3   \n",
       "\n",
       "                                                Name     Sex   Age  SibSp  \\\n",
       "0                            Braund, Mr. Owen Harris    male  22.0      1   \n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
       "2                             Heikkinen, Miss. Laina  female  26.0      0   \n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
       "4                           Allen, Mr. William Henry    male  35.0      0   \n",
       "\n",
       "   Parch            Ticket     Fare Cabin Embarked  \n",
       "0      0         A/5 21171   7.2500   NaN        S  \n",
       "1      0          PC 17599  71.2833   C85        C  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3      0            113803  53.1000  C123        S  \n",
       "4      0            373450   8.0500   NaN        S  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"resources/titanic.tsv\", sep='\\t')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Para volverlo a guardar en otro fichero, por ejemplo separado por punto y coma, usaremos la función [`to_csv`](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.to_csv.html) de `pandas`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('resources/titanic_semicolon.csv', sep=';')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Si intentamos volver a cargar desde el fichero que hemos creado justo ahora, veremos que nos ha creado una columna `Unnamed`. Esto pasa porque por defecto nos guarda el índice del `DataFrame`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "scrolled": false
   },
   "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>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0  PassengerId  Survived  Pclass  \\\n",
       "0           0            1         0       3   \n",
       "1           1            2         1       1   \n",
       "2           2            3         1       3   \n",
       "3           3            4         1       1   \n",
       "4           4            5         0       3   \n",
       "\n",
       "                                                Name     Sex   Age  SibSp  \\\n",
       "0                            Braund, Mr. Owen Harris    male  22.0      1   \n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
       "2                             Heikkinen, Miss. Laina  female  26.0      0   \n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
       "4                           Allen, Mr. William Henry    male  35.0      0   \n",
       "\n",
       "   Parch            Ticket     Fare Cabin Embarked  \n",
       "0      0         A/5 21171   7.2500   NaN        S  \n",
       "1      0          PC 17599  71.2833   C85        C  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3      0            113803  53.1000  C123        S  \n",
       "4      0            373450   8.0500   NaN        S  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv('resources/titanic_semicolon.csv', sep=';').head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Para evitarlo, le explicitaremos que no quremos que nos guarde el índice mediante el parámetro `index=False`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('resources/titanic_semicolon_no_index.csv', sep=';', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##  Ficheros Excel\n",
    "\n",
    "Aún y ser un software propietario, `Excel` es una de las herramientas más populares y usadas en el tratamiento de datos. `Pandas` es capaz de leer los ficheros que genera este software en sus diferentes versiones."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "El fichero `Excel` que leeremos corresponde al dataset de la competición [TMDB 5000 Movie Dataset](https://www.kaggle.com/tmdb/tmdb-movie-metadata) de [Kaggle](https://www.kaggle.com/). Este `Excel` tiene tres `sheets` que corresponden a las películas de los años `1900s`, `2000s` i `2010s`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Para leer un fichero `Excel` usaremos la función [`read_excel`](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_excel.html) de `pandas`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>Title</th>\n",
       "      <th>Year</th>\n",
       "      <th>Genres</th>\n",
       "      <th>Language</th>\n",
       "      <th>Country</th>\n",
       "      <th>Content Rating</th>\n",
       "      <th>Duration</th>\n",
       "      <th>Aspect Ratio</th>\n",
       "      <th>Budget</th>\n",
       "      <th>Gross Earnings</th>\n",
       "      <th>...</th>\n",
       "      <th>Facebook Likes - Actor 1</th>\n",
       "      <th>Facebook Likes - Actor 2</th>\n",
       "      <th>Facebook Likes - Actor 3</th>\n",
       "      <th>Facebook Likes - cast Total</th>\n",
       "      <th>Facebook likes - Movie</th>\n",
       "      <th>Facenumber in posters</th>\n",
       "      <th>User Votes</th>\n",
       "      <th>Reviews by Users</th>\n",
       "      <th>Reviews by Crtiics</th>\n",
       "      <th>IMDB Score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Intolerance: Love's Struggle Throughout the Ages</td>\n",
       "      <td>1916</td>\n",
       "      <td>Drama|History|War</td>\n",
       "      <td>NaN</td>\n",
       "      <td>USA</td>\n",
       "      <td>Not Rated</td>\n",
       "      <td>123</td>\n",
       "      <td>1.33</td>\n",
       "      <td>385907.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>436</td>\n",
       "      <td>22</td>\n",
       "      <td>9.0</td>\n",
       "      <td>481</td>\n",
       "      <td>691</td>\n",
       "      <td>1</td>\n",
       "      <td>10718</td>\n",
       "      <td>88</td>\n",
       "      <td>69.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Over the Hill to the Poorhouse</td>\n",
       "      <td>1920</td>\n",
       "      <td>Crime|Drama</td>\n",
       "      <td>NaN</td>\n",
       "      <td>USA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>110</td>\n",
       "      <td>1.33</td>\n",
       "      <td>100000.0</td>\n",
       "      <td>3000000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>The Big Parade</td>\n",
       "      <td>1925</td>\n",
       "      <td>Drama|Romance|War</td>\n",
       "      <td>NaN</td>\n",
       "      <td>USA</td>\n",
       "      <td>Not Rated</td>\n",
       "      <td>151</td>\n",
       "      <td>1.33</td>\n",
       "      <td>245000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>81</td>\n",
       "      <td>12</td>\n",
       "      <td>6.0</td>\n",
       "      <td>108</td>\n",
       "      <td>226</td>\n",
       "      <td>0</td>\n",
       "      <td>4849</td>\n",
       "      <td>45</td>\n",
       "      <td>48.0</td>\n",
       "      <td>8.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Metropolis</td>\n",
       "      <td>1927</td>\n",
       "      <td>Drama|Sci-Fi</td>\n",
       "      <td>German</td>\n",
       "      <td>Germany</td>\n",
       "      <td>Not Rated</td>\n",
       "      <td>145</td>\n",
       "      <td>1.33</td>\n",
       "      <td>6000000.0</td>\n",
       "      <td>26435.0</td>\n",
       "      <td>...</td>\n",
       "      <td>136</td>\n",
       "      <td>23</td>\n",
       "      <td>18.0</td>\n",
       "      <td>203</td>\n",
       "      <td>12000</td>\n",
       "      <td>1</td>\n",
       "      <td>111841</td>\n",
       "      <td>413</td>\n",
       "      <td>260.0</td>\n",
       "      <td>8.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Pandora's Box</td>\n",
       "      <td>1929</td>\n",
       "      <td>Crime|Drama|Romance</td>\n",
       "      <td>German</td>\n",
       "      <td>Germany</td>\n",
       "      <td>Not Rated</td>\n",
       "      <td>110</td>\n",
       "      <td>1.33</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9950.0</td>\n",
       "      <td>...</td>\n",
       "      <td>426</td>\n",
       "      <td>20</td>\n",
       "      <td>3.0</td>\n",
       "      <td>455</td>\n",
       "      <td>926</td>\n",
       "      <td>1</td>\n",
       "      <td>7431</td>\n",
       "      <td>84</td>\n",
       "      <td>71.0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               Title  Year  \\\n",
       "0  Intolerance: Love's Struggle Throughout the Ages   1916   \n",
       "1                    Over the Hill to the Poorhouse   1920   \n",
       "2                                    The Big Parade   1925   \n",
       "3                                        Metropolis   1927   \n",
       "4                                     Pandora's Box   1929   \n",
       "\n",
       "                Genres Language  Country Content Rating  Duration  \\\n",
       "0    Drama|History|War      NaN      USA      Not Rated       123   \n",
       "1          Crime|Drama      NaN      USA            NaN       110   \n",
       "2    Drama|Romance|War      NaN      USA      Not Rated       151   \n",
       "3         Drama|Sci-Fi   German  Germany      Not Rated       145   \n",
       "4  Crime|Drama|Romance   German  Germany      Not Rated       110   \n",
       "\n",
       "   Aspect Ratio     Budget  Gross Earnings  ... Facebook Likes - Actor 1  \\\n",
       "0          1.33   385907.0             NaN  ...                      436   \n",
       "1          1.33   100000.0       3000000.0  ...                        2   \n",
       "2          1.33   245000.0             NaN  ...                       81   \n",
       "3          1.33  6000000.0         26435.0  ...                      136   \n",
       "4          1.33        NaN          9950.0  ...                      426   \n",
       "\n",
       "  Facebook Likes - Actor 2 Facebook Likes - Actor 3  \\\n",
       "0                       22                      9.0   \n",
       "1                        2                      0.0   \n",
       "2                       12                      6.0   \n",
       "3                       23                     18.0   \n",
       "4                       20                      3.0   \n",
       "\n",
       "  Facebook Likes - cast Total  Facebook likes - Movie  Facenumber in posters  \\\n",
       "0                         481                     691                      1   \n",
       "1                           4                       0                      1   \n",
       "2                         108                     226                      0   \n",
       "3                         203                   12000                      1   \n",
       "4                         455                     926                      1   \n",
       "\n",
       "   User Votes  Reviews by Users  Reviews by Crtiics  IMDB Score  \n",
       "0       10718                88                69.0         8.0  \n",
       "1           5                 1                 1.0         4.8  \n",
       "2        4849                45                48.0         8.3  \n",
       "3      111841               413               260.0         8.3  \n",
       "4        7431                84                71.0         8.0  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xls_file = pd.read_excel('resources/movies.xls')\n",
    "xls_file.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Nuestro `Excel` tiene tres `sheets`. Si no le decimos nada, por defecto la función [`read_excel`](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_excel.html) nos carga el primero. Si queremos especificar otro, lo podemos hacer por el nombre mediante el parámetro `sheet_name`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "scrolled": true
   },
   "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>Title</th>\n",
       "      <th>Year</th>\n",
       "      <th>Genres</th>\n",
       "      <th>Language</th>\n",
       "      <th>Country</th>\n",
       "      <th>Content Rating</th>\n",
       "      <th>Duration</th>\n",
       "      <th>Aspect Ratio</th>\n",
       "      <th>Budget</th>\n",
       "      <th>Gross Earnings</th>\n",
       "      <th>...</th>\n",
       "      <th>Facebook Likes - Actor 1</th>\n",
       "      <th>Facebook Likes - Actor 2</th>\n",
       "      <th>Facebook Likes - Actor 3</th>\n",
       "      <th>Facebook Likes - cast Total</th>\n",
       "      <th>Facebook likes - Movie</th>\n",
       "      <th>Facenumber in posters</th>\n",
       "      <th>User Votes</th>\n",
       "      <th>Reviews by Users</th>\n",
       "      <th>Reviews by Crtiics</th>\n",
       "      <th>IMDB Score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>127 Hours</td>\n",
       "      <td>2010.0</td>\n",
       "      <td>Adventure|Biography|Drama|Thriller</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>R</td>\n",
       "      <td>94.0</td>\n",
       "      <td>1.85</td>\n",
       "      <td>18000000.0</td>\n",
       "      <td>18329466.0</td>\n",
       "      <td>...</td>\n",
       "      <td>11000.0</td>\n",
       "      <td>642.0</td>\n",
       "      <td>223.0</td>\n",
       "      <td>11984</td>\n",
       "      <td>63000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>279179</td>\n",
       "      <td>440.0</td>\n",
       "      <td>450.0</td>\n",
       "      <td>7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3 Backyards</td>\n",
       "      <td>2010.0</td>\n",
       "      <td>Drama</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>R</td>\n",
       "      <td>88.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>300000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>795.0</td>\n",
       "      <td>659.0</td>\n",
       "      <td>301.0</td>\n",
       "      <td>1884</td>\n",
       "      <td>92</td>\n",
       "      <td>0.0</td>\n",
       "      <td>554</td>\n",
       "      <td>23.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>5.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2010.0</td>\n",
       "      <td>Comedy|Drama|Romance</td>\n",
       "      <td>German</td>\n",
       "      <td>Germany</td>\n",
       "      <td>Unrated</td>\n",
       "      <td>119.0</td>\n",
       "      <td>2.35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>59774.0</td>\n",
       "      <td>...</td>\n",
       "      <td>24.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>69</td>\n",
       "      <td>2000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4212</td>\n",
       "      <td>18.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>6.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8: The Mormon Proposition</td>\n",
       "      <td>2010.0</td>\n",
       "      <td>Documentary</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>R</td>\n",
       "      <td>80.0</td>\n",
       "      <td>1.78</td>\n",
       "      <td>2500000.0</td>\n",
       "      <td>99851.0</td>\n",
       "      <td>...</td>\n",
       "      <td>191.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>210</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1138</td>\n",
       "      <td>30.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>7.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>A Turtle's Tale: Sammy's Adventures</td>\n",
       "      <td>2010.0</td>\n",
       "      <td>Adventure|Animation|Family</td>\n",
       "      <td>English</td>\n",
       "      <td>France</td>\n",
       "      <td>PG</td>\n",
       "      <td>88.0</td>\n",
       "      <td>2.35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>783.0</td>\n",
       "      <td>749.0</td>\n",
       "      <td>602.0</td>\n",
       "      <td>3874</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5385</td>\n",
       "      <td>22.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>6.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  Title    Year  \\\n",
       "0                            127 Hours   2010.0   \n",
       "1                          3 Backyards   2010.0   \n",
       "2                                    3   2010.0   \n",
       "3            8: The Mormon Proposition   2010.0   \n",
       "4  A Turtle's Tale: Sammy's Adventures   2010.0   \n",
       "\n",
       "                               Genres Language  Country Content Rating  \\\n",
       "0  Adventure|Biography|Drama|Thriller  English      USA              R   \n",
       "1                               Drama  English      USA              R   \n",
       "2                Comedy|Drama|Romance   German  Germany        Unrated   \n",
       "3                         Documentary  English      USA              R   \n",
       "4          Adventure|Animation|Family  English   France             PG   \n",
       "\n",
       "   Duration  Aspect Ratio      Budget  Gross Earnings     ...      \\\n",
       "0      94.0          1.85  18000000.0      18329466.0     ...       \n",
       "1      88.0           NaN    300000.0             NaN     ...       \n",
       "2     119.0          2.35         NaN         59774.0     ...       \n",
       "3      80.0          1.78   2500000.0         99851.0     ...       \n",
       "4      88.0          2.35         NaN             NaN     ...       \n",
       "\n",
       "  Facebook Likes - Actor 1 Facebook Likes - Actor 2 Facebook Likes - Actor 3  \\\n",
       "0                  11000.0                    642.0                    223.0   \n",
       "1                    795.0                    659.0                    301.0   \n",
       "2                     24.0                     20.0                      9.0   \n",
       "3                    191.0                     12.0                      5.0   \n",
       "4                    783.0                    749.0                    602.0   \n",
       "\n",
       "  Facebook Likes - cast Total  Facebook likes - Movie  Facenumber in posters  \\\n",
       "0                       11984                   63000                    0.0   \n",
       "1                        1884                      92                    0.0   \n",
       "2                          69                    2000                    0.0   \n",
       "3                         210                       0                    0.0   \n",
       "4                        3874                       0                    2.0   \n",
       "\n",
       "   User Votes  Reviews by Users  Reviews by Crtiics  IMDB Score  \n",
       "0      279179             440.0               450.0         7.6  \n",
       "1         554              23.0                20.0         5.2  \n",
       "2        4212              18.0                76.0         6.8  \n",
       "3        1138              30.0                28.0         7.1  \n",
       "4        5385              22.0                56.0         6.1  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xls_file = pd.read_excel('movies.xls', sheet_name='2010s')\n",
    "xls_file.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Para volverlo a guardar en otro fichero `Excel` usaremos la función  [`to_excel`](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.to_excel.html) de `pandas`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "xls_file.to_excel('resources/movies_2010.xlsx', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Ficheros TXT"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A veces los ficheros de datos no estan separados por ningún caracter en concreto, sino que cada campo tiene una medida fija. Estos tipos de ficheros se llaman _Fixed Width Format_, o de campos de ancho fija. La función [`read_fwf`](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_fwf.html) de `pandas` nos permite tratar con estos ficheros. Si no especificamos el ancho de los campos, intentará inferir la estructura del fichero."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Los datos que usaremos son los [_ratings_](https://ratings.fide.com/download.phtml) de los jugadores de la Federación Internacional de Ajedrez."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>ID Number</th>\n",
       "      <th>Name</th>\n",
       "      <th>Fed</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Tit</th>\n",
       "      <th>WTit</th>\n",
       "      <th>OTit</th>\n",
       "      <th>FOA</th>\n",
       "      <th>SRtng</th>\n",
       "      <th>SGm</th>\n",
       "      <th>SK</th>\n",
       "      <th>RRtng</th>\n",
       "      <th>RGm</th>\n",
       "      <th>Rk</th>\n",
       "      <th>BRtng</th>\n",
       "      <th>BGm</th>\n",
       "      <th>BK</th>\n",
       "      <th>B-day</th>\n",
       "      <th>Flag</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10224084</td>\n",
       "      <td>A B M Hasibuzzaman, Tapan</td>\n",
       "      <td>BAN</td>\n",
       "      <td>M</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1977</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>35077023</td>\n",
       "      <td>A Chakravarthy</td>\n",
       "      <td>IND</td>\n",
       "      <td>M</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1151.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1986</td>\n",
       "      <td>i</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10207538</td>\n",
       "      <td>A E M, Doshtagir</td>\n",
       "      <td>BAN</td>\n",
       "      <td>M</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1840.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>1836.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>1860.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>1974</td>\n",
       "      <td>i</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5716365</td>\n",
       "      <td>A Hamid, Harman</td>\n",
       "      <td>MAS</td>\n",
       "      <td>M</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NI</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1593.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10207546</td>\n",
       "      <td>A K M Aminul, Islam</td>\n",
       "      <td>BAN</td>\n",
       "      <td>M</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID Number                       Name  Fed Sex  Tit WTit OTit  FOA   SRtng  \\\n",
       "0   10224084  A B M Hasibuzzaman, Tapan  BAN   M  NaN  NaN  NaN  NaN     NaN   \n",
       "1   35077023             A Chakravarthy  IND   M  NaN  NaN  NaN  NaN  1151.0   \n",
       "2   10207538           A E M, Doshtagir  BAN   M  NaN  NaN  NaN  NaN  1840.0   \n",
       "3    5716365            A Hamid, Harman  MAS   M  NaN  NaN   NI  NaN     NaN   \n",
       "4   10207546        A K M Aminul, Islam  BAN   M  NaN  NaN  NaN  NaN     NaN   \n",
       "\n",
       "   SGm    SK   RRtng  RGm    Rk   BRtng  BGm    BK  B-day Flag  \n",
       "0  NaN   NaN     NaN  NaN   NaN     NaN  NaN   NaN   1977  NaN  \n",
       "1  0.0  40.0     NaN  NaN   NaN     NaN  NaN   NaN   1986    i  \n",
       "2  0.0  40.0  1836.0  0.0  20.0  1860.0  0.0  20.0   1974    i  \n",
       "3  NaN   NaN  1593.0  0.0  20.0     NaN  NaN   NaN      0  NaN  \n",
       "4  NaN   NaN     NaN  NaN   NaN     NaN  NaN   NaN      0  NaN  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_fwf('resources/players_list_foa.txt')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Ficheros JSON\n",
    "\n",
    "`JSON`, acrónimo de _JavaScript Object Notation_, es un formato estándard de transferencia de datos que utiliza una sintaxi legible para los humanos y que consiste en listas anidadas de pares clave/valor. Por [ejemplo](http://json.org/example.html), aquí podemos ver un registro de una base de datos no relacional en formato JSON:\n",
    "\n",
    "```json\n",
    "{\n",
    "  \"menu\": {\n",
    "    \"id\": \"file\",\n",
    "    \"value\": \"File\",\n",
    "    \"popup\": {\n",
    "      \"menuitem\": [\n",
    "        {\"value\": \"New\", \"onclick\": \"CreateNewDoc()\"},\n",
    "        {\"value\": \"Open\", \"onclick\": \"OpenDoc()\"},\n",
    "        {\"value\": \"Close\", \"onclick\": \"CloseDoc()\"}\n",
    "      ]\n",
    "    }\n",
    "  }\n",
    "}\n",
    "```\n",
    "\n",
    "Como podemos ver, los datos no están estructurados en formato tabla. Cuando carguemos el `JSON` a un `DataFrame` con `pandas`, cada columna corresponderá a una de las claves de primer nivel de cada registro. Y su valor será, en el caso de listas anidadas, una lista en formato `JSON`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": false
   },
   "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>assignee</th>\n",
       "      <th>assignees</th>\n",
       "      <th>author_association</th>\n",
       "      <th>body</th>\n",
       "      <th>closed_at</th>\n",
       "      <th>comments</th>\n",
       "      <th>comments_url</th>\n",
       "      <th>created_at</th>\n",
       "      <th>events_url</th>\n",
       "      <th>html_url</th>\n",
       "      <th>...</th>\n",
       "      <th>user.id</th>\n",
       "      <th>user.login</th>\n",
       "      <th>user.organizations_url</th>\n",
       "      <th>user.received_events_url</th>\n",
       "      <th>user.repos_url</th>\n",
       "      <th>user.site_admin</th>\n",
       "      <th>user.starred_url</th>\n",
       "      <th>user.subscriptions_url</th>\n",
       "      <th>user.type</th>\n",
       "      <th>user.url</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>None</td>\n",
       "      <td>[]</td>\n",
       "      <td>OWNER</td>\n",
       "      <td>This adds the matplotlib.sphinxext.plot_direct...</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>https://api.github.com/repos/pandas-dev/pandas...</td>\n",
       "      <td>2018-03-06T15:20:53Z</td>\n",
       "      <td>https://api.github.com/repos/pandas-dev/pandas...</td>\n",
       "      <td>https://github.com/pandas-dev/pandas/pull/20015</td>\n",
       "      <td>...</td>\n",
       "      <td>1020496</td>\n",
       "      <td>jorisvandenbossche</td>\n",
       "      <td>https://api.github.com/users/jorisvandenbossch...</td>\n",
       "      <td>https://api.github.com/users/jorisvandenbossch...</td>\n",
       "      <td>https://api.github.com/users/jorisvandenbossch...</td>\n",
       "      <td>False</td>\n",
       "      <td>https://api.github.com/users/jorisvandenbossch...</td>\n",
       "      <td>https://api.github.com/users/jorisvandenbossch...</td>\n",
       "      <td>User</td>\n",
       "      <td>https://api.github.com/users/jorisvandenbossche</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>None</td>\n",
       "      <td>[]</td>\n",
       "      <td>CONTRIBUTOR</td>\n",
       "      <td>xref #18614  \\r\\n\\r\\n- [ ] remove the classes,...</td>\n",
       "      <td>None</td>\n",
       "      <td>1</td>\n",
       "      <td>https://api.github.com/repos/pandas-dev/pandas...</td>\n",
       "      <td>2018-03-06T11:40:05Z</td>\n",
       "      <td>https://api.github.com/repos/pandas-dev/pandas...</td>\n",
       "      <td>https://github.com/pandas-dev/pandas/issues/20014</td>\n",
       "      <td>...</td>\n",
       "      <td>953992</td>\n",
       "      <td>jreback</td>\n",
       "      <td>https://api.github.com/users/jreback/orgs</td>\n",
       "      <td>https://api.github.com/users/jreback/received_...</td>\n",
       "      <td>https://api.github.com/users/jreback/repos</td>\n",
       "      <td>False</td>\n",
       "      <td>https://api.github.com/users/jreback/starred{/...</td>\n",
       "      <td>https://api.github.com/users/jreback/subscript...</td>\n",
       "      <td>User</td>\n",
       "      <td>https://api.github.com/users/jreback</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>None</td>\n",
       "      <td>[]</td>\n",
       "      <td>NONE</td>\n",
       "      <td>#### Code Sample, a copy-pastable example if p...</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>https://api.github.com/repos/pandas-dev/pandas...</td>\n",
       "      <td>2018-03-06T11:22:54Z</td>\n",
       "      <td>https://api.github.com/repos/pandas-dev/pandas...</td>\n",
       "      <td>https://github.com/pandas-dev/pandas/issues/20012</td>\n",
       "      <td>...</td>\n",
       "      <td>25247745</td>\n",
       "      <td>weber-s</td>\n",
       "      <td>https://api.github.com/users/weber-s/orgs</td>\n",
       "      <td>https://api.github.com/users/weber-s/received_...</td>\n",
       "      <td>https://api.github.com/users/weber-s/repos</td>\n",
       "      <td>False</td>\n",
       "      <td>https://api.github.com/users/weber-s/starred{/...</td>\n",
       "      <td>https://api.github.com/users/weber-s/subscript...</td>\n",
       "      <td>User</td>\n",
       "      <td>https://api.github.com/users/weber-s</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>None</td>\n",
       "      <td>[]</td>\n",
       "      <td>CONTRIBUTOR</td>\n",
       "      <td>```\\r\\npandas/tests/frame/test_operators.py::T...</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>https://api.github.com/repos/pandas-dev/pandas...</td>\n",
       "      <td>2018-03-06T11:03:58Z</td>\n",
       "      <td>https://api.github.com/repos/pandas-dev/pandas...</td>\n",
       "      <td>https://github.com/pandas-dev/pandas/issues/20011</td>\n",
       "      <td>...</td>\n",
       "      <td>953992</td>\n",
       "      <td>jreback</td>\n",
       "      <td>https://api.github.com/users/jreback/orgs</td>\n",
       "      <td>https://api.github.com/users/jreback/received_...</td>\n",
       "      <td>https://api.github.com/users/jreback/repos</td>\n",
       "      <td>False</td>\n",
       "      <td>https://api.github.com/users/jreback/starred{/...</td>\n",
       "      <td>https://api.github.com/users/jreback/subscript...</td>\n",
       "      <td>User</td>\n",
       "      <td>https://api.github.com/users/jreback</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>None</td>\n",
       "      <td>[]</td>\n",
       "      <td>CONTRIBUTOR</td>\n",
       "      <td>#### Code Sample, a copy-pastable example if p...</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>https://api.github.com/repos/pandas-dev/pandas...</td>\n",
       "      <td>2018-03-06T00:24:20Z</td>\n",
       "      <td>https://api.github.com/repos/pandas-dev/pandas...</td>\n",
       "      <td>https://github.com/pandas-dev/pandas/issues/20008</td>\n",
       "      <td>...</td>\n",
       "      <td>1224492</td>\n",
       "      <td>toobaz</td>\n",
       "      <td>https://api.github.com/users/toobaz/orgs</td>\n",
       "      <td>https://api.github.com/users/toobaz/received_e...</td>\n",
       "      <td>https://api.github.com/users/toobaz/repos</td>\n",
       "      <td>False</td>\n",
       "      <td>https://api.github.com/users/toobaz/starred{/o...</td>\n",
       "      <td>https://api.github.com/users/toobaz/subscriptions</td>\n",
       "      <td>User</td>\n",
       "      <td>https://api.github.com/users/toobaz</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 73 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  assignee assignees author_association  \\\n",
       "0     None        []              OWNER   \n",
       "1     None        []        CONTRIBUTOR   \n",
       "2     None        []               NONE   \n",
       "3     None        []        CONTRIBUTOR   \n",
       "4     None        []        CONTRIBUTOR   \n",
       "\n",
       "                                                body closed_at  comments  \\\n",
       "0  This adds the matplotlib.sphinxext.plot_direct...      None         0   \n",
       "1  xref #18614  \\r\\n\\r\\n- [ ] remove the classes,...      None         1   \n",
       "2  #### Code Sample, a copy-pastable example if p...      None         0   \n",
       "3  ```\\r\\npandas/tests/frame/test_operators.py::T...      None         0   \n",
       "4  #### Code Sample, a copy-pastable example if p...      None         0   \n",
       "\n",
       "                                        comments_url            created_at  \\\n",
       "0  https://api.github.com/repos/pandas-dev/pandas...  2018-03-06T15:20:53Z   \n",
       "1  https://api.github.com/repos/pandas-dev/pandas...  2018-03-06T11:40:05Z   \n",
       "2  https://api.github.com/repos/pandas-dev/pandas...  2018-03-06T11:22:54Z   \n",
       "3  https://api.github.com/repos/pandas-dev/pandas...  2018-03-06T11:03:58Z   \n",
       "4  https://api.github.com/repos/pandas-dev/pandas...  2018-03-06T00:24:20Z   \n",
       "\n",
       "                                          events_url  \\\n",
       "0  https://api.github.com/repos/pandas-dev/pandas...   \n",
       "1  https://api.github.com/repos/pandas-dev/pandas...   \n",
       "2  https://api.github.com/repos/pandas-dev/pandas...   \n",
       "3  https://api.github.com/repos/pandas-dev/pandas...   \n",
       "4  https://api.github.com/repos/pandas-dev/pandas...   \n",
       "\n",
       "                                            html_url  ...   user.id  \\\n",
       "0    https://github.com/pandas-dev/pandas/pull/20015  ...   1020496   \n",
       "1  https://github.com/pandas-dev/pandas/issues/20014  ...    953992   \n",
       "2  https://github.com/pandas-dev/pandas/issues/20012  ...  25247745   \n",
       "3  https://github.com/pandas-dev/pandas/issues/20011  ...    953992   \n",
       "4  https://github.com/pandas-dev/pandas/issues/20008  ...   1224492   \n",
       "\n",
       "           user.login                             user.organizations_url  \\\n",
       "0  jorisvandenbossche  https://api.github.com/users/jorisvandenbossch...   \n",
       "1             jreback          https://api.github.com/users/jreback/orgs   \n",
       "2             weber-s          https://api.github.com/users/weber-s/orgs   \n",
       "3             jreback          https://api.github.com/users/jreback/orgs   \n",
       "4              toobaz           https://api.github.com/users/toobaz/orgs   \n",
       "\n",
       "                            user.received_events_url  \\\n",
       "0  https://api.github.com/users/jorisvandenbossch...   \n",
       "1  https://api.github.com/users/jreback/received_...   \n",
       "2  https://api.github.com/users/weber-s/received_...   \n",
       "3  https://api.github.com/users/jreback/received_...   \n",
       "4  https://api.github.com/users/toobaz/received_e...   \n",
       "\n",
       "                                      user.repos_url  user.site_admin  \\\n",
       "0  https://api.github.com/users/jorisvandenbossch...            False   \n",
       "1         https://api.github.com/users/jreback/repos            False   \n",
       "2         https://api.github.com/users/weber-s/repos            False   \n",
       "3         https://api.github.com/users/jreback/repos            False   \n",
       "4          https://api.github.com/users/toobaz/repos            False   \n",
       "\n",
       "                                    user.starred_url  \\\n",
       "0  https://api.github.com/users/jorisvandenbossch...   \n",
       "1  https://api.github.com/users/jreback/starred{/...   \n",
       "2  https://api.github.com/users/weber-s/starred{/...   \n",
       "3  https://api.github.com/users/jreback/starred{/...   \n",
       "4  https://api.github.com/users/toobaz/starred{/o...   \n",
       "\n",
       "                              user.subscriptions_url user.type  \\\n",
       "0  https://api.github.com/users/jorisvandenbossch...      User   \n",
       "1  https://api.github.com/users/jreback/subscript...      User   \n",
       "2  https://api.github.com/users/weber-s/subscript...      User   \n",
       "3  https://api.github.com/users/jreback/subscript...      User   \n",
       "4  https://api.github.com/users/toobaz/subscriptions      User   \n",
       "\n",
       "                                          user.url  \n",
       "0  https://api.github.com/users/jorisvandenbossche  \n",
       "1             https://api.github.com/users/jreback  \n",
       "2             https://api.github.com/users/weber-s  \n",
       "3             https://api.github.com/users/jreback  \n",
       "4              https://api.github.com/users/toobaz  \n",
       "\n",
       "[5 rows x 73 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import json\n",
    "from pandas.io.json import json_normalize\n",
    "\n",
    "with open('resources/pandas_issues.json') as f:\n",
    "    issues = json.load(f)\n",
    "    \n",
    "df = json_normalize(issues)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Vemos que ahora los campos ya no contienen listas de valores. Y es que el campo `user`, por ejemplo, se nos ha convertido en los camps `user.id`, `user.login`, `user.organizations_url`, `user.received_events_url`, `user.repos_url`, `user.site_admin`, `user.starred_url`, `user.subscriptions_url`, `user.type` y `user.url`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}