worksheet-1.R

## Editor

vals <- seq(1,100)

vals <- seq(from = 1,
  to = 100)

## Load Data

storm <- read.csv('data/StormEvents.csv')

storm <- read.csv('data/StormEvents.csv', na.strings = c('NA', 'UNKNOWN'))

## Data Structures

## Lists

x <- list('abc', 1:3, sin)

## Vectors

c(1,2,3)

## Data Types

## Factors

education <- factor(
  c('college', 'highschool', 'college', 'middle', 'middle'),
  levels = c('middle', 'highschool', 'college'))

## Data Frames

income <- c(32000, 28000, 89000, 0, 0)
df <- data.frame(education, income)

## Parts and Subsets

## Names

names(df) <- c('ed', 'inc')

## Subsetting 

days <- c(
  'Sunday', 'Monday', 'Tuesday',
  'Wednesday', 'Thursday', 'Friday',
  'Saturday')

weekdays <- days[2:6]

weekend <- days[c(1,7)]

## Functions

first <- function(a) {
       result <- a[1, ]
       return(result)
}

## Flow Control

if (df$ed[1] == "college") {
  print(df$inc[1])
} else {
  print("no college education")
}


first <- function(dat) {
  if (is.vector(dat)) {
    result <- dat[[1]]
  } else {
    result <- dat[1, ]
  }
  return(result)
}

## Distributions and Statistics

rnorm(n = 10)

x <- rnorm(n = 100, mean = 15, sd = 7)
y <- rbinom(n = 100, size = 20, prob = .85)


# Exercise 1
x <- (-0.3 + sqrt(0.3^2-4*1.5*(-2.9)))/(2*1.5)

# Exercise 2
storm <- read.csv(
  'data/StormEvents.csv',
  stringsAsFactors = FALSE)
storm$STATE <- factor(storm$STATE)

#Exercise 3
typeof(income)
list1 <- list(1:5)
typeof(list1)
comb <- c(income, list1)
typeof(comb)

#Exercise 4
species <- c('cat', 'dog', 'horse', 'fish')
abund <- 1:8
data <- data.frame(species, abund)

#Exercise 5
days[c(-1, -7)]
days[seq(2,7,2)]

#Exercise 6
first <- function(dat) {
  if (is.vector(dat)) {
    result <- dat[[1]]
  } else if (is.matrix(dat)) {
    result <- dat[[1, 1]]
  } else {
    result <- dat[1, ]
  }
  return(result)
}