slides.Rmd

title: "R#4: data transformation"
author: "Laurent Modolo [laurent.modolo@ens-lyon.fr](mailto:laurent.modolo@ens-lyon.fr)"
date: "08 Nov 2019"
output:
  beamer_presentation:
    theme: metropolis
    slide_level: 3
    fig_caption: no
    df_print: tibble
    highlight: tango
    latex_engine: xelatex
  slidy_presentation:
    highlight: tango

knitr::opts_chunk$set(echo = FALSE)
library(tidyverse)

R#4: data transformation

The goal of this practical is to practices data transformation with tidyverse. The objectives of this session will be to:

• Filter rows with filter()
• Arrange rows with arrange()
• Select columns with select()
• Add new variables with mutate()
• Combining multiple operations with the pipe %>%

nycflights13

nycflights13::flightscontains all 336,776 flights that departed from New York City in 2013. The data comes from the US Bureau of Transportation Statistics, and is documented in ?flights

library(nycflights13)
library(tidyverse)

nycflights13

flights

• int stands for integers.
• dbl stands for doubles, or real numbers.
• chr stands for character vectors, or strings.
• dttm stands for date-times (a date + a time).
• lgl stands for logical, vectors that contain only TRUE or FALSE.
• fctr stands for factors, which R uses to represent categorical variables with fixed possible values.
• date stands for dates.

Filter rows with filter()

filter() allows you to subset observations based on their values.

filter(flights, month == 1, day == 1)

Filter rows with filter()

dplyr functions never modify their inputs, so if you want to save the result, you’ll need to use the assignment operator, <-

jan1 <- filter(flights, month == 1, day == 1)

R either prints out the results, or saves them to a variable.

(dec25 <- filter(flights, month == 12, day == 25))

Logical operators