Data basics1 / 18

Packages

2 / 18

3 / 18

4 / 18

Using packages

install.packages("name")

Downloads files
to your computer

Do this once per computer

5 / 18

Using packages

install.packages("name")

Downloads files
to your computer

Do this once per computer

library("name")

Loads the package

Do this once per R session

5 / 18

The tidyverse

"The tidyverse is an opinionated collection of R packages designed for data science. All packages share an underlying design philosophy, grammar, and data structures."

… the tidyverse makes data science faster, easier and more fun…

6 / 18

The tidyverse

7 / 18

From "Master the Tidyverse" by RStudio

The tidyverse package

library(tidyverse)

The tidyverse package is a shortcut for
installing and loading all the key tidyverse packages

8 / 18

install.packages("tidyverse")
install.packages("ggplot2")
install.packages("dplyr")
install.packages("tidyr")
install.packages("readr")
install.packages("purrr")
install.packages("tibble")
install.packages("stringr")
install.packages("forcats")
install.packages("lubridate")
install.packages("hms")
install.packages("DBI")
install.packages("haven")
install.packages("httr")
install.packages("jsonlite")
install.packages("readxl")
install.packages("rvest")
install.packages("xml2")
install.packages("modelr")
install.packages("broom")

9 / 18

install.packages("tidyverse")
install.packages("ggplot2")
install.packages("dplyr")
install.packages("tidyr")
install.packages("readr")
install.packages("purrr")
install.packages("tibble")
install.packages("stringr")
install.packages("forcats")
install.packages("lubridate")
install.packages("hms")
install.packages("DBI")
install.packages("haven")
install.packages("httr")
install.packages("jsonlite")
install.packages("readxl")
install.packages("rvest")
install.packages("xml2")
install.packages("modelr")
install.packages("broom")

library("tidyverse")
library("ggplot2")
library("dplyr")
library("tidyr")
library("readr")
library("purrr")
library("tibble")
library("stringr")
library("forcats")

9 / 18

Rectangular data

10 / 18

Data frames and tibbles

Data frames are the most common kind of data objects; used for rectangular data (like spreadsheets)

11 / 18

Data frames and tibbles

Data frames are the most common kind of data objects; used for rectangular data (like spreadsheets)

Data frames: R's native data object

11 / 18

Data frames and tibbles

Data frames are the most common kind of data objects; used for rectangular data (like spreadsheets)

Data frames: R's native data object

Tibbles (tbl): a fancier enhanced kind of data frame

11 / 18

Data frames and tibbles

Data frames are the most common kind of data objects; used for rectangular data (like spreadsheets)

Data frames: R's native data object

Tibbles (tbl): a fancier enhanced kind of data frame

(You really won't notice a difference today)

11 / 18

Vectors and lists

12 / 18

Vectors

Vectors are a list of values of the same time
(all text, or all numbers, etc.)

Make them with c():

c(1, 4, 2, 5, 7)

13 / 18

Vectors

Vectors are a list of values of the same time
(all text, or all numbers, etc.)

Make them with c():

c(1, 4, 2, 5, 7)

You'll usually want to assign them to something:

neat_numbers <- c(1, 4, 2, 5, 7)

13 / 18

Basic data types
  
    Integer
    Whole numbers
    c(1, 2, 3, 4)
  

    Double
    Numbers
    c(1, 2.4, 3.14, 4)
  

    Character
    Text
    c("1", "blue", "fun", "monster")
  

    Logical
    True or false
    c(TRUE, FALSE, TRUE, FALSE)
  

    Factor
    Category
    c("Strongly disagree", "Agree", "Neutral")
  
14 / 18

Importing data

15 / 18

Packages for importing data

	Work with plain text data	`my_data <- read_csv("file.csv")`
	Work with Excel files	`my_data <- read_excel("file.xlsx")`
	Work with Stata, SPSS, and SAS data	`my_data <- read_stata("file.dta")`

16 / 18

Other types of data
  
    Package
    Type of data
  
    jsonlite
    JSON data
  
    xml2
    XML data
  
    httr
    Web APIs
  
    rvest
    Web pages (web scraping)
  
    DBI
    Databases (SQL)
  
17 / 18

Package	Type of data
jsonlite	JSON data
xml2	XML data
httr	Web APIs
rvest	Web pages (web scraping)
DBI	Databases (SQL)

Next up

Data visualization

18 / 18

Data basics1 / 18

Packages

2 / 18

3 / 18

4 / 18

Using packages

install.packages("name")

Downloads files
to your computer

Do this once per computer

5 / 18

Using packages

install.packages("name")

Downloads files
to your computer

Do this once per computer

library("name")

Loads the package

Do this once per R session

5 / 18

The tidyverse

"The tidyverse is an opinionated collection of R packages designed for data science. All packages share an underlying design philosophy, grammar, and data structures."

… the tidyverse makes data science faster, easier and more fun…

6 / 18

The tidyverse

7 / 18

From "Master the Tidyverse" by RStudio

The tidyverse package

library(tidyverse)

The tidyverse package is a shortcut for
installing and loading all the key tidyverse packages

8 / 18

install.packages("tidyverse")
install.packages("ggplot2")
install.packages("dplyr")
install.packages("tidyr")
install.packages("readr")
install.packages("purrr")
install.packages("tibble")
install.packages("stringr")
install.packages("forcats")
install.packages("lubridate")
install.packages("hms")
install.packages("DBI")
install.packages("haven")
install.packages("httr")
install.packages("jsonlite")
install.packages("readxl")
install.packages("rvest")
install.packages("xml2")
install.packages("modelr")
install.packages("broom")

9 / 18

install.packages("tidyverse")
install.packages("ggplot2")
install.packages("dplyr")
install.packages("tidyr")
install.packages("readr")
install.packages("purrr")
install.packages("tibble")
install.packages("stringr")
install.packages("forcats")
install.packages("lubridate")
install.packages("hms")
install.packages("DBI")
install.packages("haven")
install.packages("httr")
install.packages("jsonlite")
install.packages("readxl")
install.packages("rvest")
install.packages("xml2")
install.packages("modelr")
install.packages("broom")

library("tidyverse")
library("ggplot2")
library("dplyr")
library("tidyr")
library("readr")
library("purrr")
library("tibble")
library("stringr")
library("forcats")

9 / 18

Rectangular data

10 / 18

Data frames and tibbles

Data frames are the most common kind of data objects; used for rectangular data (like spreadsheets)

11 / 18

Data frames and tibbles

Data frames are the most common kind of data objects; used for rectangular data (like spreadsheets)

Data frames: R's native data object

11 / 18

Data frames and tibbles

Data frames are the most common kind of data objects; used for rectangular data (like spreadsheets)

Data frames: R's native data object

Tibbles (tbl): a fancier enhanced kind of data frame

11 / 18

Data frames and tibbles

Data frames are the most common kind of data objects; used for rectangular data (like spreadsheets)

Data frames: R's native data object

Tibbles (tbl): a fancier enhanced kind of data frame

(You really won't notice a difference today)

11 / 18

Vectors and lists

12 / 18

Vectors

Vectors are a list of values of the same time
(all text, or all numbers, etc.)

Make them with c():

c(1, 4, 2, 5, 7)

13 / 18

Vectors

Vectors are a list of values of the same time
(all text, or all numbers, etc.)

Make them with c():

c(1, 4, 2, 5, 7)

You'll usually want to assign them to something:

neat_numbers <- c(1, 4, 2, 5, 7)

13 / 18

Basic data types
  
    Integer
    Whole numbers
    c(1, 2, 3, 4)
  

    Double
    Numbers
    c(1, 2.4, 3.14, 4)
  

    Character
    Text
    c("1", "blue", "fun", "monster")
  

    Logical
    True or false
    c(TRUE, FALSE, TRUE, FALSE)
  

    Factor
    Category
    c("Strongly disagree", "Agree", "Neutral")
  
14 / 18

Importing data

15 / 18

Packages for importing data

	Work with plain text data	`my_data <- read_csv("file.csv")`
	Work with Excel files	`my_data <- read_excel("file.xlsx")`
	Work with Stata, SPSS, and SAS data	`my_data <- read_stata("file.dta")`

16 / 18

Other types of data
  
    Package
    Type of data
  
    jsonlite
    JSON data
  
    xml2
    XML data
  
    httr
    Web APIs
  
    rvest
    Web pages (web scraping)
  
    DBI
    Databases (SQL)
  
17 / 18

Package	Type of data
jsonlite	JSON data
xml2	XML data
httr	Web APIs
rvest	Web pages (web scraping)
DBI	Databases (SQL)

Next up

Data visualization

18 / 18

Integer	Whole numbers	`c(1, 2, 3, 4)`
Double	Numbers	`c(1, 2.4, 3.14, 4)`
Character	Text	`c("1", "blue", "fun", "monster")`
Logical	True or false	`c(TRUE, FALSE, TRUE, FALSE)`
Factor	Category	`c("Strongly disagree", "Agree", "Neutral")`

↑, ←, Pg Up, k	Go to previous slide
↓, →, Pg Dn, Space, j	Go to next slide
Home	Go to first slide
End	Go to last slide
Number + Return	Go to specific slide
b / m / f	Toggle blackout / mirrored / fullscreen mode
c	Clone slideshow
p	Toggle presenter mode
t	Restart the presentation timer
?, h	Toggle this help
o	Tile View: Overview of Slides

Integer	Whole numbers	`c(1, 2, 3, 4)`
Double	Numbers	`c(1, 2.4, 3.14, 4)`
Character	Text	`c("1", "blue", "fun", "monster")`
Logical	True or false	`c(TRUE, FALSE, TRUE, FALSE)`
Factor	Category	`c("Strongly disagree", "Agree", "Neutral")`

Data basics

Using packages

Using packages

The tidyverse

The tidyverse

The tidyverse package

Data frames and tibbles

Data frames and tibbles

Data frames and tibbles

Data frames and tibbles

Vectors

Vectors

Basic data types

Packages for importing data

Other types of data

Next up

Help

Data basics

Data basics

Using packages

Using packages

The tidyverse

The tidyverse

The tidyverse package

Data frames and tibbles

Data frames and tibbles

Data frames and tibbles

Data frames and tibbles

Vectors

Vectors

Basic data types

Packages for importing data

Other types of data

Next up