Getting Started with R
Iain Carmichael, Edited by Robin Cunningham
(Edit July 10, 2017)
Install R
Download the latest version of R from the Comprehensive R Archive Network (CRAN). R is a programming language built for statistical analysis.
Install R Studio
Download R Studio which is an IDE built for R. While you can use R without R Studio, R Studio makes life much better. All R work in this class will be done using Rstudio (At least, that work the IA and I can support.)
Below is an enticing image of Rstudio.
An enticing image of Rstudio. Admit it, your understanding of diamond pricing just skyrocketed.
Basic R commands
You downloaded base R from CRAN.
Run the following in your RStudio console
1 + 1## [1] 2a <- 1
b <- 2
a + b## [1] 3Packages
The power of R comes from the many wonderful R packages people develope. R is an open source language meaning anyone can develope a new R package.
You can install a package from CRAN like this
install.packages("tidyverse")(There are other sources of R packags such as Bioconductor and Github. Packages from CRAN and Bioconductor are vetted (though not perfectly). Packages on Github are not.)
To use code from an R package you need to load it
# ignore the warnings for now
library(tidyverse)## Loading tidyverse: ggplot2
## Loading tidyverse: tibble
## Loading tidyverse: tidyr
## Loading tidyverse: readr
## Loading tidyverse: purrr
## Loading tidyverse: dplyr## Conflicts with tidy packages ----------------------------------------------## filter(): dplyr, stats
## lag(): dplyr, statsYou need to load an R package everytime you want to use it. You only need to install it once.
# IMDB Load the movies data set generously currated by Mine Cetinkaya-Rundel
load(url('https://stat.duke.edu/~mc301/data/movies.Rdata'))The first thing you should do when you get a data set is look at it.
numerical summaries
head() prints the first six rows of a data set (and as many columns that will fit on the screen)
head(movies)## # A tibble: 6 x 32
## title title_type genre runtime mpaa_rating
## <chr> <fctr> <fctr> <dbl> <fctr>
## 1 Filly Brown Feature Film Drama 80 R
## 2 The Dish Feature Film Drama 101 PG-13
## 3 Waiting for Guffman Feature Film Comedy 84 R
## 4 The Age of Innocence Feature Film Drama 139 PG
## 5 Malevolence Feature Film Horror 90 R
## 6 Old Partner Documentary Documentary 78 Unrated
## # ... with 27 more variables: studio <fctr>, thtr_rel_year <dbl>,
## # thtr_rel_month <dbl>, thtr_rel_day <dbl>, dvd_rel_year <dbl>,
## # dvd_rel_month <dbl>, dvd_rel_day <dbl>, imdb_rating <dbl>,
## # imdb_num_votes <int>, critics_rating <fctr>, critics_score <dbl>,
## # audience_rating <fctr>, audience_score <dbl>, best_pic_nom <fctr>,
## # best_pic_win <fctr>, best_actor_win <fctr>, best_actress_win <fctr>,
## # best_dir_win <fctr>, top200_box <fctr>, director <chr>, actor1 <chr>,
## # actor2 <chr>, actor3 <chr>, actor4 <chr>, actor5 <chr>,
## # imdb_url <chr>, rt_url <chr>If you double click a data frame it will pull up R’s built in spreadsheet 
str() gives a different view of the columns and includes some metadata
str(movies)## Classes 'tbl_df', 'tbl' and 'data.frame': 651 obs. of 32 variables:
## $ title : chr "Filly Brown" "The Dish" "Waiting for Guffman" "The Age of Innocence" ...
## $ title_type : Factor w/ 3 levels "Documentary",..: 2 2 2 2 2 1 2 2 1 2 ...
## $ genre : Factor w/ 11 levels "Action & Adventure",..: 6 6 4 6 7 5 6 6 5 6 ...
## $ runtime : num 80 101 84 139 90 78 142 93 88 119 ...
## $ mpaa_rating : Factor w/ 6 levels "G","NC-17","PG",..: 5 4 5 3 5 6 4 5 6 6 ...
## $ studio : Factor w/ 211 levels "20th Century Fox",..: 91 202 167 34 13 163 147 118 88 84 ...
## $ thtr_rel_year : num 2013 2001 1996 1993 2004 ...
## $ thtr_rel_month : num 4 3 8 10 9 1 1 11 9 3 ...
## $ thtr_rel_day : num 19 14 21 1 10 15 1 8 7 2 ...
## $ dvd_rel_year : num 2013 2001 2001 2001 2005 ...
## $ dvd_rel_month : num 7 8 8 11 4 4 2 3 1 8 ...
## $ dvd_rel_day : num 30 28 21 6 19 20 18 2 21 14 ...
## $ imdb_rating : num 5.5 7.3 7.6 7.2 5.1 7.8 7.2 5.5 7.5 6.6 ...
## $ imdb_num_votes : int 899 12285 22381 35096 2386 333 5016 2272 880 12496 ...
## $ critics_rating : Factor w/ 3 levels "Certified Fresh",..: 3 1 1 1 3 2 3 3 2 1 ...
## $ critics_score : num 45 96 91 80 33 91 57 17 90 83 ...
## $ audience_rating : Factor w/ 2 levels "Spilled","Upright": 2 2 2 2 1 2 2 1 2 2 ...
## $ audience_score : num 73 81 91 76 27 86 76 47 89 66 ...
## $ best_pic_nom : Factor w/ 2 levels "no","yes": 1 1 1 1 1 1 1 1 1 1 ...
## $ best_pic_win : Factor w/ 2 levels "no","yes": 1 1 1 1 1 1 1 1 1 1 ...
## $ best_actor_win : Factor w/ 2 levels "no","yes": 1 1 1 2 1 1 1 2 1 1 ...
## $ best_actress_win: Factor w/ 2 levels "no","yes": 1 1 1 1 1 1 1 1 1 1 ...
## $ best_dir_win : Factor w/ 2 levels "no","yes": 1 1 1 2 1 1 1 1 1 1 ...
## $ top200_box : Factor w/ 2 levels "no","yes": 1 1 1 1 1 1 1 1 1 1 ...
## $ director : chr "Michael D. Olmos" "Rob Sitch" "Christopher Guest" "Martin Scorsese" ...
## $ actor1 : chr "Gina Rodriguez" "Sam Neill" "Christopher Guest" "Daniel Day-Lewis" ...
## $ actor2 : chr "Jenni Rivera" "Kevin Harrington" "Catherine O'Hara" "Michelle Pfeiffer" ...
## $ actor3 : chr "Lou Diamond Phillips" "Patrick Warburton" "Parker Posey" "Winona Ryder" ...
## $ actor4 : chr "Emilio Rivera" "Tom Long" "Eugene Levy" "Richard E. Grant" ...
## $ actor5 : chr "Joseph Julian Soria" "Genevieve Mooy" "Bob Balaban" "Alec McCowen" ...
## $ imdb_url : chr "http://www.imdb.com/title/tt1869425/" "http://www.imdb.com/title/tt0205873/" "http://www.imdb.com/title/tt0118111/" "http://www.imdb.com/title/tt0106226/" ...
## $ rt_url : chr "//www.rottentomatoes.com/m/filly_brown_2012/" "//www.rottentomatoes.com/m/dish/" "//www.rottentomatoes.com/m/waiting_for_guffman/" "//www.rottentomatoes.com/m/age_of_innocence/" ...summary() prints out some descriptive statistics of each column
summary(movies)## title title_type genre
## Length:651 Documentary : 55 Drama :305
## Class :character Feature Film:591 Comedy : 87
## Mode :character TV Movie : 5 Action & Adventure: 65
## Mystery & Suspense: 59
## Documentary : 52
## Horror : 23
## (Other) : 60
## runtime mpaa_rating studio
## Min. : 39.0 G : 19 Paramount Pictures : 37
## 1st Qu.: 92.0 NC-17 : 2 Warner Bros. Pictures : 30
## Median :103.0 PG :118 Sony Pictures Home Entertainment: 27
## Mean :105.8 PG-13 :133 Universal Pictures : 23
## 3rd Qu.:115.8 R :329 Warner Home Video : 19
## Max. :267.0 Unrated: 50 (Other) :507
## NA's :1 NA's : 8
## thtr_rel_year thtr_rel_month thtr_rel_day dvd_rel_year
## Min. :1970 Min. : 1.00 Min. : 1.00 Min. :1991
## 1st Qu.:1990 1st Qu.: 4.00 1st Qu.: 7.00 1st Qu.:2001
## Median :2000 Median : 7.00 Median :15.00 Median :2004
## Mean :1998 Mean : 6.74 Mean :14.42 Mean :2004
## 3rd Qu.:2007 3rd Qu.:10.00 3rd Qu.:21.00 3rd Qu.:2008
## Max. :2014 Max. :12.00 Max. :31.00 Max. :2015
## NA's :8
## dvd_rel_month dvd_rel_day imdb_rating imdb_num_votes
## Min. : 1.000 Min. : 1.00 Min. :1.900 Min. : 180
## 1st Qu.: 3.000 1st Qu.: 7.00 1st Qu.:5.900 1st Qu.: 4546
## Median : 6.000 Median :15.00 Median :6.600 Median : 15116
## Mean : 6.333 Mean :15.01 Mean :6.493 Mean : 57533
## 3rd Qu.: 9.000 3rd Qu.:23.00 3rd Qu.:7.300 3rd Qu.: 58300
## Max. :12.000 Max. :31.00 Max. :9.000 Max. :893008
## NA's :8 NA's :8
## critics_rating critics_score audience_rating audience_score
## Certified Fresh:135 Min. : 1.00 Spilled:275 Min. :11.00
## Fresh :209 1st Qu.: 33.00 Upright:376 1st Qu.:46.00
## Rotten :307 Median : 61.00 Median :65.00
## Mean : 57.69 Mean :62.36
## 3rd Qu.: 83.00 3rd Qu.:80.00
## Max. :100.00 Max. :97.00
##
## best_pic_nom best_pic_win best_actor_win best_actress_win best_dir_win
## no :629 no :644 no :558 no :579 no :608
## yes: 22 yes: 7 yes: 93 yes: 72 yes: 43
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## top200_box director actor1 actor2
## no :636 Length:651 Length:651 Length:651
## yes: 15 Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## actor3 actor4 actor5
## Length:651 Length:651 Length:651
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
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## imdb_url rt_url
## Length:651 Length:651
## Class :character Class :character
## Mode :character Mode :character
##
##
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## Vizualization
You can only learn so much by looking a lists of numbers, so let’s try to make some plots.
There are two popular plotting systmes in R. There is the base R system
plot(movies$imdb_rating, movies$critics_score)
and ggplot2.
# ggplot was loaded with tidyverse
ggplot(data = movies) + geom_point(mapping = aes(x = imdb_rating, y = critics_score))
We will use ggplot2 in this course (see readings below about ggplot2 vs base). ggplot2 can be a bit intimidating at first.
ggplot(data=movies, aes(x=audience_score)) + geom_histogram()## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
ggplot2 has a ton of functionality built it and you will learn to love it when you get used to it.
ggplot(data = movies) + geom_point(mapping = aes(x = imdb_rating, y = critics_score, color=mpaa_rating))
Reading
- read the introduction to our textbook (with care!) r4ds