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R data wrangling Cheat Sheet (DRAFT) by

This is a draft cheat sheet. It is a work in progress and is not finished yet.

Read / Write .csv

read.csv(file.csv)
write.csv(df, file.csv)

Meta Data

summar­y(df)
 
str(df)
 
ls()
 
dir()
 
length(df)
 
dim(df)
 
class (df)
 
nrow(df) / ncol(df)
 
colnam­es(df)

Arrange

rename(df, varold = varnew)
select(df, var1, var2)
arrange(df, var) / arrange(df, desc(var))

Filter

filter(df, var1 > 10) / df[df$var1 > 10, ]
slice(df, 10:15) / df[10:15, ] # select rows
distinct(df, var)
sample_frac(df, 0.5, replace = FALSE) / sample_n(df, 10, replace = FALSE)
select(df, col1, col2, ...) / df[, c('col1', 'col2')]
select(df, contains() starts_with() ends_with())
na.omit(df)

Useful Functions

min() / max()
 
first() / last()
 
n() / n_dist­inct()
 
mean() / median()
 
lead() / lag()
 
var() / sd()
 
between(a, b)
 
cumsum()
 
is.na()
 
%in%
 
if_else() / case_w­hen()
 
coalesce()
 
na_if()
 
sum(!i­s.na())
 
quanti­le(x, probs=)
 
seq(1, 10)
 
rep(c(­1,2,3), 2)
 
is.na() / is.null() / is.num­eric()
 
as.cha­rac­ter() / as.num­eric() ...
 
replace(x, list, values)
 
round(x, n)
 
mod()
 
abs()
 
corr(x) / corr(x, y)
 
weight­ed.m­ean(x, w)
 
paste(­vect, sep) /paste0()
 
substr(x, 1, 3)
 
grep(pat, repl, x)
 
tolower() / toupper()
 
nchar(x)
 

Write Functions

function_name <- function(x, y) {
    if (statement) {
        do
    } elif (statement) {
        do
    }
    for (year in 201:2015) {
        do
    }
    return(result)
}

Applying Functions

mutate_each(df, funs(sum))
summarise_each(df, funs(sum))
apply(x, index, fun)
lapply(x, fun) / sapply(x, fun)

Summarise

group_by(df, var) %>%
    summarise(avg = mean(val)) 
    count(var, wt = weight)
table(df$var)
aggregate(x, by, fun)

Join

left_join(df1, df2, by = "var") / right_join(df1, df2, by = "var")
inner_join(df1, df2, by = "var") / full_join(df1, df2, by = "var")
anti_join(df1, df2, by = "var") / semi_join(df1, df2, by = "var")

Method Chaining

df = df %>%
    select(var1, var2) %>%
    mutate(newvar = var1 + var2)

New Variable / Column

df$newvar = df$var1 + df$var2
mutate(df, newvar = var1 + var2)
transmute(df, newvar = var1 + var2) # drop orig cols

Reshape Data

gather(df, 'var', 'val') # columns into rows
spread(df, var, val) # rows into columns
unite(df, col1, col2, sep) # sev cols into 1
bind_rows(df1, df2) / bind_cols(df1, df2) / rbind(...) / cbind(..)
melt() / cast() / recast() / reshape()