Essential Statistics with R: Cheat Sheet - GitHub
Essential Statistics with R: Cheat Sheet
Important libraries to load
If you don¡¯t have a particular package installed already: install.packages(Tmisc).
library(readr)
library(dplyr)
library(ggplot2)
library(broom)
library(Tmisc)
#
#
#
#
#
for optimized read with read_csv() instead of read.csv()
for filter(), mutate(), %>%, etc. see dplyr lesson.
for making plots in this lesson
OPTIONAL: for model tidying with tidy(), augment(), glance()
OPTIONAL: for gg_na() and propmiss()
The pipe: %>%
When you load the dplyr library you can use %>%, the pipe. Running x %>% f(args) is the same as f(x, args). If you wanted to
run function f() on data x, then run function g() on that, then run function h() on that result: instead of nesting multiple functions,
h(g(f(x))), it¡¯s preferable and more readable to create a chain or pipeline of functions: x %>% f %>% g %>% h. Pipelines can be
spread across multiple lines, with each line ending in %>% until the pipeline terminates. The keyboard shortcut for inserting %>% is
Cmd+Shift+M on Mac, Ctrl+Shift+M on Windows.
Functions
Function
Description
read_csv("path/nhanes.csv")
View(df)
head(df) ; tail(df)
mean, median, range
is.na(x)
filter(df, ..,)
t.test(y~grp, data=df)
wilcox.test(y~grp, data=df)
lmfit ................
................
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