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Get help with the example datasets

Get help with operators and `magrittr` pipes

Get help with Base `R`

Working with data types

Topic	Description
`as.character()`	Coerce (“change”) a value to be character type
`as.factor()`	Coerce (“change”) a value to be factor type
`as.numeric()`	Coerce (“change”) a value to be character type
`class()`	Determine a value’s type

Working with R libraries/packages

Function	Description
`library()`	Load a library/package into an R session
`install.packages()`	Install a library/package for the first time

Working with files and directories

Function	Description
`getwd()`	Ask `R` what your R session’s working directory is
`setwd()`	Change the current R session’s working directory
`dir.exists()`	Ask if a given directory (folder) exists on your computer
`file.exists()`	Ask if a given file exists on your computer
`file.path()`	Construct a path to a given file or directory (folder)

Working with numbers

Function	Description
`log()`	Calculate the natural log (or other specified base) of a number or array of numbers
`sqrt()`	Calculate the square root of a number or array of numbers
`abs()`	Calculate the absolute value of a number or array of numbers
`round()`	Round a number or array of numbers to a specified number of decimal places
`ceiling()`	Round a number or array of numbers up to the next highest integer
`floor()`	Round a number or array of numbers down to the next lowest integer

Working with arrays, strings, and more

Function	Description
`c()`	Create new arrays
`length()`	Determine the length of an array (not of a single string)
`nchar()`	Determine the number of characters in a string
`levels()`	Determine the levels (i.e., ordered categories) of a factor variable
`unique()`	Remove duplicates from an array, i.e. keep only unique values
`paste()` and `paste0()`	Combine several strings into one
`ifelse()`	Assign a value based on whether a statement is `TRUE` or `FALSE`
`cat()` and `print`	Functions you can use to explicitly print
`all()`	Asks, “do ALL values in an array meet a logical condition?”
`any()`	Asks, “do ANY (at least one) values in an array meet a logical condition?”

Working with data frames (and other objects)

Function	Description
`data.frame()`	Create a new data frame from scratch
`nrow()`	Determine the number of rows in a tibble (data frame)
`ncol()`	Determine the number of columns in a tibble (data frame)
`names()`	Determine the column names of a tibble (data frame)
`head()`	See the first 6 rows of a tibble (data frame)
`tail()`	See the last 6 rows of a tibble (data frame)
`summary()`	See a summary of columns in tibble (data frame)
`str()`	See the structure of a tibble (data frame)

Summary statistics

Function	Description
`mean()`	Calculate the average of an array of numbers
`median()`	Calculate the median of an array of numbers
`max()`	Calculate the maximum value of an array of numbers
`min()`	Calculate the minimum value of an array of numbers
`sd()`	Calculate the standard deviation of an array of numbers
`sum()`	Calculate the sum of an array of numbers
`summary()`	Calculate several summary statistics for an array of numbers
`table()`	Count the occurrences of each value in an array of any type

Get help with `ggplot2`

Fundamental `ggplot2`

Function	Description
`aes()`	Provide a ggplot2 with aesthetic mappings from dataset columns
`ggplot()`	Tell ggplot2 which dataset to plot and establish a ggplot2 canvas
`ggsave()`	Save a plot made with ggplot2 to a file

Geoms

Function	Description
`geom_boxplot()`	Create boxplots
`geom_density()`	Create density plots
`geom_histogram()`	Create histograms
`geom_jitter()`	Create jitter (strip) plots
`geom_point()`	Create point shapes, often (but not always) to create scatterplots
`geom_smooth()`	Add a trendline to a plot, often (but not always) to a scatterplot
`geom_col()`	Create bar plots whose height corresponds to literal values in the data
`geom_bar()`	Create bar plots whose height corresponds to counted number of observations of a categorical variable
`geom_text()` and `geom_label()`	Create labels in plots
`geom_segment()`	Add line segments to plots

Axes, labels, and faceting

Function or tutorial	Description
Axes tutorial	Customizing x- and y- axes
`xlim()`	Change x-axis limits
`ylim()`	Change y-axis limits
`labs()`	Customize plot labels, including axes, titles, and legends
`facet_wrap()`	Create a faceted (paneled) plot across 1 variable
`facet_grid()`	Create a faceted (paneled) grid of plots across 2 variables

Color and fill scales

Function or tutorial	Description
Color and fill scales tutorial	Customizing color and fill scales
`scale_color_manual()`	Specify custom color scale mappings for discrete data
`scale_fill_manual()`	Specify custom fill scale mappings for discrete data
`scale_color_gradient()`	Specify custom color gradient scale mappings for continuous data
`scale_fill_gradient()`	Specify custom fill gradient scale mappings for continuous data
`scale_color_gradient2()`	Specify custom two-way color gradient scale mappings for continuous data
`scale_fill_gradient2()`	Specify custom two-way fill gradient scale mappings for continuous data
`scale_color_brewer()`	Specify `colorbrewer` color scale mappings for discrete data
`scale_fill_brewer()`	Specify `colorbrewer` fill scale mappings for discrete data
`scale_color_distiller()`	Specify `colorbrewer` color scale mappings for continuous data
`scale_fill_distiller()`	Specify `colorbrewer` fill scale mappings for continuous data
`scale_color_viridis_d()`	Specify `viridis` color scale mappings for discrete data
`scale_fill_viridis_d()`	Specify `viridis` fill scale mappings for discrete data
`scale_color_viridis_c()`	Specify `viridis` color scale mappings for continuous data
`scale_fill_viridis_c()`	Specify `viridis` fill scale mappings for continuous data

Other scales

Link	Description
`scale_shape_manual()`	Specify custom shape mappings
`scale_size_manual()`	Specify custom size mappings
`scale_alpha_manual()`	Specify custom alpha (transparency) mappings
`scale_linetype_manual()`	Specify custom linetype mappings

Themes

Function	Description
`theme()` and associated tutoral	Customizing themes
`theme_set()`	Set the default theme
`theme_gray()`	Specify the built-in “gray” (default) theme
`theme_grey()`	Specify the built-in “grey” (default) theme
`theme_bw()`	Specify the built-in “bw” theme
`theme_linedraw()`	Specify the built-in “linedraw” theme
`theme_light()`	Specify the built-in “light” theme
`theme_dark()`	Specify the built-in “dark” theme
`theme_minimal()`	Specify the built-in “minimal” theme
`theme_classic()`	Specify the “classic” theme
`theme_void()`	Specify the built-in “void” theme

Get help with `dplyr`

One-table verbs

Function	Description
`arrange()`	Arrange tibble (data frame) rows
`distinct()`	Remove duplicate rows from a tibble (data frame)
`mutate()`	Create new or modify existing columns in a tibble (data frame)
`filter()`	Keep only certain rows from a tibble (data frame) based on `TRUE` or `FALSE`
`select()`	Keep, remove, or reorder columns in a tibble (data frame)
`rename()`	Rename existing columns in a tibble (data frame)
`glimpse()`	See an overview of tibble (data frame) contents
`pull()`	Extract out a column from a tibble (data frame) into its own array
`slice()`	Keep only certain rows from a tibble (data frame) based on index
`group_by()`	Establish a grouping in a tibble (data frame)
`ungroup()`	Undo any groupings in a tibble (data frame)
`summarize()`	Summarize values in a tibble (data frame) to produce a smaller summarized tibble
`tally()`	Count the number of rows in each grouping of a tibble (data frame)
`count()`	Simultaneously group and count the number of rows in each grouping of a tibble (data frame)

Two-table verbs

Function	Description
`bind_cols()`	Combine arrays or tibbles (data frames) by columns
`bind_rows()`	Combine arrays or tibbles (data frames) by rows
`left_join()`	Merge two relational tibbles (data frames) based on the left side
`right_join()`	Merge two relational tibbles (data frames) based on the right side
`full_join()`	Merge two relational tibbles (data frames) fully
`inner_join()`	Merge two relational tibbles (data frames) based on what they have in common
`anti_join()`	Merge relational tibbles (data frames) based on what they do not have in common

Helper functions

Function	Description
`if_else()`	Assign a value based on whether a statement is `TRUE` or `FALSE` , ensuring same type
`case_when()`	Assign a value based on a series of conditions are `TRUE` or `FALSE`
`n()`	Returns the number of rows in a tibble group

Get help with `tidyselect` helpers

Function	Description
`everything()`	Select all columns, except those already explicitly stated
`contains()`	Select all columns that contain a given string argument
`starts_with()`	Select all columns that start with a given string, i.e. prefix
`ends_with()`	Select all columns that end with a given string, i.e. suffix
`last_col()`	Select the last column
`matches()`	Select all columns that match a regular expression (a special type of pattern-matching string)

Get help with `forcats`

Function	Description
`fct_relevel()`	Reorder levels in a factor to a custom order
`fct_infreq()`	Reorder levels factor in a factor based on frequency
`fct_rev()`	Reverse the order of levels in a factor
`fct_reorder()`	Reorder levels in a factor based on values of another variable
`fct_lump_n()`	Combine infrequently occurring levels of a factor into one
`fct_lump_min()`	Combine infrequently occurring levels of a factor into one
`fct_lump_prop()`	Combine infrequently occurring levels of a factor into one

Get help with `readr`

Function	Description
`read_csv()`	Read a CSV file into `R`
`read_tsv()`	Read a TSV file into `R`
`read_csv2()`	Read a CSV2 file into `R`
`read_delim()`	Read a delimited file of any kind into `R`
`write_csv()`	Write (save) a tibble (data frame) to a CSV file
`write_tsv()`	Write (save) a tibble (data frame) to a TSV file
`write_csv2()`	Write (save) a tibble (data frame) to a CSV2 file
`write_delim()`	Write (save) a tibble (data frame) to a delimited file

Get help with `tibble`

Function	Description
`as_tibble()`	Coerce a variable (often a data frame) into a tibble
`tibble()`	Create a new tibble from scratch
`tribble()`	Create a new tibble from scratch

Get help with `tidyr`

Function	Description
`pivot_longer()`	Make a tibble (data frame) longer
`pivot_wider()`	Make a tibble (data frame) wider
`drop_na()`	Remove rows containing `NA` values from a tibble (data frame)
`unite()`	Unite (combine) two columns in a tibble (data frame) into a single column
`separate()`	Separate a single column in a tibble (data frame) into two new columns

Get help with `stringr`

Function	Description
`str_count()`	Count the number of occurrences of a substring or regular expression in a string
`str_replace()`	Replace the first occurrence of a substring or regular expression in a string with a given replacement string
`str_replace_all()`	Replace all occurrences of a substring or regular expression in a string with a given replacement string
`str_detect()`	Determine whether it is `TRUE` or `FALSE` that a given string contains a substring
`str_starts()`	Determine whether it is `TRUE` or `FALSE` that a given string starts with a given substring
`str_ends()`	Determine whether it is `TRUE` or `FALSE` that a given string ends with a given substring

Get help with `glue`

Function	Description
`glue()`	Quickly combine strings and variables into a single string