{purrr}
safely return result or default when there is an error
{ggplot2}
save a ggplot
{stats}
compute standard deviation
{tibble}
create tibble
{purrr}
apply multiple functions over two arguments in parallel, only for side effects
{dplyr}
apply function to columns and return TRUE if any values are TRUE
{readr}
parse a character vector to numbers
{purrr}
apply a function to multiple elements of an object to obtain side effects
{stats}
compute sample median
{stringr}
format and interpolate a string with glue
{lubridate}
extract day number of month
{base}
assess whether conditional is true for any elements of a vector
{ggplot2}
create histogram of counts as bars
{dplyr}
apply transformation across multiple columns
{base}
sum elements of vector
{base}
return (and can assign) column names
{tidyselect}
select all variables
{dplyr}
apply function to columns and return TRUE if all values are TRUE
{base}
determine if input is of type numeric
{base}
create repetitions of numbers, characters, etc.
{dplyr}
keep rows based on values of columns
{tidyr}
pivot data frame to be longer
{base}
randomly sample from vector
{dplyr}
count unique values of variables
{base}
determine whether elements of vector are missing
{dplyr}
create or modify data columns
{magrittr}
set names of object
{lubridate}
parse dates with year, month, and day components
{stats}
generate random number from uniform distribution
{dplyr}
combine vectors by returning the first non-missing value at each position
{base}
create vector of numbers, characters, etc.
{ggplot2}
create a plotting area
{base}
create recursive vector (list)
{lubridate}
get days component of date-time
{base}
calculate mean of elements of vector
{dplyr}
summarize data usually by grouping variable
{stats}
generate random sample from normal distribution
{tidyr}
pivot data frame to be wider
{DBI}
create connection to database
{ggplot2}
create aesthetic mappings between data and plot
{readxl}
import either xls or xlsx Excel files
{purrr}
apply a function to multiple elements of an object in purrr, return a integer vector
{dplyr}
create a database table from data source
{base}
load R packages
{purrr}
apply a function to multiple elements of an object in purrr, return a list
{base}
divide range of vector into intervals
{lubridate}
return or set month component of a date-time
{dplyr}
return current group size
{dplyr}
keep specified columns
{base}
return number of elements in a vector
{dplyr}
group data by levels of column
{lubridate}
return or set year component of a date-time
{purrr}
apply a function to multiple elements of an object in purrr, return a character vector
{readr}
write data frame to comma delimited file
{utils}
load specific data set
The end!