log
{base}
log (default base = e)
tibble
{tibble}
A modern data frame from the tidyverse
order
{base}
Get indexes that will sort a vector
group_tt
{tinytable}
Grouping in tinytable
library
{base}
Load an R package
list
{base}
Create a list object
is.na
{base}
Check if a value is NA/elements of vector are NA
pnorm
{base}
Returns the cumulative distribution function (CDF) of the normal distribution
par
{graphics}
Set parameters of the plotting device
ggsave
{ggplot2}
Saves the last ggplot or a specified ggplot object to a file
ifelse
{base}
Return a or b depending on the value of test
setwd
{base}
Set Working Directory
var
{stats}
Calculate variance
filter
{dplyr}
Filter out rows of a data frame according to logical vector
sd
{stats}
Get standard deviation of a vector
mutate
{dplyr}
Modify/create a column in a data frame
dnorm
{stats}
Density distribution for the normal distribution
mean
{base}
Get mean of a vector
rnorm
{base}
Generate random numbers from a normal distribution
seq
{base}
Create a sequence
str
{utils}
Get the structure of an R object
bar
{base}
Used for annotations, such as “expression(paste(”-“,bar(y)))”
names
{base}
Retrieve names of a list/vector
plot
{graphics}
Generic function from base R to produce a plot
as.data.frame
{base}
Functions to check if an object is a data frame, or coerce it if possible.
read_excel
{readxl}
Read an Excel file
binomial
{base}
Family argument in glm()
min
{base}
Get minimum of a vector
c
{base}
Combine values/vectors into a vector
nrow
{base}
Get number of rows of a data frame
head
{utils}
Show first 5 rows of a data frame
subset
{base}
Return subsets of vectors, matrices or data frames which meet conditions.
arrange
{dplyr}
Sort values of data frame according to a variable/combination of varaibles
cut
{base}
Convert Numeric to Factor
length
{base}
Returns number of elements in an object
expression
{base}
Used in plots to add symbols to axes
data.frame
{base}
Create a data.frame from vectors
range
{base}
Return range of values
read.csv
{utils}
Read a csv file to data frame. Specify stringsAsFactors = FALSE to keep all string columns as characters
lm
{base}
Fit a linear model
as.character
{base}
Coerce a vector to character
sample
{base}
Takes a sample of the specified size
group_by
{dplyr}
Group tibble/data.frame by a factor variable. All further tidyverse operations are performed group-wise
summary
{base}
Obtain summary statistics or detailed regression output
median
{stats}
Get median of a vector
which
{base}
return indexes of TRUE entries of a logical vector
modelsummary
{modelsummary}
Creates regression and data tables
glm
{base}
Fits generalized linear models
ordered
{dplyr}
Create an ordered factor
ungroup
{dplyr}
Resolve grouping created with “group_by”
predict
{stats}
Predict Probability
max
{base}
Get maximum of a vector
nobs
{gdata}
Compute the number of non-missing observations
The end!