sjmisc

Add or replace data frame columns

Merge labelled data frames

Add variables or cases to data frames

Check if vector only has NA values

Format numbers

Frequency table of tagged NA values

Compute group-meaned and de-meaned variables

Basic descriptive statistics

Dichotomize variables

Sample dataset from the EUROFAMCARE project

Return or remove variables or observations that are completely missing

Find variable by name or label

Flat (proportional) tables

Frequency table of labelled variables

Value matching

Group near elements of string vectors

Recode numeric variables into equal-ranged groups

Check if variables or cases have missing / infinite values

Check whether two factors are crossed or nested

Check whether string, list or vector is empty

Check whether value is even or odd

Check if a variable is of (non-integer) double type or a whole number

Check whether a factor has numeric levels only

Merges multiple imputed data frames into a single data frame

Move columns to other positions in a data frame

Convert numeric vectors into factors associated value labels

Recode variables

Create recode pattern for 'rec' function

Recode variable categories into new values

Objects exported from other packages

Change reference level of (numeric) factors

Remove variables from a data frame

Replace NA with specific values

Reshape data into long format

Rotate a data frame

Round numeric variables in a data frame

Count row or column indices

Row sums and means for data frames

Sequence generation for column or row counts of data frames

Replace specific values in vector with NA

Shorten character strings

Data and Variable Transformation Functions

Split numeric variables into smaller groups

Spread model coefficients of list-variables into columns

Standardize and center variables

Check if string contains pattern

Find partial matching and close distance elements in strings

Find start and end index of pattern in string

Clean values of character vectors.

Split (categorical) vectors into dummy variables

Convert wide data to long format

Convert factors to numeric variables

Trim leading and trailing whitespaces from strings

Return the typical value of a vector

Rename variables

Determine variable type

Insert line breaks in long labels

Convert infiite or NaN values into regular NA