Sample dataset from the EUROFAMCARE project
Return or remove variables or observations that are completely missing
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 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
Convert numeric vectors into factors associated value labels
Create recode pattern for 'rec' function
Recode variable categories into new values
Change reference level of (numeric) factors
Replace specific values in vector with NA
Data and Variable Transformation Functions
Split numeric variables into smaller groups
Spread model coefficients of list-variables into columns
Find partial matching and close distance elements in strings
Find start and end index of pattern in string
Convert variable into character vector and replace values with associated value labels
Split (categorical) vectors into dummy variables
Convert variable into factor and keep value labels
Convert variable into factor with associated value labels
Trim leading and trailing whitespaces from strings
Convert infiite or NaN values into regular NA