adjust                  Adjust data for the effect of other variable(s)
center                  Centering (Grand-Mean Centering)
compact_character       Remove empty strings from character
compact_list            Remove empty elements from lists
convert_data_to_numeric
                        Convert data to numeric
data_addprefix          Convenient dataframe manipulation
                        functionalities
data_extract            Extract a single column or element from an
                        object
data_match              Find row indices of a data frame matching a
                        specific condition
data_partition          Partition data into a test and a training set
data_relocate           Relocate (reorder) columns of a data frame
data_rescale            Rescale Variables to a New Range
data_restoretype        Restore the type of columns according to a
                        reference data frame
data_to_long            Reshape (pivot) data from wide to long
data_transpose          Transpose a dataframe
demean                  Compute group-meaned and de-meaned variables
describe_distribution   Describe a distribution
format_text             Convenient text formatting functionalities
is_empty_object         Check if object is empty
nhanes_sample           Sample dataset from the National Health and
                        Nutrition Examination Survey
normalize               Normalize numeric variable to 0-1 range
ranktransform           (Signed) rank transformation
rescale_weights         Rescale design weights for multilevel analysis
reshape_ci              Reshape CI between wide/long formats
skewness                Compute Skewness and (Excess) Kurtosis
smoothness              Quantify the smoothness of a vector
standardize             Standardization (Z-scoring)
to_numeric              Convert to Numeric (if possible)
visualisation_recipe    Prepare objects for visualisation
winsorize               Winsorize data
