Man pages for datawizard
Easy Data Wrangling and Statistical Transformations

adjustAdjust data for the effect of other variable(s)
assign_labelsAssign variable and value labels
categorizeRecode (or "cut" / "bin") data into groups of values.
centerCentering (Grand-Mean Centering)
coef_varCompute the coefficient of variation
coerce_to_numericConvert to Numeric (if possible)
colnamesTools for working with column names
contr.deviationDeviation Contrast Matrix
convert_na_toReplace missing values in a variable or a data frame.
convert_to_naConvert non-missing values in a variable into missing values.
data_arrangeArrange rows by column values
data_codebookGenerate a codebook of a data frame.
data_duplicatedExtract all duplicates
data_extractExtract one or more columns or elements from an object
data_groupCreate a grouped data frame
data_matchReturn filtered or sliced data frame, or row indices
data_mergeMerge (join) two data frames, or a list of data frames
data_modifyCreate new variables in a data frame
data_partitionPartition data
data_peekPeek at values and type of variables in a data frame
data_readRead (import) data files from various sources
data_relocateRelocate (reorder) columns of a data frame
data_renameRename columns and variable names
data_restoretypeRestore the type of columns according to a reference data...
data_rotateRotate a data frame
data_seekFind variables by their names, variable or value labels
data_separateSeparate single variable into multiple variables
data_tabulateCreate frequency tables of variables
data_to_longReshape (pivot) data from wide to long
data_to_wideReshape (pivot) data from long to wide
data_uniqueKeep only one row from all with duplicated IDs
data_uniteUnite ("merge") multiple variables
datawizard-packagedatawizard: Easy Data Wrangling and Statistical...
demeanCompute group-meaned and de-meaned variables
describe_distributionDescribe a distribution
distribution_modeCompute mode for a statistical distribution
dot-is_deprecatedPrint a message saying that an argument is deprecated and...
efcSample dataset from the EFC Survey
find_columnsFind or get columns in a data frame based on search patterns
labels_to_levelsConvert value labels into factor levels
makepredictcall.dw_transformerUtility Function for Safe Prediction with 'datawizard'...
means_by_groupSummary of mean values by group
mean_sdSummary Helpers
nhanes_sampleSample dataset from the National Health and Nutrition...
normalizeNormalize numeric variable to 0-1 range
ranktransform(Signed) rank transformation
recode_intoRecode values from one or more variables into a new variable
recode_valuesRecode old values of variables into new values
reexportsObjects exported from other packages
remove_emptyReturn or remove variables or observations that are...
replace_nan_infConvert infinite or 'NaN' values into 'NA'
rescaleRescale Variables to a New Range
rescale_weightsRescale design weights for multilevel analysis
reshape_ciReshape CI between wide/long formats
reverseReverse-Score Variables
row_meansRow means (optionally with minimum amount of valid values)
rownamesTools for working with row names or row ids
skewnessCompute Skewness and (Excess) Kurtosis
slideShift numeric value range
smoothnessQuantify the smoothness of a vector
standardizeStandardization (Z-scoring)
standardize.defaultRe-fit a model with standardized data
text_formatConvenient text formatting functionalities
to_factorConvert data to factors
to_numericConvert data to numeric
visualisation_recipePrepare objects for visualisation
weighted_meanWeighted Mean, Median, SD, and MAD
winsorizeWinsorize data
datawizard documentation built on Sept. 15, 2023, 9:06 a.m.