| adjust | Adjust data for the effect of other variable(s) |
| assign_labels | Assign variable and value labels |
| categorize | Recode (or "cut" / "bin") data into groups of values. |
| center | Centering (Grand-Mean Centering) |
| coef_var | Compute the coefficient of variation |
| coerce_to_numeric | Convert to Numeric (if possible) |
| colnames | Tools for working with column names |
| contr.deviation | Deviation Contrast Matrix |
| convert_na_to | Replace missing values in a variable or a data frame. |
| convert_to_na | Convert non-missing values in a variable into missing values. |
| data_arrange | Arrange rows by column values |
| data_codebook | Generate a codebook of a data frame. |
| data_duplicated | Extract all duplicates |
| data_extract | Extract one or more columns or elements from an object |
| data_group | Create a grouped data frame |
| data_match | Return filtered or sliced data frame, or row indices |
| data_merge | Merge (join) two data frames, or a list of data frames |
| data_modify | Create new variables in a data frame |
| data_partition | Partition data |
| data_peek | Peek at values and type of variables in a data frame |
| data_prefix_suffix | Add a prefix or suffix to column names |
| data_read | Read (import) data files from various sources |
| data_relocate | Relocate (reorder) columns of a data frame |
| data_rename | Rename columns and variable names |
| data_replicate | Expand (i.e. replicate rows) a data frame |
| data_restoretype | Restore the type of columns according to a reference data... |
| data_rotate | Rotate a data frame |
| data_seek | Find variables by their names, variable or value labels |
| data_separate | Separate single variable into multiple variables |
| data_summary | Summarize data |
| data_tabulate | Create frequency and crosstables of variables |
| data_to_long | Reshape (pivot) data from wide to long |
| data_to_wide | Reshape (pivot) data from long to wide |
| data_unique | Keep only one row from all with duplicated IDs |
| data_unite | Unite ("merge") multiple variables |
| datawizard-package | datawizard: Easy Data Wrangling and Statistical... |
| demean | Compute group-meaned and de-meaned variables |
| describe_distribution | Describe a distribution |
| distribution_mode | Compute mode for a statistical distribution |
| dot-is_deprecated | Print a message saying that an argument is deprecated and... |
| efc | Sample dataset from the EFC Survey |
| extract_column_names | Find or get columns in a data frame based on search patterns |
| labels_to_levels | Convert value labels into factor levels |
| makepredictcall.dw_transformer | Utility Function for Safe Prediction with 'datawizard'... |
| means_by_group | Summary of mean values by group |
| mean_sd | Summary Helpers |
| nhanes_sample | Sample dataset from the National Health and Nutrition... |
| normalize | Normalize numeric variable to 0-1 range |
| ranktransform | (Signed) rank transformation |
| recode_into | Recode values from one or more variables into a new variable |
| recode_values | Recode old values of variables into new values |
| reexports | Objects exported from other packages |
| remove_empty | Return or remove variables or observations that are... |
| replace_nan_inf | Convert infinite or 'NaN' values into 'NA' |
| rescale | Rescale Variables to a New Range |
| rescale_weights | Rescale design weights for multilevel analysis |
| reshape_ci | Reshape CI between wide/long formats |
| reverse | Reverse-Score Variables |
| row_count | Count specific values row-wise |
| row_means | Row means or sums (optionally with minimum amount of valid... |
| rownames | Tools for working with row names or row ids |
| skewness | Compute Skewness and (Excess) Kurtosis |
| slide | Shift numeric value range |
| smoothness | Quantify the smoothness of a vector |
| standardize | Standardization (Z-scoring) |
| standardize.default | Re-fit a model with standardized data |
| text_format | Convenient text formatting functionalities |
| to_factor | Convert data to factors |
| to_numeric | Convert data to numeric |
| visualisation_recipe | Prepare objects for visualisation |
| weighted_mean | Weighted Mean, Median, SD, and MAD |
| winsorize | Winsorize data |
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