A C D E F K L M N P R S T U V W
| adjust | Adjust data for the effect of other variable(s) |
| as.data.frame.datawizard_tables | Create frequency and crosstables of variables |
| assign_labels | Assign variable and value labels |
| assign_labels.data.frame | Assign variable and value labels |
| assign_labels.numeric | Assign variable and value labels |
| categorize | Recode (or "cut" / "bin") data into groups of values. |
| categorize.data.frame | Recode (or "cut" / "bin") data into groups of values. |
| categorize.numeric | Recode (or "cut" / "bin") data into groups of values. |
| center | Centering (Grand-Mean Centering) |
| center.data.frame | Centering (Grand-Mean Centering) |
| center.numeric | Centering (Grand-Mean Centering) |
| centre | Centering (Grand-Mean Centering) |
| change_scale | Rescale Variables to a New Range |
| coef_var | Compute the coefficient of variation |
| coef_var.numeric | Compute the coefficient of variation |
| coerce_to_numeric | Convert to Numeric (if possible) |
| colnames_to_row | Tools for working with column names |
| column_as_rownames | Tools for working with row names or row ids |
| contr.deviation | Deviation Contrast Matrix |
| convert_na_to | Replace missing values in a variable or a data frame. |
| convert_na_to.character | Replace missing values in a variable or a data frame. |
| convert_na_to.data.frame | Replace missing values in a variable or a data frame. |
| convert_na_to.numeric | Replace missing values in a variable or a data frame. |
| convert_to_na | Convert non-missing values in a variable into missing values. |
| convert_to_na.data.frame | Convert non-missing values in a variable into missing values. |
| convert_to_na.factor | Convert non-missing values in a variable into missing values. |
| convert_to_na.numeric | Convert non-missing values in a variable into missing values. |
| data_addprefix | Add a prefix or suffix to column names |
| data_addsuffix | Add a prefix or suffix to column names |
| data_adjust | Adjust data for the effect of other variable(s) |
| 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_extract.data.frame | Extract one or more columns or elements from an object |
| data_filter | Return filtered or sliced data frame, or row indices |
| data_group | Create a grouped data frame |
| data_join | Merge (join) two data frames, or a list of data frames |
| 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_merge.data.frame | Merge (join) two data frames, or a list of data frames |
| data_merge.list | Merge (join) two data frames, or a list of data frames |
| data_modify | Create new variables in a data frame |
| data_modify.data.frame | 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_peek.data.frame | Peek at values and type of variables in a data frame |
| data_read | Read (import) data files from various sources |
| data_relocate | Relocate (reorder) columns of a data frame |
| data_remove | Relocate (reorder) columns of a data frame |
| data_rename | Rename columns and variable names |
| data_rename_rows | Rename columns and variable names |
| data_reorder | Relocate (reorder) columns of a data frame |
| data_replicate | Expand (i.e. replicate rows) a data frame |
| data_restoretype | Restore the type of columns according to a reference data frame |
| data_rotate | Rotate a data frame |
| data_seek | Find variables by their names, variable or value labels |
| data_select | Find or get columns in a data frame based on search patterns |
| data_separate | Separate single variable into multiple variables |
| data_summary | Summarize data |
| data_summary.data.frame | Summarize data |
| data_tabulate | Create frequency and crosstables of variables |
| data_tabulate.data.frame | Create frequency and crosstables of variables |
| data_tabulate.default | 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_transpose | Rotate a data frame |
| data_ungroup | Create a grouped data frame |
| data_unique | Keep only one row from all with duplicated IDs |
| data_unite | Unite ("merge") multiple variables |
| data_write | Read (import) data files from various sources |
| degroup | Compute group-meaned and de-meaned variables |
| demean | Compute group-meaned and de-meaned variables |
| describe_distribution | Describe a distribution |
| describe_distribution.data.frame | Describe a distribution |
| describe_distribution.factor | Describe a distribution |
| describe_distribution.numeric | Describe a distribution |
| detrend | Compute group-meaned and de-meaned variables |
| distribution_coef_var | Compute the coefficient of variation |
| distribution_cv | Compute the coefficient of variation |
| distribution_mode | Compute mode for a statistical distribution |
| efc | Sample dataset from the EFC Survey |
| empty_columns | Return or remove variables or observations that are completely missing |
| empty_rows | Return or remove variables or observations that are completely missing |
| extract_column_names | Find or get columns in a data frame based on search patterns |
| find_columns | Find or get columns in a data frame based on search patterns |
| kurtosis | Compute Skewness and (Excess) Kurtosis |
| kurtosis.numeric | Compute Skewness and (Excess) Kurtosis |
| labels_to_levels | Convert value labels into factor levels |
| labels_to_levels.data.frame | Convert value labels into factor levels |
| labels_to_levels.factor | Convert value labels into factor levels |
| makepredictcall.dw_transformer | Utility Function for Safe Prediction with 'datawizard' transformers |
| means_by_group | Summary of mean values by group |
| means_by_group.data.frame | Summary of mean values by group |
| means_by_group.numeric | Summary of mean values by group |
| mean_sd | Summary Helpers |
| median_mad | Summary Helpers |
| nhanes_sample | Sample dataset from the National Health and Nutrition Examination Survey |
| normalize | Normalize numeric variable to 0-1 range |
| normalize.data.frame | Normalize numeric variable to 0-1 range |
| normalize.numeric | Normalize numeric variable to 0-1 range |
| print.parameters_kurtosis | Compute Skewness and (Excess) Kurtosis |
| print.parameters_skewness | Compute Skewness and (Excess) Kurtosis |
| print_html.data_codebook | Generate a codebook of a data frame. |
| ranktransform | (Signed) rank transformation |
| ranktransform.data.frame | (Signed) rank transformation |
| ranktransform.numeric | (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 |
| recode_values.data.frame | Recode old values of variables into new values |
| recode_values.numeric | Recode old values of variables into new values |
| remove_empty | Return or remove variables or observations that are completely missing |
| remove_empty_columns | Return or remove variables or observations that are completely missing |
| remove_empty_rows | Return or remove variables or observations that are completely missing |
| replace_nan_inf | Convert infinite or 'NaN' values into 'NA' |
| rescale | Rescale Variables to a New Range |
| rescale.data.frame | Rescale Variables to a New Range |
| rescale.numeric | Rescale Variables to a New Range |
| rescale_weights | Rescale design weights for multilevel analysis |
| reshape_ci | Reshape CI between wide/long formats |
| reshape_longer | Reshape (pivot) data from wide to long |
| reshape_wider | Reshape (pivot) data from long to wide |
| reverse | Reverse-Score Variables |
| reverse.data.frame | Reverse-Score Variables |
| reverse.numeric | Reverse-Score Variables |
| reverse_scale | Reverse-Score Variables |
| rowid_as_column | Tools for working with row names or row ids |
| rownames_as_column | Tools for working with row names or row ids |
| row_count | Count specific values row-wise |
| row_means | Row means or sums (optionally with minimum amount of valid values) |
| row_sums | Row means or sums (optionally with minimum amount of valid values) |
| row_to_colnames | Tools for working with column names |
| skewness | Compute Skewness and (Excess) Kurtosis |
| skewness.numeric | Compute Skewness and (Excess) Kurtosis |
| slide | Shift numeric value range |
| slide.data.frame | Shift numeric value range |
| slide.numeric | Shift numeric value range |
| smoothness | Quantify the smoothness of a vector |
| standardise | Standardization (Z-scoring) |
| standardize | Standardization (Z-scoring) |
| standardize.data.frame | Standardization (Z-scoring) |
| standardize.default | Re-fit a model with standardized data |
| standardize.factor | Standardization (Z-scoring) |
| standardize.numeric | Standardization (Z-scoring) |
| standardize_models | Re-fit a model with standardized data |
| summary.parameters_kurtosis | Compute Skewness and (Excess) Kurtosis |
| summary.parameters_skewness | Compute Skewness and (Excess) Kurtosis |
| text_concatenate | Convenient text formatting functionalities |
| text_format | Convenient text formatting functionalities |
| text_fullstop | Convenient text formatting functionalities |
| text_lastchar | Convenient text formatting functionalities |
| text_paste | Convenient text formatting functionalities |
| text_remove | Convenient text formatting functionalities |
| text_wrap | Convenient text formatting functionalities |
| to_factor | Convert data to factors |
| to_factor.data.frame | Convert data to factors |
| to_factor.numeric | Convert data to factors |
| to_numeric | Convert data to numeric |
| to_numeric.data.frame | Convert data to numeric |
| unnormalize | Normalize numeric variable to 0-1 range |
| unnormalize.data.frame | Normalize numeric variable to 0-1 range |
| unnormalize.grouped_df | Normalize numeric variable to 0-1 range |
| unnormalize.numeric | Normalize numeric variable to 0-1 range |
| unstandardise | Standardization (Z-scoring) |
| unstandardize | Standardization (Z-scoring) |
| unstandardize.data.frame | Standardization (Z-scoring) |
| unstandardize.numeric | Standardization (Z-scoring) |
| visualisation_recipe | Prepare objects for visualisation |
| weighted_mad | Weighted Mean, Median, SD, and MAD |
| weighted_mean | Weighted Mean, Median, SD, and MAD |
| weighted_median | Weighted Mean, Median, SD, and MAD |
| weighted_sd | Weighted Mean, Median, SD, and MAD |
| winsorize | Winsorize data |
| winsorize.numeric | Winsorize data |