R: Automated Data Preparation

# Automated Data Preparation

## Documentation for package ‘dataPreparation’ version 1.1.2

- DESCRIPTION file
- Package NEWS

## Help Pages

adult | Adult for UCI repository
aggregate_by_key | Automatic data_set aggregation by key
as.POSIXct_fast | Faster date transformation
build_bins | Compute bins
build_date_factor | Date Factor
build_encoding | Compute encoding
build_scales | Compute scales
build_target_encoding | Build target encoding
compute_probability_ratio | Compute probability ratio
compute_weight_of_evidence | Compute weight of evidence
data_preparation_news | Show the NEWS file
date_format_unifier | Unify dates format
description | Describe data set
fast_discretization | Discretization
fast_filter_variables | Filtering useless variables
fast_handle_na | Handle NA values
fast_is_equal | Fast checks of equality
fast_round | Fast round
fast_scale | scale
find_and_transform_dates | Identify date columns
find_and_transform_numerics | Identify numeric columns in a data_set set
generate_date_diffs | Date difference
generate_factor_from_date | Generate factor from dates
generate_from_character | Recode character
generate_from_factor | Recode factor
get_most_frequent_element | Get most frequent element
identify_dates | Identify date columns
messy_adult | Adult with some ugly columns added
one_hot_encoder | One hot encoder
prepare_set | Preparation pipeline
remove_percentile_outlier | Percentile outlier filtering
remove_rare_categorical | Filter rare categories
remove_sd_outlier | Standard deviation outlier filtering
same_shape | Give same shape
set_as_numeric_matrix | Numeric matrix preparation for Machine Learning.
set_col_as_character | Set columns as character
set_col_as_date | Set columns as POSIXct
set_col_as_factor | Set columns as factor
set_col_as_numeric | Set columns as numeric
shape_set | Final preparation before ML algorithm
target_encode | Target encode
tiny_messy_adult | First 500 rows of 'messy_adult'
un_factor | Unfactor factor with too many values
which_are_bijection | Identify bijections
which_are_constant | Identify constant columns
which_are_included | Identify columns that are included in others
which_are_in_double | Identify double columns