Automated Data Preparation
Automatic data_set aggregation by key
Faster date transformation
Compute bins
Date Factor
Compute encoding
Compute scales
Build target encoding
Compute probability ratio
Compute weight of evidence
Show the NEWS file
Unify dates format
Describe data set
Discretization
Filtering useless variables
Handle NA values
Fast checks of equality
Fast round
scale
Identify date columns
Identify numeric columns in a data_set set
Date difference
Generate factor from dates
Recode character
Recode factor
Get most frequent element
Identify date columns
One hot encoder
Preparation pipeline
Percentile outlier filtering
Filter rare categories
Standard deviation outlier filtering
Give same shape
Numeric matrix preparation for Machine Learning.
Set columns as character
Set columns as POSIXct
Set columns as factor
Set columns as numeric
Final preparation before ML algorithm
Target encode
Unfactor factor with too many values
Identify bijections
Identify constant columns
Identify double columns
Identify columns that are included in others
Do most of the painful data preparation for a data science project with a minimum amount of code; Take advantages of 'data.table' efficiency and use some algorithmic trick in order to perform data preparation in a time and RAM efficient way.