dataPreparation (version 0.4.3)

prepareSet: Preparation pipeline

Description

Full pipeline for preparing your dataSet set.

Usage

prepareSet(dataSet, finalForm = "data.table", verbose = TRUE, ...)

Arguments

dataSet

Matrix, data.frame or data.table

finalForm

"data.table" or "numerical_matrix" (default to data.table)

verbose

Should the algorithm talk? (logical, default to TRUE)

...

Additional parameters to tune pipeline (see details)

Value

A data.table or a numerical matrix (according to finalForm). It will perform the following steps:

• Correct set: unfactor factor with many values, id dates and numeric that are hiden in character

• Transform set: compute differences between every date, transform dates into factors, generate features from character..., if key is provided, will perform aggregate according to this key

• Filter set: filter constant, in double or bijection variables. If `digits` is provided, will round numeric

• Handle NA: will perform fastHandleNa)

• Shape set: will put the result in asked shape (finalForm) with acceptable columns format.

Details

Additional arguments are available to tune pipeline:

• key Name of a column of dataSet according to which dataSet should be aggregated (character)

• analysisDate A date at which the dataSet should be aggregated (differences between every date and analysisDate will be computed) (Date)

• n_unfactor Number of max value in a facotr, set it to -1 to disable unFactor function. (numeric, default to 53)

• digits The number of digits after comma (optional, numeric, if set will perform fastRound)

• dateFormats List of format of Dates in dataSet (list of characters)

• name_separator character to separate parts of new column names (character, default to ".")

• functions Aggregation functions for numeric columns, see aggregateByKey (list of functions names (character))

• factor_date_type Aggregation level to factorize date (see generateFactorFromDate) (character, default to "yearmonth")

• target_col A target column to perform target encoding, see target_encode (character)

• target_encoding_functions Functions to perform target encoding, see build_target_encoding, if target_col is not given will not do anything, (list, default to "mean")

Examples

# NOT RUN {
# Load ugly set
# }
# NOT RUN {
data(messy_adult)

# Have a look to set
head(messy_adult)

# Compute full pipeline
clean_adult <- prepareSet(messy_adult)

# With a reference date
adult_agg <- prepareSet(messy_adult, analysisDate = as.Date("2017-01-01"))

# Add aggregation by country
adult_agg <- prepareSet(messy_adult, analysisDate = as.Date("2017-01-01"), key = "country")

# With some new aggregation functions
power <- function(x){sum(x^2)}
adult_agg <- prepareSet(messy_adult, analysisDate = as.Date("2017-01-01"), key = "country", 
                        functions = c("min", "max", "mean", "power"))
# }
# NOT RUN {
# "##NOT RUN:" mean that this example hasn't been run on CRAN since its long. But you can run it!
# }