Transform
Generate analytics-ready features from data
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Generate analytics-ready features from data
Last updated
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Feature engineering prepares raw data for analysis by creating new, insightful features:
Applies a log function to positive values, commonly used to handle skewed data.
Converts a date to its day of the week as a number (1-7).
Categorises a date as a weekday (1) or weekend (2).
Categorises ages into specified age ranges for easier analysis.
Each method produces targeted features, simplifying data for analytics.
Log transformation is a data transformation method in which it replaces each variable x with a log(x) where x is a positive number and greater than zero
source field
The column to perform the calculation upon
Double
Provide the day of week from the passed date object to a number between 1 and 7, where start of week is Monday = 1.
Supported date objects:
java.time.LocalDate
java.sql.Date
org.joda.time.DateTime
source field
The column to perform the calculation upon
Double
Categorise a day into one of two categories following the Gregorian calendar.
Weekday (Mon-Fri) = 1
Weekends (Sat-Sun) = 2
source field
The column to perform the calculation upon
Double
Categorise a passed age in a pre-configured age bin as either an integer or date object.
bins
Array of age bins to use. Default bins are set to 0-9, 10-19,...110-119
Int[][]
as date
Passed event field is a supported date object
Supported Data classes:
java.time.LocalDate
java.sql.Date
Boolean
Default: false
base date
Provide a date which is used to calculate the age. Default set to the date process is started
String
Format: YYYY-MM-DD
source field
The column to perform the calculation upon
Double