Data Cleaning component - ClickML Studio

The Data Cleaning component gives you quick strategies to deal with missing values across selected features.

Configuration

Option	Description
Features	Columns to apply the strategy to. Select individual columns, `All Numerical Features`, or `All Categorical Features`.
Strategy	How to handle missing values (see table below).

Strategies

Strategy	What it does
Drop Rows	Remove rows that have a missing value in any selected column
Drop Columns	Remove the selected columns entirely
Fill with Mean	Replace missing values with the column mean (numerical only)
Fill with Median	Replace missing values with the column median (numerical only)
Fill with Mode	Replace missing values with the most frequent value
Fill with ffill, bfill	Forward-fill then backward-fill missing values

Input / Output

	Type
Input	DataFrame
Output	DataFrame

If no features are selected or Strategy is left at “Select”, the component passes the DataFrame through unchanged.