> ## Documentation Index
> Fetch the complete documentation index at: https://docs.clickml.app/llms.txt
> Use this file to discover all available pages before exploring further.

# Data Cleaning component

> Quickly handle missing values in your dataset by dropping rows and columns or filling gaps with mean, median, mode, or constant strategies.

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 |

<Note>
  If no features are selected or Strategy is left at "Select", the component passes the DataFrame through unchanged.
</Note>