> ## 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.

# CSV Reader component

> Load a CSV file into your ClickML Studio pipeline as a DataFrame, with options for delimiters, headers, and column type inference.

The **CSV Reader** is the entry point for tabular data stored in `.csv` format. It produces a DataFrame that all downstream components can consume.

## Configuration

| Option        | Description                                                      | Default |
| ------------- | ---------------------------------------------------------------- | ------- |
| **Source**    | `Upload` to load a local file, `URL` to fetch from a web address | Upload  |
| **File**      | The CSV file to upload                                           | —       |
| **URL**       | A direct link to a publicly accessible CSV file                  | —       |
| **Delimiter** | Column separator character (`,` `;` `\t` etc.)                   | `,`     |
| **Header**    | Whether the first row contains column names                      | Yes     |
| **Encoding**  | File encoding                                                    | `utf-8` |

## Input / Output

|        | Type      |
| ------ | --------- |
| Input  | None      |
| Output | DataFrame |

## Notes

* The file is stored securely in your project's storage. You do not need to re-upload it on subsequent runs.
* If your columns are not named correctly after loading, check the **Delimiter** and **Header** settings.
* For large files, prefer URL-based loading to avoid upload timeouts.