# Create a markdown table from raw data

This is useful if you want to quickly format a great deal of raw data into a more useful markdown table.

**Prompt**

````txt
You are an expert in data formatting. For the following csv data, output it as a markdown table.
Output the table only. 

```
name,age,occupation
Jane Smith,25,Data Scientist
Bob Johnson,42,Software Developer
Emily Davis,37,Product Manager
```
````

**Output**

```
| Name | Age | Occupation |
| --- | --- | --- |
| Jane Smith | 25 | Data Scientist |
| Bob Johnson | 42 | Software Developer |
| Emily Davis | 37 | Product Manager |
```

**API Request**

````python PYTHON
import cohere

co = cohere.ClientV2(api_key="<YOUR API KEY>")

response = co.chat(
    model="command-a-plus-05-2026",
    messages=[
        {
            "role": "user",
            "content": """
    You are an expert in data formatting. For the following csv data, output it as a markdown table.
    Output the table only. 

    ```
    name,age,occupation
    Jane Smith,25,Data Scientist
    Bob Johnson,42,Software Developer
    Emily Davis,37,Product Manager
    ```
    """,
        }
    ],
)

print(response.message.content[0].text)
````

## Related pages

- [Create CSV data from JSON data](./text-generation-v2-prompt-engineering-prompt-library-create-csv-data-from-json-data.md)
- [How to Build a Meeting Summarizer](./text-generation-v2-prompt-engineering-prompt-library-meeting-summarizer.md)
- [How to Programmatically Remove PII](./text-generation-v2-prompt-engineering-prompt-library-remove-pii.md)
- [How to Add a Docstring to Your Code](./text-generation-v2-prompt-engineering-prompt-library-add-a-docstring-to-your-code.md)
- [How to Evaluate your LLM Response](./text-generation-v2-prompt-engineering-prompt-library-evaluate-your-llm-response.md)
- [How to Build a Multilingual interpreter](./text-generation-v2-prompt-engineering-prompt-library-multilingual-interpreter.md)

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