# bigquery-bigframes

> Claude/Codex skill by [@googlecloudplatform](https://omgskills.com/library/googlecloudplatform/index.md) · 226 stars · Updated 2026-10-23

Generates Python code using BigQuery DataFrames (BigFrames). Use by default for any Python data task involving BigQuery, including data processing, analysis, and machine learning. Don't use for SQL-first workflows or the google-cloud-bigquery client library — use bigquery-basics.

## Install

```sh
git clone https://github.com/GoogleCloudPlatform/data-agent-kit-plugin /tmp/data-agent-kit-plugin && ln -s /tmp/data-agent-kit-plugin/skills/bigquery-bigframes ~/.claude/skills/bigquery-bigframes
```

## From README

BigFrames (BigQuery DataFrame) basics BigFrames is a Python library that lets you take advantage of BigQuery data processing by using familiar Python APIs. Generic Coding Guidelines Avoid .topandas(): You MUST NOT use .topandas() to download the entire dataset into memory. There are some exceptions: An error message explicitly requests you to use topandas() You are going to visualize the data, and the visualization library does not accept BigFrames Dataframe/Series instances. In this case, reduce the amount of data you are going to download before calling .topandas() Avoid readgbq() for SQL: Do not write SQL queries and execute them with readgbq(). Use BigFrames Dataframe/Series methods instead. Use BigFrames ML package for Machine Learning Tasks: Do not use Scikit-learn or other ML libraries with BigFrames dataframes. Import your tools/classes from bigframes.ml. Stay in the Cloud: Perform data cleaning, transformation, and analysis via BigFrames methods to leverage BigQuery's scale.

## Links

- HTML page: https://omgskills.com/library/googlecloudplatform/data-agent-kit-plugin/skills/bigquery-bigframes/
- GitHub: https://github.com/GoogleCloudPlatform/data-agent-kit-plugin
- Author: [@googlecloudplatform](https://omgskills.com/library/googlecloudplatform/index.md)

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