# Turning GitHub Data into Insights with Plotly Studio

**URL:** <https://community.plotly.com/t/turning-github-data-into-insights-with-plotly-studio/94883>\
**Category:** Plotly Studio\
**Tags:** show-and-tell\
**Created:** [September 26, 2025, 5:18pm UTC](https://community.plotly.com/t/turning-github-data-into-insights-with-plotly-studio/94883 "2025-09-26T17:18:59Z")\
**Posts on this page:** 3\
**Page:** 1

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**Author:** ![SadafN](https://sea2.discourse-cdn.com/flex024/user_avatar/community.plotly.com/sadafn/32/32797_2.png) [@SadafN](https://community.plotly.com/u/SadafN)\
**Post date:** [September 26, 2025, 5:18pm UTC](https://community.plotly.com/t/turning-github-data-into-insights-with-plotly-studio/94883/1 "2025-09-26T17:18:59Z")

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Check out how I used **Plotly Studio** to analyze GitHub issues in our [public dash repository](https://github.com/plotly/dash).

I used the **GitHub CLI** to export a CSV of repository issues with all the relevant details. In just a few clicks, I created interactive charts that reveal:

- 🏷 Who has the most assigned issues

- 📈 Contributor activity trends

- 📊 Backlog growth and resolution patterns

What’s amazing is how **easy** it was to go from raw CSV data to meaningful insights — no complex setup, just install Plotly-Studio, upload CSV or Parquet data and explore.

You can do the same to visualize your team’s workload, productivity, overall project health, and more. View and share this app hosted on Plotly Cloud [https://182ad432-14de-43b1-8b5d-ddfb83ea6aaf.plotly.app](https://182ad432-14de-43b1-8b5d-ddfb83ea6aaf.plotly.app)

 ![image](https://us1.discourse-cdn.com/flex024/uploads/plot/original/3X/c/f/cf0873213cbffee641d127a9343ad41e3f4f70d6.png)

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**Author:** ![adamschroeder](https://sea2.discourse-cdn.com/flex024/user_avatar/community.plotly.com/adamschroeder/32/17280_2.png) [@adamschroeder](https://community.plotly.com/u/adamschroeder)\
**Post date:** [September 26, 2025, 8:05pm UTC](https://community.plotly.com/t/turning-github-data-into-insights-with-plotly-studio/94883/2 "2025-09-26T20:05:46Z")

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That’s a pretty app, @SadafN .  
Did you ask it for a particular graph in the outline section or did you let Plotly Studio do its thing?

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**Author:** ![SadafN](https://sea2.discourse-cdn.com/flex024/user_avatar/community.plotly.com/sadafn/32/32797_2.png) [@SadafN](https://community.plotly.com/u/SadafN)\
**Post date:** [September 29, 2025, 2:16pm UTC](https://community.plotly.com/t/turning-github-data-into-insights-with-plotly-studio/94883/3 "2025-09-29T14:16:46Z")

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I asked to show me which days of the week contributor are most active and which days least.