https://github.com/tom-doerr/x_twitter_analytics
https://github.com/tom-doerr/x_twitter_analytics
Last synced: 5 days ago
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- Host: GitHub
- URL: https://github.com/tom-doerr/x_twitter_analytics
- Owner: tom-doerr
- License: mit
- Created: 2024-08-21T14:33:02.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-08-21T17:34:51.000Z (almost 2 years ago)
- Last Synced: 2025-02-14T09:48:13.292Z (over 1 year ago)
- Language: Python
- Size: 75.2 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Twitter Analytics Visualizer
## Overview
This project is a Streamlit application that visualizes Twitter analytics data. It processes CSV files exported from the Twitter Analytics Account Overview page and provides interactive plots to analyze engagement rates and other metrics.
## Features and Advantages over Twitter Analytics
This tool offers several advantages over the built-in Twitter Analytics plots:
- **Flexible Data Exploration**: Users can select any feature for both X and Y axes, allowing for custom comparisons not available in Twitter Analytics.
- **Engagement Rate Calculation**: Automatically calculates engagement rates, a metric not directly plotted in Twitter Analytics.
- **Interactive Plotting**: Utilizes Plotly for interactive, zoomable, and exportable plots.
- **Custom Metric Combinations**: Explore relationships between any two metrics of your choice.
- **Data Table View**: Displays all imported data in a table format for easy reference.
Additional features include:
- Automatic import of the most recent CSV file from the `csv_files` directory
- Calculation of engagement rates based on likes, replies, reposts, bookmarks, and impressions
- Support for any additional columns present in the Twitter Analytics CSV export
Note: While we calculate engagement rates, our method may differ slightly from Twitter's internal calculations.
## Usage
1. Place your Twitter Analytics CSV file(s) in the `csv_files` directory
2. Run the Streamlit app:
```
streamlit run streamlit_app.py
```
3. Open the provided URL in your web browser
4. Use the interactive plot to explore your Twitter analytics data
## Data Format
The application expects CSV files with the following columns:
- Date
- Likes
- Replies
- Reposts
- Bookmarks
- Impressions
Additional columns may be present and can be used in the interactive plot.
## Contributing
Contributions to improve the application are welcome. Please feel free to submit a Pull Request.
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.