https://github.com/flofriday/youtube-data
Jupyter Notebook to analyze your YouTube data.
https://github.com/flofriday/youtube-data
data-science jupyter jupyter-lab personal-data python3 youtube
Last synced: 3 months ago
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Jupyter Notebook to analyze your YouTube data.
- Host: GitHub
- URL: https://github.com/flofriday/youtube-data
- Owner: flofriday
- License: mit
- Created: 2020-06-26T21:22:13.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2020-07-07T20:19:04.000Z (almost 6 years ago)
- Last Synced: 2025-05-05T19:03:40.191Z (about 1 year ago)
- Topics: data-science, jupyter, jupyter-lab, personal-data, python3, youtube
- Language: Python
- Homepage:
- Size: 664 KB
- Stars: 16
- Watchers: 1
- Forks: 1
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# youtube-data
Telegram bot and Jupyter Notebook to analyze your YouTube data.
*[Try the bot](https://t.me/youtube_data_bot)*
## Screenshot
The notebook can do more than just tell you what creators you watch the most, so just try it out.
## Run the bot
### Requirements
1) install docker
### Run it
```
docker build -t youtubebot-template .
docker run -e TELEGRAM_TOKEN='XXXX' --rm --name youtubebot-container youtubebot-template
```
Replace `XXXX` with your telegram token.
Note: This way all data will be lost once you shut down the bot. To prevent
this you can start the bot with a mounted docker volume.
```
docker build -t youtubebot-template .
docker volume create youtubebot-volume
docker run -d --restart unless-stopped \
-e TELEGRAM_TOKEN='XXXX' \
--mount type=volume,source=youtubebot-volume,target=/app/data \
--name youtubebot-container youtubebot-template
```
## Run the jupyter notebook
### Requirements
1) Install jupyter lab [Website](https://jupyter.org/install.html)
2) Add the ipywidgets extension to jupyter lab [Website](https://github.com/jupyter-widgets/ipywidgets#install)
3) Install python libaries used for this notebook `pip install pandas numpy matplotlib ipywidgets`
### Run it
1) Download your youtube data (and select Format=JSON) [Website](https://takeout.google.com/)
2) Copy the folder "Takeout" into the folder with the Notebook. (Note: I just got a notice that this only works if your language is set to english. If that is not the case you need to modify the path in the first code-cell. This bug will be fixed in the next commits.)
3) Run the notebook with `jupyter lab PATH-TO-NOTEBOOK`