Building a web app in Python for analyzing YouTube channels
In this video, we're going to build a Streamlit web app in Python for analyzing YouTube channel data. Webscraping was performed using BrightData to obtain data pertaining to YouTube channel information that is exported in JSON format.
🔗 Learn more about BrightData and follow along https://get.brightdata.com/dataprofessor
🐙 Code for webscraping on BrightData https://github.com/dataprofessor/youtube-data-scripts
🐙 Code for app https://github.com/dataprofessor/youtube-data-app
🕹 Demo app https://youtube-data-channels.streamlit.app/
⏰ Timeline:
0:00 Introduction
1:25 Designing the app
3:31 Preview of data app
6:11 BrightData for web scraping
8:49 Exploring the webscraped JSON data
9:36 Walkthrough of the code
12:30 Next steps
13:22 Conclusion
🖼️ Credit:
Enter https://www.flaticon.com/free-icon/enter_1828381
Paste https://www.flaticon.com/free-icon/paste_3388655
Categories https://www.flaticon.com/free-icon/categories_4277485
Json https://www.flaticon.com/free-icon/json_2581811
Coding https://www.flaticon.com/free-icon/code_2920244
Plan https://www.flaticon.com/free-icon/plan_3050533
Data collection https://www.flaticon.com/free-icon/data-collection_7440290
Problem solving https://www.flaticon.com/free-icon/problem-solving_4133585
Data collection https://www.flaticon.com/free-icon/data-collection_9409659
Data https://www.flaticon.com/free-icon/data_1197409
Database https://www.flaticon.com/free-icon/database_5139710
IP https://www.flaticon.com/free-icon/ip_1674968
#datascience #webscraping #brightdata #streamlit #dataprofessor
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Chapters (8)
Introduction
1:25
Designing the app
3:31
Preview of data app
6:11
BrightData for web scraping
8:49
Exploring the webscraped JSON data
9:36
Walkthrough of the code
12:30
Next steps
13:22
Conclusion
🎓
Tutor Explanation
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