Skip to content

This YouTube data project aims to extract valuable insights by delving into audience preferences in diverse areas such as gaming, educational trends, and political sentiment. Harnessing the vast YouTube data pool, it uncovers nuanced patterns and trends for a deeper understanding of these specific domains.

Notifications You must be signed in to change notification settings

Prashanth292003/YOUTUBE-DATA-HARVESTING-AND-WAREHOUSEING-PROJECT

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

15 Commits
 
 
 
 
 
 

Repository files navigation

YOUTUBE-DATA-HARVESTING-AND-WAREHOUSEING-PROJECT

YOUTUBE DATA HARVESTING AND WAREHOUSEING PROJECT USING PYTHON, MYSQL,MONGODB,API AND STREAMLIT. YouTube data harvesting involves the unauthorized collection of user information from the platform, raising privacy concerns. This practice often includes extracting personal details and preferences without explicit user consent, posing risks of misuse for targeted advertising or other purposes. Users should be cautious and aware of privacy implications when engaging with YouTube and similar online platforms.

Python scripting: You will gain proficiency in Python programming by developing scripts to interact with the YouTube API, fetch data, and process it for storage and analysis.

API integration: You will understand how to integrate with the YouTube API, authenticate requests, and retrieve data using API endpoints.

Data collection: You will learn how to retrieve data from the YouTube API, including video details, comments, likes, views, and other relevant information.

MongoDB: You will gain hands-on experience with MongoDB, a NoSQL database, and learn how to store and manage YouTube data efficiently using MongoDB's document-oriented approach.

Data management using MongoDB Atlas & Compass: You will learn how to set up and manage a MongoDB Compass and MongoDB Atlas cluster for cloud-based storage and access to your YouTube data.

SQL: You will gain knowledge of SQL (Structured Query Language) and learn how to use it alongside MongoDB for advanced data analysis and querying.

Streamlit: You will learn how to create interactive web applications using Streamlit, a Python library for building data-driven apps. You will design and develop a user-friendly interface to visualize and explore the YouTube data.

About

This YouTube data project aims to extract valuable insights by delving into audience preferences in diverse areas such as gaming, educational trends, and political sentiment. Harnessing the vast YouTube data pool, it uncovers nuanced patterns and trends for a deeper understanding of these specific domains.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages