Efficient YouTube data harvesting and warehousing with Python, SQL, MongoDB, and Streamlit, enabling seamless analysis and visualization for insightful decision-making in content management and audience engagement strategies

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A project for analysing blockchain transactions and tracing fund movements using Tronscan APIs. Verifies recipient addresses, checks transaction accuracy, and maps fund flows to detect discrepancies, ensuring transparency and integrity in cryptocurrency transactions.

ETRADE API Python

YouTube Data Harvesting and Warehousing using SQL, MongoDB and Streamlit

The "YouTube Data Analyzer" is a versatile tool for businesses and content creators, enabling them to gather, analyze, and harness valuable insights from multiple YouTube channels. With streamlined data collection, storage in MongoDB, migration to SQL, and a user-friendly Streamlit interface, it empowers users to make data-driven decisions

The YouTube Data Harvesting and Warehousing project is a robust solution for extracting, storing, and analyzing data from YouTube channels. Leveraging the Google API, this project enables users to seamlessly collect, secure, and migrate data within a user-friendly Streamlit application.

This repository contains a Python web application that allows users to search for YouTube videos based on a given topic and retrieves relevant video data such as video title, channel name, view count, likes, duration. The data is then saved to a CSV file for further analysis and can be downloaded by the user.