INTRODUCTION
It is a simple project that analyzes how one can extract data from youtube by intergrating youtube api keys and channel ids to fetch for video content analysis,subscriber trends,video details and commnets.
FEATURES
Retrieve channel statistics, Get detailed information about YouTube channels, including subscriber count, view count, video count, and other relevant metrics.
Fetch video details,Extract data such as video title, description, duration, view count, like count, dislike count, and publish date for individual videos.
Analyze comments, Retrieve comments made on YouTube videos and perform analysis, such as sentiment analysis or comment sentiment distribution.
Generate reports, Generate reports and visualizations based on the collected data, allowing users to gain insights into channel performance, video engagement, and audience interaction.
Data storage, Store the collected YouTube data in a database for easy retrieval and future reference.
TECHNOLOGIES USED
Python,its a language built with mathematical libraries and different functions.
Youtube Data Api,it aids in generating custom reports containing youtube analytics data.
Matplotlib, A popular data visualization library in Python used for creating charts, graphs, and visual representations of the data retrieved from YouTube. Matplotlib helps in analyzing and presenting the data in a meaningful way.
Pandas,A powerful data manipulation and analysis library in Python. Pandas is used in the YouTube Data Scraper to handle and process data obtained from YouTube, providing functionalities such as data filtering, transformation, and aggregation.
PROCESS FLOW
Obtain youtube Api credentials:
-Visit the Google Cloud Console.
-Create a new project or select an existing project.
-Enable the YouTube Data API v3 for your project.
-Create API credentials for youtube API v3.
CONCLUSION
Through the youtube api scrapper has enabled the efficient way of gauging different sets of data,visualizations,insights,content subscribers,engagements,views and understanding different digital landscapes
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