Title
Rapid API
Introduction
The YouTube Trending Videos Analysis project focuses on retrieving data on trending videos from the YouTube platform using the YouTube Search and Download API. The project aims to preprocess the fetched data by flattening nested JSON structures and converting the JSON data into a pandas DataFrame. This preprocessing step facilitates easy analysis and exploration of the trending videos dataset.
Processing Steps
1. Data Retrieval:
- Utilize the YouTube Search and Download API to fetch data on trending videos.
- Access relevant parameters such as video title, channel ID, view count, likes, dislikes, and comments.
- Utilize the YouTube Search and Download API to fetch data on trending videos.
- Access relevant parameters such as video title, channel ID, view count, likes, dislikes, and comments.
2. Data Preprocessing:
- Flatten nested JSON structures to simplify the data hierarchy.
- Convert the JSON data into a pandas DataFrame.
- Flatten nested JSON structures to simplify the data hierarchy.
- Convert the JSON data into a pandas DataFrame.
Conclusion
The initial stages of the project involve retrieving data on trending videos from YouTube using the designated API. Subsequently, the fetched data undergoes preprocessing, including flattening nested JSON structures and conversion into a pandas DataFrame. These steps lay the groundwork for further analysis and exploration of the trending videos dataset, enabling the extraction of valuable insights and trends from the YouTube platform.
The initial stages of the project involve retrieving data on trending videos from YouTube using the designated API. Subsequently, the fetched data undergoes preprocessing, including flattening nested JSON structures and conversion into a pandas DataFrame. These steps lay the groundwork for further analysis and exploration of the trending videos dataset, enabling the extraction of valuable insights and trends from the YouTube platform.
Source
GitHub: Rapid API
