Youtube Data Analysis

Using a public dataset powered by the YouTube API, this project uncovers insights into trending videos for one of the largest search engines and one of the largest social media platforms.

Youtube Data Analysis

Project Details

Technologies Used

YouTube API, Jupyter Notebook, Python, Pandas, Matplotlib

Project Features

- Used a public kaggle dataset. This dataset is powered by the YouTube API. It includes various information about trending videos in the US from 2017 - 2018 and includes video information for several other countries as well.
- Project primarily looks at the US but does compare the US vs OUS for a couple of the visualizations/research questions.
- The data includes a lot of useful information about each video, such as publish time, number of views, number of likes, and the tags associated with each video.

Project Overview

YouTube is one of the largest search engines and one of the largest social media platforms. It is used by people all over the US and around the world. People use YouTube for a variety of reasons, such as watching music videos, learning how to do something new, watching sports highlights, or just watching random videos for entertainment. Because of the popularity of YouTube, we decided to dig a little deeper into some of the characteristics that videos (in particular, trending videos) share. After gathering the information, we used that data to uncover some observations into what makes up a trending video and some insights for how a YouTube creator can improve their viewer engagement (likes, comments, dislikes, etc).