Data Analysis with Python

Project Title - Youtube Trending videos analysis

YouTube is the most popular and most used video platfrom in the world today. YouTube has a list of trending videos that is updated constantly. Here in this project, we will use Python with some packages like Pandas and Matplotlib to analyze a dataset that was collected for several days. For each of those days, the dataset contains data about the trending videos of that day. It contains data about more than 40,000 trending videos. We will analyze this data to get insights into YouTube trending videos, to see what is common between these videos. Those insights might also be used by people who want to increase popularity of their videos on YouTube.

The dataset that we will use is obtained from Kaggle. It contains data about trending videos for many countries.

Questions we want to ask to our dataset:

1. How many views do our trending videos have? Do most of them have a large number of views? Is having a large number of views required for a video to become trending?

2. The same questions above, but applied to likes and comment count instead of views.

3. How many trending videos contain a fully-capitalized word in their titles?

4. What are the lengths of trending video titles? Is this length related to the video becoming trendy?

5. How are views, likes correlate with (relate to) each other? How are they connected?