Skip to content
Compare Youtube series content with data analysis, statistics, and observations
Branch: master
Clone or download
Latest commit 1f80f1d Jun 7, 2019
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
Images updated mockup Jun 7, 2019
Resources added HTML and files May 3, 2019
.gitignore Initial commit May 2, 2019
README.md
_config.yml added sitemap May 29, 2019
comparision.html updated font and buttons May 29, 2019
config.py added regression graphs May 4, 2019
index.html updated font and buttons May 29, 2019
style.css
taste_comments.html updated font and buttons May 29, 2019
taste_data.html updated font and buttons May 29, 2019
taste_views.html
unsolved_comments.html updated font and buttons May 29, 2019
unsolved_data.html updated font and buttons May 29, 2019
unsolved_views.html
youtube_data_api.ipynb added regression graphs May 4, 2019

README.md

YT Trends

Welcome! The purpose of this project is analyze and compare Youtube content between two BuzzFeed shows, Unsolved and Taste Test.

This is important because we want to know which of these series reaches audiences in a positive way and helps us understand the type of content that is worth investing.

In this project, we examined how video likes changes as view count or comment count increases and presented our data visualizations and observations through a website.

Live webpage

Getting Started

  • Get Youtube API from Google's Developer API and paste in config.py file. Note: For security concerns, my own Google API key has been hidden.

Requirements

Instructions

  • Open the Jupyter Notebook file to see how we requested the Youtube API, used Pandas to clean the data and save to CSV file, and scipy/matplotlib to observe any significant trends.

Resources

Authors

Ying Li

You can’t perform that action at this time.