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ZhaoyiW/YouTube-Trending-Video-Analysis

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YouTube Trending Video Analysis License: MIT

Installation

Modules

pip install these modules

  • pandas: data processing
  • numpy: linear algebra
  • seaborn: data visualization
  • matplotlib: data visualization
  • re: regular expression
  • datetime: manipulate date time types of data
  • os: create folders
  • PTL: image processing
  • wordcloud: word cloud creating

Data Source

Trending YouTube Video Statistics from Kaggle
Focus on the US dataset

Project Motivation

Through analyzing the YouTube trending videos data, I was aiming to answer these questions:

  1. What types of videos are more likely to be trending?
  2. Do descriptions or tags matter?
  3. How long does it take for a video to go viral?

File Description

Datasets

  • USvideos.csv
    Information about trending videos on YouTube dated from 2017-11-14 to 2018-06-14.
    Shape: (40949, 16)
  • US_category_id.json
    Category names

DataWrangling_Visualization.ipynb

  • Data wrangling
  • Explorary data analysis
  • Data visualization

img

Includes all images used for word cloud, and output visualizations

Results

My blog on Medium:
Data-Driven Tips to Make aVideo Go Viral on YouTube

License

This project is under MIT License.

Author

Zhaoyi Wang

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