Project to analyse the youtube's video data by fetching data through the youtube's APIs, then storing it into SQLite database and performing data analysis using queries and other techniques.
- Create Virtual Environment
virtualenv envs
- Activate Virtual environment
source envs/bin/activate
- **Pip the requirements.txt **
pip install -r requirements.txt
- python == 3.8
- antiorm==1.2.1
- certifi==2021.5.30
- charset-normalizer==2.0.5
- connection==2021.7.20
- db==0.1.1
- db-sqlite3==0.0.1
- idna==3.2
- numpy==1.21.2
- pandas==1.3.3
- python-dateutil==2.8.2
- pytz==2021.1
- requests==2.26.0
- six==1.16.0
- urllib3==1.26.6
- Create Database connection 👍
connection.py
- Create Tables
- Videos
- Tags
- Videos_vs_Tags
create_tables.py
- Fetch Data
- Use API
- Keyword (python)
- Clean up Data
- Store data in DB
fetch_data.py
- Tag Vs number videos
- Tag with most videos, least videos etc
- Tag vs Avg duration of videos
- Tag with most video time, least video time etc
- Tag Classification
- Classify tags as Tutorials, demos, live coding etc
- And calculate above data for each category
analyzer.py
-
Output:
- As Excel file sheets
Excel_files/
-
Some more Queries
- tags vs no.of comments
- tags vs no.of view count
- tags vs no.of likes count