https://github.com/NishuMehta/Netflix-Trends-Data-Analysis
Analyzing Netflix content data to uncover trends in content type, ratings, genres, and time of release using Python, Tableau, and Excel.
https://github.com/NishuMehta/Netflix-Trends-Data-Analysis
excel jupyter-notebook matplotlib-pyplot python python3 tableau
Last synced: about 1 month ago
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Analyzing Netflix content data to uncover trends in content type, ratings, genres, and time of release using Python, Tableau, and Excel.
- Host: GitHub
- URL: https://github.com/NishuMehta/Netflix-Trends-Data-Analysis
- Owner: NishuMehta
- Created: 2025-01-19T19:08:21.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-06-28T10:17:03.000Z (5 months ago)
- Last Synced: 2025-07-20T15:40:00.539Z (4 months ago)
- Topics: excel, jupyter-notebook, matplotlib-pyplot, python, python3, tableau
- Language: Jupyter Notebook
- Homepage: https://public.tableau.com/views/NetflixContentAnalysisDashboard_17428087464750/Dashboard1?:language=en-US&:sid=&:redirect=auth&:display_count=n&:origin=viz_share_link
- Size: 2.43 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Netflix Trends Data Analysis
This project analyzes Netflix content data to uncover trends in content type, ratings, genres, and time of release using **Python**, **Tableau**, and **Excel**.
---
## Dataset Overview
- Source: Netflix Titles Dataset (Kaggle)
- Rows: 8,790+ records
- Fields: Title, Type, Genre, Date Added, Country, Rating, Duration
---
## Tools & Technologies
| Tool | Usage |
|------------|-----------------------------------|
| Python | Data cleaning, EDA (`.ipynb` file)|
| Pandas, Matplotlib | EDA and visual analysis |
| Excel | Data checks and formatting |
| Tableau | Interactive dashboard creation |
---
## Dashboard Insights
### Key Highlights:
- **Content Growth**: Massive spike in content added between 2016–2019
- **Popular Genres**: Dramas, Documentaries, Comedy dominate top categories
- **Type Split**: 69.7% Movies vs 30.3% TV Shows
- **Top Ratings**: Most content rated TV-MA, TV-14
- **Peak Year**: 2019 had the highest number of new additions
---
## File Structure
Netflix-Data-Analysis/
│
├── dashboard/
│ ├── Dashboard.twb # Tableau workbook
│ └── Dashboard.png # Dashboard image
│
├── data/
│ ├── netflix_data.csv # Raw data
│ └── netflix_data.xlsx # Cleaned or used in Tableau
│
├── notebooks/
│ └── netflix_data_analysis.ipynb # EDA notebook
│
└── README.md
---
## What I Learned
- Conducting deep EDA on media/entertainment datasets
- Identifying content trends using date-time analysis
- Visual storytelling using Tableau
- Structuring professional GitHub repos
---
*This project is part of my Data Analyst Portfolio.*