https://github.com/arpit-k16/-netflix-data-visualization-with-matplotlib
Netflix data visualization project using Matplotlib and Pandas.
https://github.com/arpit-k16/-netflix-data-visualization-with-matplotlib
data-visualization explora exploratory-data-analysis matplotlib-pyplot netflix pandas
Last synced: about 2 months ago
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Netflix data visualization project using Matplotlib and Pandas.
- Host: GitHub
- URL: https://github.com/arpit-k16/-netflix-data-visualization-with-matplotlib
- Owner: arpit-k16
- Created: 2025-06-19T14:38:00.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-06-19T14:47:55.000Z (about 1 year ago)
- Last Synced: 2025-06-19T15:37:44.770Z (about 1 year ago)
- Topics: data-visualization, explora, exploratory-data-analysis, matplotlib-pyplot, netflix, pandas
- Language: Jupyter Notebook
- Homepage:
- Size: 0 Bytes
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# 📊 Netflix Data Visualization Capstone Project
This project is a capstone built while learning Matplotlib, inspired by [this tutorial video](https://youtu.be/kM_eVEEWfnE?feature=shared). It explores Netflix’s catalog using data visualization techniques with Python.
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## 🗂 Dataset
**Netflix Movies and TV Shows Dataset** from Kaggle:
📎 [https://www.kaggle.com/datasets/shivamb/netflix-shows](https://www.kaggle.com/datasets/shivamb/netflix-shows)
---
## 🎯 Project Goals
- Understand the distribution of content types (Movies vs TV Shows)
- Analyze release trends by year and month
- Explore countries contributing most content
- Visualize most popular genres and durations
- Highlight missing metadata (directors, cast, etc.)
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## 🔧 Tools & Technologies
- **Python**
- **Jupyter Notebook**
- **Pandas** – data wrangling
- **Matplotlib (pyplot)** – static plotting
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## 📊 Key Visual Insights
- **Movies dominate** over TV Shows in total titles available
- Most content is produced in the **United States**, with India and the UK also contributing significantly
- **Content additions peaked** in 2019–2020, indicating rapid platform growth
- **Genres like Documentaries, Dramas, and Comedies** are most frequent
- Many entries lack complete metadata, which could impact recommendation systems
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## 📁 Repository Structure
📦 Netflix-Matplotlib-Capstone
┣ 📄 netflix_titles.csv # Dataset
┣ 📄 Netflix_Analysis.ipynb # Jupyter Notebook with all code & plots
┣ 📄 README.md # This file
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## ✅ Outcomes
- Strengthened my Matplotlib fundamentals
- Learned how to extract insights from real-world data
- Gained experience in visual storytelling for analytics
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## 🚀 Future Improvements
- Add Seaborn/Plotly for improved visual aesthetics
- Make an interactive dashboard (Streamlit or Dash)
- Add genre clustering or NLP on descriptions
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## 📬 Contact
If you have suggestions, feedback, or want to collaborate, feel free to connect via [LinkedIn](https://www.linkedin.com/in/arpit-kumar-261888315/).
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> ⭐ If you found this useful, consider starring the repo or sharing it!