Exploratory data analysis of the included Netflix titles CSV using Python, pandas, NumPy, and Matplotlib. The scripts and notebook create charts covering content type, release trends, countries, maturity ratings, and duration.
Project status: Completed analysis project. No live demo is provided in the repository.
- Clean missing values in fields such as
directorandcast. - Parse
date_addedas a date and prepare columns for analysis. - Compare movies and TV shows.
- Explore release-year patterns, countries, maturity ratings, and movie duration.
- Export static charts for review in this README/repository.
Additional charts are available as movie_duration_histogram.png and release_year_scatter.png.
netflix_titles.csv is included and is described by the original project as the Netflix titles dataset sourced from Kaggle. The repository does not include the original Kaggle URL or a formal citation, so users should verify the publisher and terms before redistributing the data.
Prerequisites: Python 3.x and Jupyter Notebook (or another notebook-compatible environment).
git clone https://github.com/jahidstm/Netflix-Data-Visualization-Python-Project.git
cd Netflix-Data-Visualization-Python-Project
python -m venv .venv
# Windows
.venv\Scripts\activate
# macOS/Linux: source .venv/bin/activate
pip install pandas numpy matplotlib jupyter
jupyter notebook netflix_project.ipynbThe standalone netflix_data_visualization.py script provides a script-based entry point. Run it from the repository root after installing the same Python libraries.
The visualizations show that movies outnumber TV shows in the included snapshot and allow inspection of content additions, countries, ratings, and duration. The dataset is a historical snapshot, the analysis is descriptive rather than causal, and no independent validation or current Netflix catalog claim is made.
No LICENSE file is present, so license status is not specified.