Netflix Data Analysis

This project is a comprehensive data analysis of the Netflix dataset, providing insights into various aspects of the content library. The analysis covers key metrics and trends, including content distribution by category and country, an examination of movie durations, and a look at content release years.

Features

Data Cleaning and Preprocessing: Handles missing values and standardizes data formats for consistent analysis.

Content Distribution: Visualizes the number of movies and TV shows in the dataset.

Geographical Analysis: Identifies the top countries producing Netflix content.

Temporal Trends: Explores the number of titles added to Netflix over the years.

Content Type Insights: Analyzes movie durations and their distribution.

Rating Analysis: Examines the distribution of content ratings.

Files

Netflix Data Analysis.ipynb: The main Jupyter Notebook containing all the Python code, visualizations, and analysis.

Netflix Dataset.csv: The raw dataset used for this analysis.

Requirements

The following Python libraries are required to run the notebook:

pandas

seaborn

matplotlib

How to Run

Make sure you have all the required libraries installed. You can install them using pip:

pip install pandas seaborn matplotlib

Place the Netflix Dataset.csv file in the same directory as the Netflix Data Analysis.ipynb notebook.

Open the notebook in a Jupyter environment (JupyterLab, Jupyter Notebook, or VS Code with the Jupyter extension).

Run all the cells in the notebook to reproduce the analysis.

Author: Santanu Kumar Mohapatra