This project explores a dataset of Netflix titles to uncover patterns in content type, genre, release year, country distribution, and more.

Netflix is one of the largest streaming platforms globally. This dataset contains information about TV shows and movies available on Netflix, including details like title, director, cast, country, release year, and genre.

The goal of this project is to analyze the dataset to answer questions such as:

What’s the breakdown of Movies vs TV Shows?

Which countries produce the most Netflix content?

What are the most common genres?

Who are the most frequently featured actors?

How has content output changed over time?

Pandas for data manipulation

Matplotlib for visualizations

Google Colab for running the notebook

Movies make up the majority of content on Netflix.

The United States is the top content-producing country.

The most common genres are Documentaries, Dramas, and Comedies.

Certain actors appear frequently across titles.

Netflix content output increased significantly after 2015.

Source: [Kaggle Netflix Titles Dataset](https://www.kaggle.com/datasets/shivamb/netflix-shows)

Rows: ~8800+

Columns: 12

This project helped reinforce my skills in:

Data cleaning (handling missing values)

Exploratory data analysis (EDA)

Generating insights using charts

Using Google Colab effectively

Grouping by director or production company

Time-series analysis of yearly trends

Genre popularity by country