Big-Data Analysis with Python
Welcome to my project on Analyzing Netflix Data using Python! This repository contains a Jupyter Notebook that demonstrates an analysis of Netflix movie and TV show data using Python programming language. The analysis includes exploratory data analysis (EDA), data visualization, and insights derived from the dataset.
- Introduction
- Dataset
- Installation and Usage
- Analysis Performed
- Results and Visualizations
- Contributions
With the rise of streaming platforms, Netflix has become a prominent player in the entertainment industry. This project aims to provide insights into the Netflix content library, trends, and user preferences through data analysis and visualization.
The dataset used for this analysis is the Netflix Movies and TV Shows dataset from Kaggle. It contains information about various movies and TV shows available on Netflix, including attributes like title, type (movie/TV show), director, cast, country, release year, rating, and more.
To run the analysis locally, follow these steps:
-
Clone this GitHub repository:
git clone https://github.com/Merrill007/Analyzing-Netflix-Data-using-Python.git
In this notebook, the following analyses are performed:
- Exploratory Data Analysis (EDA) to understand the structure of the dataset.
- Visualizations showcasing the distribution of content types (movies/TV shows), countries, and release years.
- Identification of top directors, actors, and genres on Netflix.
- Distribution and trends of content ratings.
- Duration analysis of movies and TV shows.
The results of the analysis, along with corresponding visualizations, are present in the notebook itself. Each section of the notebook contains insights and graphical representations derived from the dataset.
Contributions to this project are welcomed! If you have ideas for additional analyses, improvements to the code, or any other enhancements, feel free to open issues or submit pull requests.