Amazon Prime Video Users Data - Exploratory Data Analysis (EDA)

This repository contains data and scripts for performing Exploratory Data Analysis (EDA) on the Amazon Prime Video Users Dataset. The dataset is available for download from Kaggle.

Dataset Overview

The Amazon Prime Users Dataset contains information about 2500 fictional users of the Amazon Prime subscription service. Each entry in the dataset includes details such as the user's name, email address, location, subscription plan, payment information, and engagement metrics. Additionally, demographic data such as gender and date of birth are provided, along with user preferences such as favorite genres and devices used to access the platform.

The dataset aims to represent a diverse range of Prime users, including different demographics, subscription plans, and usage patterns. It is designed to facilitate analysis and insights into user behavior, preferences, and interactions with the Amazon Prime platform. Researchers and analysts can use this dataset to study trends, conduct targeted marketing campaigns, and improve user experience on the platform.

Repository Structure

• amazon_prime_users.csv: The dataset downloaded from Kaggle.
• data_import.ipynb: Jupyter Notebook for importing the dataset, performing data cleaning, and exporting it to CSV and SQL formats.
• dataset_questions.txt: File containing EDA questions to be answered.
• pandas_answers.ipynb: Jupyter Notebook with answers to EDA questions using Pandas.
• sqlJupy_answers.ipynb: Jupyter Notebook with answers to EDA questions using SQL in Jupyter.

Usage

1. Download the dataset from Kaggle.
2. Place the downloaded amazon_prime_users.csv file in the repository root.
3. Open and run the data_import.ipynb notebook to import the dataset, perform data cleaning, and export it to CSV and SQL formats.
4. Use the provided EDA questions in dataset_questions.txt to guide your analysis.
5. Refer to pandas_answers.ipynb and sqlJupy_answers.ipynb for answers to the EDA questions using Pandas and SQL, respectively.

This README is currently available in English, Hindi, Odia, Tamil & Telugu.