https://github.com/ferdos-coder/instacartmarketbasketanalysisportflio

a repository for statistical and visual analyses utilizing tools like Pandas, NumPy, SQL, and Power BI using InstaCart Market Basket Data
https://github.com/ferdos-coder/instacartmarketbasketanalysisportflio

jupyter-notebook machine-learning numpy pandas python statistics

Last synced: 3 months ago
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a repository for statistical and visual analyses utilizing tools like Pandas, NumPy, SQL, and Power BI using InstaCart Market Basket Data

• Host: GitHub
• URL: https://github.com/ferdos-coder/instacartmarketbasketanalysisportflio
• Owner: ferdos-coder
• Created: 2025-03-20T21:06:36.000Z (over 1 year ago)
• Default Branch: master
• Last Pushed: 2025-03-28T08:46:10.000Z (over 1 year ago)
• Last Synced: 2025-03-28T09:36:41.805Z (over 1 year ago)
• Topics: jupyter-notebook, machine-learning, numpy, pandas, python, statistics
• Language: Jupyter Notebook
• Homepage:
• Size: 116 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: ReadMe.md

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README

          
# Instacart Market Basket Analysis Portfolio

This repository contains a comprehensive portfolio of statistical and visual analyses performed on the Instacart Market Basket dataset. The project leverages multiple data analysis and visualization tools including Pandas, NumPy, SQL, and Power BI to extract insights and present meaningful findings from the data.

---

## Table of Contents

- [Project Overview](#project-overview)  

- [Dataset](#dataset)  

- [Tools and Technologies](#tools-and-technologies)  

- [Contents](#contents)   

---

## Project Overview

Market basket analysis is a popular data mining technique used to understand customer purchasing behavior by analyzing the combinations of products frequently bought together. This project explores the Instacart dataset, which contains detailed information about customer orders, products, and purchasing patterns.

The goal is to uncover patterns, trends, and associations in the data through statistical analysis, SQL queries, and interactive visualizations, enabling better business decisions and marketing strategies.

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## Dataset

The dataset used in this project is the **Instacart Market Basket Dataset**, which includes:

- Customer orders and order sequences  

- Product details and categories  

- Department and aisle information  

- User purchase history  

This rich dataset allows for in-depth analysis of shopping behaviors and product affinities.

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## Tools and Technologies

- **Python**: Pandas and NumPy for data manipulation and statistical analysis  

- **SQL**: For querying and aggregating data efficiently  

- **Power BI**: For creating interactive dashboards and visualizations  

- **Jupyter Notebooks**: For combining code, analysis, and visual output in a single document  

---

## Contents

- Data cleaning and preprocessing scripts  

- Exploratory data analysis notebooks  

- SQL scripts for advanced querying  

- Power BI reports and dashboards for visualization  

- Documentation and summaries of key findings