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This project analyzes household transactions from 2,500 frequent shoppers over two years, including demographics and marketing history. It features a Streamlit dashboard with pages for Data exploration, demographic insights, product data, and sales data. It also has a notebook for data management and processing.

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Medkallel/Dunhumby-The-complete-Journey-Dashboard

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📈 Dunhumby The complete Journey Dashboard

banner

Table of Contents


Technologies Used

Python Pandas NumPyMatplotlib Plotly Jupyter Notebook JSON Streamlit App


Description

This dataset contains household level transactions over two years from a group of 2,500 households who are frequent shoppers at a retailer. For certain households, demographic information as well as direct marketing contact history are included. The objective of this dashboard is to present relevant metrics about the financials of the stores, the demographic distribution of the customers and other key metrics. Multiple updates could be made to study the results of several marketing campaigns and product displays.

  • App Overview

    • A python Notebook for the data management and creation of new metrics/columns
    • The streamlit app has 5 pages:
      • 👋 Dataset Presentation
      • 🔍 Data Exploration
      • 🏠 Demographic Data
      • 📦 Product_Data
      • 🧮 Sales Data
  • App Screenshots

Dataset Presentation
Dataset Presentation
Data Exploration
Data Exploration
Demographic Data
Demographic Data
Product Presence Product Sales
Product Presence Product Presence
General Sales Sales By Demographic Customer Acqiosition
General Sales Sales By Demographic Customer Acquisition

Demo

The app demo is hosted & available on the following link: Demo Link

Streamlit App

Installation

Important

The project was done on Python 3.11.6

To run this project locally, follow these steps:

  1. Clone the repository:
# Clone the repository
git clone https://github.com/Medkallel/Dunhumby-The-complete-Journey-Dashboard
# Navigate into the directory
cd Dunhumby-The-complete-Journey-Dashboard
  1. Install the required dependencies:
# Install the requirements
pip install -r requirements.txt

Usage

# Run the Streamlit app
streamlit run Src/Streamlit/1_👋_Dataset_Presentation.py

Tip

You can access the app on another device by following the link: http://<server-ip>:8501


Project Structure

Here's a visual representation of the structure:
📦Project
 ┣ 📁.streamlit/
 ┃ ┗ 📄config.toml
 ┣ 📁Assets/
 ┃ ┣ 🖼️ banner.jpg
 ┃ ┗ 🖼️ WordCloudMask.png
 ┣ 📁Data/ Contains the dataset csv files
 ┣ 📁Export/ Contains the cleaned dataset files
 ┣ 📁Doc/
 ┃ ┣ 📄dataset_description.json
 ┃ ┗ 📄dunnhumby - The Complete Journey User Guide.pdf
 ┣ 📁Src/
 ┃ ┣ 🐍Data_Exploration-Preprocessing.ipynb
 ┃ ┗ 📁Streamlit/
 ┃   ┣ 🐍1_👋_Dataset_Presentation.py
 ┃   ┣ 🐍config.py
 ┃   ┣ 🐍display_graph.py
 ┃   ┣📁pages/
 ┃    ┣ 🐍2_🔍_Data Exploration.py
 ┃    ┣ 🐍3_🏠_Demographic Data.py
 ┃    ┣ 🐍4_📦_Product_Data.py
 ┃    ┗ 🐍5_🧮_Sales_Data.py
 ┣ 📄README.md
 ┗ 📄requirements.txt

📫 Contact me

LinkedIn


License

This project is under the CC BY-NC 4.0 Licence. Check the licence file for more info.
License: CC BY-NC 4.0

About

This project analyzes household transactions from 2,500 frequent shoppers over two years, including demographics and marketing history. It features a Streamlit dashboard with pages for Data exploration, demographic insights, product data, and sales data. It also has a notebook for data management and processing.

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