E-commerce Data Analysis Dashboard 📊

This repository contains a data analysis dashboard built using Streamlit that analyzes e-commerce data. The dashboard provides interactive visualizations and insights from the dataset.

📁 Project Structure

SUBMISSION/
├── .vscode/
├── dashboard/
│   ├── dashboard.py
│   ├── rfm_df.csv
│   ├── segment_analysis.csv
│   └── segment_distribution.csv
├── data/
│   └── E-commerce-public-dataset.zip
├── Proyek_Analisis_Data.ipynb
├── README.md
└── requirements.txt

🛠️ Setup Instructions

You can set up this project using either Anaconda or a regular Python environment with pip. Choose the method that best suits your needs.

Option 1: Using Anaconda

1. Create a new conda environment:

conda create --name main-ds python=3.9

2. Activate the conda environment:

conda activate main-ds

3. Install the required packages:

pip install -r requirements.txt

Option 2: Using Regular Python Environment

1. Create a new project directory:

mkdir proyek_analisis_data
cd proyek_analisis_data

2. Set up a virtual environment using pipenv:

pipenv install
pipenv shell

3. Install the required packages:

pip install -r requirements.txt

📊 Dataset

The project uses an E-commerce public dataset (E-commerce-public-dataset.zip) which is processed using the Jupyter notebook (Proyek_Analisis_Data.ipynb) to generate the following analysis files:

• rfm_df.csv: RFM (Recency, Frequency, Monetary) analysis data
• segment_analysis.csv: Customer segment analysis data
• segment_distribution.csv: Distribution of customer segments

🚀 Running the Dashboard

After setting up your environment, navigate to the dashboard directory and run:

cd dashboard
streamlit run dashboard.py

The dashboard will open in your default web browser.

📦 Dependencies

The main dependencies for this project are listed in requirements.txt. Make sure to install them before running the dashboard.

📧 Contact

If you have any questions or suggestions, please open an issue in this repository.