Digital Cultural Consumption in France

EFREI Paris — Data Storytelling Dashboard (Streamlit)
Author: Mathieu Alassoeur
Course: Data Visualization & Storytelling — 2025

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Project Overview

This project explores how socio-demographic characteristics and digital behaviors influence cultural consumption in France.
It is based on an open public dataset provided by data.gouv.fr and is presented through an interactive Streamlit data storytelling dashboard.

The objective is not only to visualize data, but to build a structured narrative that guides the user from raw observations to insights and implications.

Narrative structure used in the dashboard:

Problem → Analysis → Insights → Implications

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Dataset

• Source: data.gouv.fr
• Topic: Digital practices and cultural consumption in France
• Scope: Socio-demographic variables, digital access, online cultural behaviors

The dataset is provided in CSV format and processed using Python data analysis tools.

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Technologies Used

• Python 3
• Pandas, NumPy
• Matplotlib, Seaborn, Plotly
• Streamlit
• Jupyter Notebook

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Project Structure

dataviz-dashboard/
│
├── app.py                 # Main Streamlit application
├── requirements.txt       # Python dependencies
├── data/                  # Dataset files
├── sections/              # Analysis and visualization logic
├── utils/                 # Helper functions
└── README.md

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Quick Start

Follow the steps below to run the dashboard locally.

1. Clone the repository

git clone https://github.com/MatALass/Data-viz-dashboard.git
cd Data-viz-dashboard

2. Create a virtual environment (recommended)

python -m venv venv

Activate it:

macOS / Linux

source venv/bin/activate

Windows (PowerShell)

venv\Scripts\Activate.ps1

3. Install dependencies

pip install -r requirements.txt

4. Check the data

Ensure the dataset files are present in the data/ directory. If you use a different dataset or file name, update the paths accordingly in the code.

5. Run the Streamlit application

streamlit run app.py

The dashboard will be available at:

http://localhost:8501

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Dashboard Content

The Streamlit application includes:

• Exploratory data analysis
• Interactive visualizations
• Socio-demographic comparisons
• Interpretation of digital cultural behaviors
• A storytelling-driven user flow

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Learning Objectives

This project was developed to:

• Apply data visualization best practices
• Build a coherent data storytelling narrative
• Design interactive dashboards with Streamlit
• Translate data insights into societal interpretations