Vizualizing Climate Change

Description

This project was developped for a class project on using Streamlit with Docker. It leverages plotly to vizualize climate change on two aspects:

• Global temperature anomalies vs 1950-1980 averages at a latitude x longitude granularity
• Evolution of temperatures in 5 cities, as well as the projections until 2100 is we follow the ongoing trends

The app hosted on Streamlit Community Hub can be found here.

It was built based on the GISTEMP data on historical temperature anomalies.

Global map:

City temperatures:

Installation

Prerequisites

• Python 3.7 or higher or:
• Docker

Usage

Option 1: Run Streamlit app locally

1. Clone the repository:

   git clone https://github.com/matthieudelsart/climate-change-app.git

2. Navigate to the project directory:

   cd climate-change-app

3. Run the Streamlit root page:

   streamlit run Welcome.py

Option 2: Run with Docker

1. Build the Docker image:

   docker pull mdelsart/climate-change-app

2. Run the Docker container:

   docker run -p 8501:8501 mdelsart/climate-change-app

3. Open your browser and go to http://localhost:8501 to see the app.

If need be, the docker image can be found there https://hub.docker.com/repository/docker/mdelsart/climate-change-app