🌎 CO2 emissions & GDP

In this Streamlit app we examine the CO2 emissions of countries over the years and compare a country's emissions with their GDP. Which countries emit the most CO2, do they have a higher GDP? We use a linear regression model to predict emissions for future years based on the GDP and Population of countries.

Dependencies

Dependencies to install for this project:

• Python 3.11
• streamlit 1.27.0
• pandas 2.1.1
• numpy 1.26.0
• matplotlib 3.8.0
• seaborn 0.12.2
• python-dotenv 1.0.0
• plotly 5.17.0
• geopandas 0.14
• folium 0.14.0
• streamlit_folium 0.15.0
• statsmodels 0.14.0

Getting Started

Installation

1. Clone the repository to your local machine:
2. Navigate to the project directory:
3. Create a virtual environment (recommended):

python -m venv venv

4. Activate the virtual environment:

• On Windows:

venv\Scripts\activate

• On macOS and Linux:

source venv/bin/activate

5. Install project dependencies from requirements.txt:

pip install -r requirements.txt

6. Explain how to use your project once it's set up. Provide examples and usage instructions.

streamlit run app.py

Column Explanations

Here is a breakdown of the columns in the dataset:

• "Country": Name of Country
• "Code": ISO alpha-3 calling code of every country
• "Year": Year of CO2 emission / GDP
• "GDP": GDP of every country
• "Calling Code": Calling code of every country
• "CO2 emission (Tons)": Amount of CO2 emission in Tons
• "Area": Area of that country in km2
• "% of World": How much % of World landmass, this country covered
• "Density(km2)": Density according to Area in km2