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🌎 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
  1. Activate the virtual environment:
  • On Windows:
venv\Scripts\activate
  • On macOS and Linux:
source venv/bin/activate
  1. Install project dependencies from requirements.txt:
pip install -r requirements.txt
  1. 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