RenewablesPrediction-

The main objective of this project is to create a dashboard to analyze the data from several sources and develop a common place for these insights. This is a part of a bigger project, so check more about the first part.

Medium Article

Check the part 1 here: Renewable Insights — EDA with Streamlit

Datasets

• Renewable Energy Production by Country (2000 - 2021) IRENA

• Investment in Renewable by Source (1960 - 2022) Our World in Data

• Renewable Energy (1960 - 2023) - main source (https://www.oecd-ilibrary.org/energy/renewable-energy/indicator/english_aac7c3f1-en) Kaggle dataset

• World GDP by Country (1960 - 2022) Kaggle dataset

Code focus objectives

• Import and clear the data from the datasets
• Combine all the different sources into a main dataframe
• Analyze the dataframe and create metrics
• Create a local dashboard (StreamLit)
• Sort the global datasets by countries

Libraries

• Pandas
• StreamLit
• Seaborn
• MathplotLib
• Plotly Express

How to run

1. Clone this project git clone https://github.com/forceliuss/RenewablesPrediction.git
2. Run your python kernel
3. Install all the libraries above pip install -r requirements.txt
4. Run app.py through the streamlit command streamlit run app.py