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POWER PLANTS DATA ANALYSIS

This project seeks to analyze data from power plants around the world. The dataset that was chosen [1] (https://www.kaggle.com/datasets/ramjasmaurya/global-powerplants/code) provides us the information of all power plants from every country, their geographical location, their installed capacity, the energy source of each power plant and other more information. Later in this project we are going to provide some information and basic concepts related to power plants.

With this dataset we will answer some question like:
How the energy matrix of each country is composed?
What is the biggest energy source in the world?
what are the countries with the cleanest energy matrix in the world?

And many other questions that can be answered but we will discuss it later. Basically, what we are going to do is to transform all this data in valuable information to answer some questions like the ones we saw above.

For this project we use the Python pandas, numpy libraries to clean the data, to sort, filter and group the information. We also ulse plotly expres for geospatial visualizations and matplotlib for normal visualizations. Finally we use the analytical skills and python language skills that we learn from the jovian course [2] Data Analysis with Python: Zero to Pandas.

Downloading the Dataset

Let´s begin the project by downloading and importing the data. The data that I chose is from https://www.kaggle.com/datasets/ which is a reliable source.

!pip install jovian opendatasets --upgrade --quiet

Let's begin by downloading the data, and listing the files within the dataset.

# This is the dataset I choose for the project. I took it from kaggle.com
dataset_url = 'https://www.kaggle.com/datasets/ramjasmaurya/global-powerplants'