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Have you always wanted to make visuals of pokemon data? I found a csv file that has stats on most of the pokemon and I used python, seaborn and matplotlib to make some cool visualizations. This work was sampled from a cool tutorial on seaborn's great visualizations(https://elitedatascience.com/python-seaborn-tutorial#step-1). This covers a good summary of Seaborn’s strengths. In practice, the “well-defined set of hard things” includes: Using default themes that are aesthetically pleasing, making attractive statistical plots, visualizing information from matrices and data frames. I have included the work in a jupyter notebook file and the csv file that has the pokemon data used for this side project.

License: GNU General Public License v3.0

Jupyter Notebook 100.00%
pokemon-data seaborn data-frames data-visualization matplotlib csv python pandas

data-visualization-of-pokemon-data-with-python-and-seaborn_side_project's Introduction

Data Visualization of Pokemon Data with Python and Seaborn (side project)

Introduction

This repository displays the creative use of data visualization of Pokemon data. This project made the process of data visualization fun for me. This project was based on the Pokemon Go mobile game that raised interest on the subject of Pokemon's fighting data.

Abstract

Have you always wanted to make visuals of pokemon data? I found a csv file that has stats on most of the pokemon. This work was sampled from a cool tutorial on seaborn's great visualizations (https://elitedatascience.com/python-seaborn-tutorial#step-1). This covers a good summary of Seaborn’s strengths. In practice, the “well-defined set of hard things” includes: Using default themes that are aesthetically pleasing, making attractive statistical plots, visualizing information from matrices and data frames. I have included the work in a jupyter notebook file and the csv file that has the pokemon data used for this side project.

Summary of Skills

I used the python environment to create data visualizations from Pokemon's fighting data. I used the seaborn and matplotlib packages to bring these visualization to life.

Preview

This preview is a colorful Violin Plot of Pokemon types.

Preview of Pokemon chart 02

This preview is a heatmap of Pokemon attack styles.

You can try this code from this project in the repository.

Findings

From this project I used default themes that are aesthetically pleasing. Then I set a custom color palette and making attractive plots. I was foud this to easy and flexible in displaying distributions. Creating visualized information from matrices and DataFrames.

Challenges

The challenge was creating visualizations that made it easy to understand the strengths of the different types of pokemons. In the code of this project, it will displays all the visualizations used. The fact it was easy to create visualizations, there was a surplus of options that made it diffcult to select one visualizations over another.

Conclusion

This project gave me a great understanding on how important visualizations play a role in making decision based on data. I have mentioned in another project, Seaborn is a great package and it make visualization creation easy for anyone.

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