FIFA19 Data Visualization by Léo

Leonardo Cavalcante Araújo

Data Analysis Full-Time FEB2021, Paris & February 29th 2021

Content

• Project Description
• Objective
• Workflow
• Organization
• Links

Project Description

Football analytics: Data Analysis and Visualizations using the FIFA19 dataset from Kaggle.

Content of the dataset

Detailed attributes for every player registered in the edition of FIFA 19 database. Scraping code at GitHub repo: https://github.com/amanthedorkknight/fifa18-all-player-statistics/tree/master/2019

Acknowledgements

Data scraped from https://sofifa.com/

Inspiration

Inspired from this dataset: https://www.kaggle.com/thec03u5/fifa-18-demo-player-dataset

Objective

• Practice visualization tools using Python (and the libraries MatplotLib and Seaborn) learned during the Week 4 of the Data Analytics Bootcamp of Ironhack.
• Deliver descriptive insights from the dataset.

Workflow

1. Import the dataset into a dataframe.
2. Clean data and prepare for analysis.
3. Analysis of interesting parameters to visualize.
4. Data Visualization.
5. Export results and conceal presentation.

Organization

• Repository "https://github.com/leo-cavalcante/fifa-19-analysis-and-visualizations" : you may find my main Python codes stored as a Jupyter Notebook format, also the folder "Players" used to store players pictures used for the code and also the folder "Visualizations" with the visualizations produced in the notebook.

PS.: individual project.

Links

Here you may find the relevant links for the repository, the main code and the final presentation slides.

GitHub Repository: fifa-19-analysis-and-visualizations

Google Slides: FIFA19 Presentation

Jupyter Notebook: FIFA19_vFinal