https://github.com/csengupta1101/fifa21-player-analysis
This repository runs through modern day footballers and it analyzes their attributes that makes them greatest in the world
https://github.com/csengupta1101/fifa21-player-analysis
fifa football jupyter-notebook messi python python3 ronaldo
Last synced: 3 months ago
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This repository runs through modern day footballers and it analyzes their attributes that makes them greatest in the world
- Host: GitHub
- URL: https://github.com/csengupta1101/fifa21-player-analysis
- Owner: Csengupta1101
- Created: 2021-09-14T14:56:12.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2021-11-15T11:02:00.000Z (over 3 years ago)
- Last Synced: 2024-12-29T04:50:55.289Z (5 months ago)
- Topics: fifa, football, jupyter-notebook, messi, python, python3, ronaldo
- Language: Jupyter Notebook
- Homepage:
- Size: 2.22 MB
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Fifa21 Player Analysis
This analysis mostly comprises the visualization of fifa players across clubs , countries and continents. Hoping this to be a treat to your eyes.
## Workflow
The Competition solution workflow goes through seven stages described in the Data Science Solution book.
1. Question or problem definition.
2. Acquire training and testing data.
3. Wrangle, prepare, cleanse the data.
4. Visualize, report, and present the problem solving steps and final solution.
5. Supply or submit the results.
The workflow indicates general sequence of how each stage may follow the other. However there are use cases with exceptions.
- We may combine mulitple workflow stages. We may analyze by visualizing data.
- Perform a stage earlier than indicated. We may analyze data before and after wrangling.
- Perform a stage multiple times in our workflow. Visualize stage may be used multiple times.
- Drop a stage altogether. We may not need supply stage to productize or service enable our dataset for a competition.
## Findings
As said earlier this analysis comprises of players and their best and worst attributes. So the best way to analyze here is to visualize -
