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Add files via upload
gitedmond Mar 16, 2023
b124243
Update README.md
gitedmond Mar 16, 2023
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2 changes: 0 additions & 2 deletions README.md
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# First-Data-Analysis-Project
This is going to be my first project where I import, clean, visualize, and make sense of a database on FIFA 19 players I imported from 'Javagar M' on Kaggle. The dataset provides information such ad name,ID,overall,potential,club, and more.

For the 'potentialvis.py' program, the output is the top 50 football clubs that, according to the dataset, had the most amount of potential increase for the players that were signed to thier club.

I will continue to make visualizations through graphs and python programs for this database.

Thank you for witnessing the first of my many projects
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20 changes: 20 additions & 0 deletions heatmap.py
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import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

# Load the dataset
df = pd.read_csv('/Users/sarge/Downloads/heatmap_cleaned.csv')

# Create a heatmap of player attributes by position
position_groups = df.groupby('Position')[df.columns[61:88]].mean().reset_index()
heatmap_data = position_groups.set_index('Position').T
sns.heatmap(heatmap_data, cmap='RdYlGn', linewidths=0.5,
annot=True, fmt='.2f', cbar=False)
plt.title('Player Attributes by Position in FIFA 19')
plt.xlabel('Position')
plt.ylabel('Attribute')

# Show the plot
plt.show()


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