gitedmond · gitedmond · Mar 16, 2023 · Mar 16, 2023 · Mar 16, 2023 · Mar 16, 2023
diff --git a/.github/workflows/Capture.PNG b/.github/workflows/Capture.PNG
diff --git a/.github/workflows/kl.csv b/.github/workflows/kl.csv
diff --git a/.github/workflows/kl_cleaned_edit_history.pdf b/.github/workflows/kl_cleaned_edit_history.pdf
diff --git a/.github/workflows/potentialvis.py b/.github/workflows/potentialvis.py
diff --git a/National_Distribution.py b/National_Distribution.py
@@ -0,0 +1,22 @@
+import pandas as pd
+import matplotlib.pyplot as plt
+
+# Load the dataset
+df = pd.read_csv('/Users/sarge/Downloads/nd_cleaned.csv')
+
+# Count the number of players from each nationality
+nationality_counts = df['Nationality'].value_counts()
+
+# Create a bar chart
+plt.bar(nationality_counts.index, nationality_counts.values)
+
+# Set the chart title and axis labels
+plt.title('Nationality Distribution of FIFA 19 Players')
+plt.xlabel('Nationality')
+plt.ylabel('Number of Players')
+
+# Rotate the x-axis labels to avoid overlapping
+plt.xticks(rotation=90)
+
+# Show the plot
+plt.show()
diff --git a/National_Distribution_vis.PNG b/National_Distribution_vis.PNG
diff --git a/.github/workflows/kl_cleaned.csv → nd_cleaned.csv b/.github/workflows/kl_cleaned.csv → nd_cleaned.csv