feat: prepare

prepare_data.py

@@ -0,0 +1,20 @@
+import pandas as pd
+from sklearn.preprocessing import MinMaxScaler
+
+def prepare_data(file_path):
+    data = pd.read_csv(file_path, sep=';')
+
+    data = pd.get_dummies(data, columns=['Sex', 'Medal'])
+    data = data.drop(columns=['Name', 'Team', 'NOC', 'Games', 'Year', 'Season', 'City', 'Sport', 'Event'])
+
+    data = data.fillna(0)
+    scaler = MinMaxScaler()
+    data = pd.DataFrame(scaler.fit_transform(data), columns=data.columns)
+
+    return data
+
+if __name__ == "__main__":
+    file_path = 'olympics-124-years-datasettill-2020/Data.csv'
+    data = prepare_data(file_path)
+
+    data.to_csv('processed_data.csv', index=False)