Label Encoded dataset

main.py

@@ -3,4 +3,10 @@ import matplotlib.pyplot as plt
 from sklearn.preprocessing import LabelEncoder
 from sklearn.model_selection import train_test_split
 
-dataset = pd.read_csv("data.csv")
+dataset = pd.read_csv("data.csv")
+
+dataset.drop(columns=['customerID'], inplace=True)
+
+encoder = LabelEncoder()
+for column in dataset.select_dtypes(include=['object']).columns:
+    dataset[column] = encoder.fit_transform(dataset[column])