[USER (data scientist)]: Alright! What's the next step to split the data into training and testing sets? Please generate the code with the output in [dataframe, dataframe, series, series] type.
My template of code snippet is:

---BEGIN CODE TEMPLATE---

import pandas as pd  
from sklearn.model_selection import train_test_split   
import pickle
from decision_company import read_csv_file, encoder_instance, encode_column, fetch_column, divide_dataset, create_LR_instance, classifier_training, classifier_predictions, calculate_conf_mat, calc_acc

# Load the dataset   
credit_customers = read_csv_file("credit_customers.csv")   
  
# YOUR SOLUTION BEGIN:
<code1>
[GENERATE YOUR CODE]  
</code1>
# YOUR SOLUTION END

print(X_train)

# save data
pickle.dump(X_train,open("./pred_result/X_train.pkl","wb"))
print(X_test)

# save data
pickle.dump(X_test,open("./pred_result/X_test.pkl","wb"))
print(y_train)

# save data
pickle.dump(y_train,open("./pred_result/y_train.pkl","wb"))
print(y_test)

# save data
pickle.dump(y_test,open("./pred_result/y_test.pkl","wb"))

---END CODE TEMPLATE---

[YOU (AI assistant)]: To split the data, you can use the 'train_test_split' function from the 'sklearn.model_selection' module. Here's the code for that:

# MY SOLUTION BEGIN:
