import pandas as pd
from sklearn.model_selection import train_test_split


combined_df = pd.read_parquet("./ml_input_data/QML9.parquet")


train_df, temp_df = train_test_split(combined_df, test_size=0.20, random_state=42)

# 2) split temp into 50/50 → 10% each of original
valid_df, test_df = train_test_split(temp_df, test_size=0.50, random_state=42)

# confirm sizes
print(f"Train: {len(train_df)/len(df):.2%}")
print(f"Valid: {len(valid_df)/len(df):.2%}")
print(f"Test:  {len(test_df)/len(df):.2%}")
train_df.to_parquet("./ml_input_data/train_split.parquet")
valid_df.to_parquet("./ml_input_data/validation_split.parquet")
test_df.to_parquet("./ml_input_data/test_split.parquet")