Files
MachineLearningNotebooks/how-to-use-azureml/automated-machine-learning/forecasting-many-models/scripts/data_preprocessing_tabular.py

32 lines
711 B
Python

from pathlib import Path
from azureml.core import Run
import argparse
def main(args):
output = Path(args.output)
output.mkdir(parents=True, exist_ok=True)
run_context = Run.get_context()
dataset = run_context.input_datasets["train_10_models"]
df = dataset.to_pandas_dataframe()
# Apply any data pre-processing techniques here
df.to_parquet(output / "data_prepared_result.parquet", compression=None)
def my_parse_args():
parser = argparse.ArgumentParser("Test")
parser.add_argument("--input", type=str)
parser.add_argument("--output", type=str)
args = parser.parse_args()
return args
if __name__ == "__main__":
args = my_parse_args()
main(args)