def save_regional_data()

in src/data_utils.py [0:0]

• 9 lines of code
• 1 McCabe index (conditional complexity)

def save_regional_data(data_dict, meta_dict, bucket):
    """Uploads the labeled data for a region to s3

    Args:
        data_dict: dictionary containing base image, mangrove and non-mangrove data frames
        meta_dict: dictionary containing metadata
        bucket: s3 bucket name
    """
    df_training = pd.concat([data_dict["df_mangrove"], data_dict["df_other"]], axis=0)
    df_training = shuffle(df_training)

#     fname = f"{meta_dict['src_dataset']}_year{meta_dict['year']}_{meta_dict['poi']}.csv"
    fname = f"{meta_dict['src_dataset']}/Year{meta_dict['year']}/{meta_dict['poi']}.csv"
    df_training.to_csv(f"s3://{bucket}/{fname}", index=False)

    num_rows = df_training.label.value_counts()
    print(
        f"rows: {len(df_training)}, rows_mangrove = {num_rows[1]},  rows_other = {num_rows[0]}"
    )