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Update code to rearrange table columns based on column_order from acsm_to_ebas.yaml. This can be removed in the future.
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@ -19,10 +19,11 @@ import argparse
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import pandas as pd
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import json, yaml
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import numpy as np
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from utils import get_metadata
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from utils import metadata_dict_to_dataframe
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from pipelines.steps.utils import get_metadata
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from pipelines.steps.utils import metadata_dict_to_dataframe
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from pipelines.steps.utils import load_project_yaml_files
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def join_tables(csv_files: list):
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"""
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Joins multiple CSV files based on their metadata-defined datetime column.
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@ -142,6 +143,9 @@ def main(paths_to_processed_files : list, path_to_flags : str, month : int = Non
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#output_file1 = os.path.join(output_dir, f'JFJ_ACSM-017_2024_month{args.month}.txt' if args.month else 'JFJ_ACSM-017_2024.txt')
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#output_file2 = os.path.join(output_dir, f'JFJ_ACSM-017_FLAGS_2024_month{args.month}.txt' if args.month else 'JFJ_ACSM-017_FLAGS_2024.txt')
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#acum_df = acum_df[[col for col in acsm_to_ebas['column_order'] if col in acum_df.columns]]
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#flags_acum_df = flags_acum_df[[col for col in acsm_to_ebas['flags_column_order'] if col in flags_acum_df.columns]]
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acum_df.loc[:, :].to_csv(output_file1, sep='\t', index=None, date_format="%Y/%m/%d %H:%M:%S")
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flags_acum_df.loc[:, :].to_csv(output_file2, sep='\t', index=None, date_format="%Y/%m/%d %H:%M:%S")
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