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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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florez_j
2025-03-18 07:23:54 +01:00
parent 261c8b8154
commit b0d68747e9
1 changed files with 6 additions and 2 deletions
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8
pipelines/steps/prepare_ebas_submission.py
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@ -19,10 +19,11 @@ import argparse
import pandas as pd import pandas as pd
import json, yaml import json, yaml
import numpy as np import numpy as np
from utils import get_metadata from pipelines.steps.utils import get_metadata
from utils import metadata_dict_to_dataframe from pipelines.steps.utils import metadata_dict_to_dataframe
from pipelines.steps.utils import load_project_yaml_files from pipelines.steps.utils import load_project_yaml_files
def join_tables(csv_files: list): def join_tables(csv_files: list):
""" """
Joins multiple CSV files based on their metadata-defined datetime column. Joins multiple CSV files based on their metadata-defined datetime column.
@ -142,6 +143,9 @@ def main(paths_to_processed_files : list, path_to_flags : str, month : int = Non
#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') #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')
#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') #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')
#acum_df = acum_df[[col for col in acsm_to_ebas['column_order'] if col in acum_df.columns]]
#flags_acum_df = flags_acum_df[[col for col in acsm_to_ebas['flags_column_order'] if col in flags_acum_df.columns]]
acum_df.loc[:, :].to_csv(output_file1, sep='\t', index=None, date_format="%Y/%m/%d %H:%M:%S") acum_df.loc[:, :].to_csv(output_file1, sep='\t', index=None, date_format="%Y/%m/%d %H:%M:%S")
flags_acum_df.loc[:, :].to_csv(output_file2, sep='\t', index=None, date_format="%Y/%m/%d %H:%M:%S") flags_acum_df.loc[:, :].to_csv(output_file2, sep='\t', index=None, date_format="%Y/%m/%d %H:%M:%S")