read_csv.py

import csv
from datetime import datetime
import re

import numpy as np
import pandas as pd

def load_meped_csv(file_name, as_df=True, remove_duplicate_cols=True):
    """
    Load the meped data into a dictionary or a pandas 
    DataFrame, togled by the as_df kwarg.
    """
    with open(file_name) as csv_file:
        reader = csv.reader(csv_file)
        mydict = dict(reader)

    for key, val in mydict.items():
        # Remove all of the non-numeric characters
        if '...' in val:
            raise ValueError('The metop data is not formatted correctly.')
        val = val.replace('\n', '')
        val = val.replace('[', '')
        val = val.replace(']', '')
        val = val.replace(',', '')

        mydict[key] = np.array(val.split()).astype(float)

    if as_df:
        df = pd.DataFrame(data=mydict)
        df['day'] = df['dom']
        df['dateTime'] = pd.to_datetime(
            df[['year', 'month', 'day', 'Hour', 'minute', 'second']]
            )
        df.index = df['dateTime']
        if remove_duplicate_cols:
            drop_cols = [
                'dateTime', 'year', 'month', 'day', 
                'Hour', 'minute', 'second', 'dom'
                ]
            df = df.drop(drop_cols, axis=1)
        return df
    else:
        return mydict

if __name__ == "__main__":   
    file_name = './csv_daily_data/data_metop0220061206.csv'
    df = load_meped_csv(file_name)
    print(df)