Merge meteotrentino data files

merge_meteo_data.py

import pandas as pd
import numpy as np
import os

#fem_data =  pd.read_csv('temperature_fem.csv', header=0, parse_dates=[1], index_col=1, squeeze=True)


variable = "temperature"
is_sum= False
stations = pd.read_csv("../stations_tot.csv", index_col=0)
dfs = {}

for key, row in stations.iterrows():
    if 'T0' in row['nomebreve'] and os.path.exists("./"+variable+"/"+ row['nomebreve'].lower()+".csv"):
        print(row['nomebreve'])
        file_path = "./"+variable+"/"+ row['nomebreve'].lower()+".csv"
        df = pd.read_csv(
            file_path,
            skiprows=4,
            header=None,
            names=['Datetime', 'Value', 'Qual', 'Metadata'],
            parse_dates=[0], index_col=0, squeeze=True,
            dayfirst=True,
            low_memory=False,
            encoding='latin1'  
        )
        df.drop(columns=['Metadata'], inplace=True)
        df = df[(df['Qual']!=140) &  (df['Qual']!=255)]
        df.drop(columns=['Qual'], inplace=True)
        if is_sum:
            df = df.resample('H').sum()
        else:
            df = df.resample('H').mean()
        df.index = df.index - pd.Timedelta(hours=1)
        dfs[key] = df['Value']

final_df = pd.concat(dfs, axis=1)

fem_data =  pd.read_csv('temperature_fem.csv', header=0, parse_dates=[1], index_col=1, squeeze=True)
d = pd.merge( fem_data,final_df, left_index=True, right_index=True, how = "outer")

d.to_csv(variable+".csv")