Python library not getting up to date monthly data compared to webapp

[willawebb]

Hi Christian,

I'm currently working to implement a simple feature that uses meteostat's Monthly to grab the last month of weather data for some location. In this case, I just wanted the data from April. By chance, I ended up trying a station in Chicago, KPWK0, which doesn't have any data newer than February:

>>> test = meteostat.Monthly('KPWK0')
>>> test.fetch()
            tavg  tmin  tmax  prcp  wspd    pres  tsun
time
2006-01-01   1.8  -1.4   5.0   NaN  15.2     NaN   NaN
2006-05-01  15.0  10.0  19.9   NaN  12.1     NaN   NaN
2006-06-01  19.7  14.9  24.3   NaN   NaN     NaN   NaN
2006-10-01   9.2   4.8  13.7   NaN  13.6     NaN   NaN
2007-01-01  -2.1  -5.5   0.9   NaN  16.5     NaN   NaN
...          ...   ...   ...   ...   ...     ...   ...
2022-10-01  11.6   6.1  17.2  43.4  12.4  1016.9   NaN
2022-11-01   6.0   1.2  10.7  33.3  15.0  1019.0   NaN
2022-12-01  -1.0  -4.9   2.3  51.9  15.1  1018.6   NaN
2023-01-01   0.3  -2.1   3.0  60.1  12.5  1016.6   NaN
2023-02-01   1.6  -3.4   6.0  90.3  15.2  1016.6   NaN

[110 rows x 7 columns]

I then checked the meteostat webapp, and saw that wasn't having any issues with that particular location.

I don't have such an issue when I use the Frankfurt airport station 10637:

>>> test = meteostat.Monthly('10637') 
>>> test.fetch()
           tavg  tmin  tmax  prcp  wspd    pres    tsun
time
1934-05-01  15.6   NaN   NaN   NaN   NaN     NaN     NaN
1934-06-01  17.9   NaN  24.7   NaN   NaN     NaN     NaN
1934-07-01  20.4   NaN  26.1   NaN   NaN     NaN     NaN
1934-08-01  17.8   NaN   NaN   NaN   NaN     NaN     NaN
1934-09-01  17.4   NaN   NaN   NaN   NaN     NaN     NaN
...          ...   ...   ...   ...   ...     ...     ...
2022-12-01   3.2   0.2   5.5  54.9  12.5  1016.6  2486.0
2023-01-01   5.0   2.5   7.1  62.9  16.8  1018.7  2035.0
2023-02-01   4.9   1.3   8.4   9.3  13.6  1028.9  5795.0
2023-03-01   7.6   3.1  12.2  98.1  16.1  1012.5  6778.0
2023-04-01   9.6   4.7  14.3  43.9  12.9  1017.3  9366.0

[1026 rows x 7 columns]

Do you happen to know why this might be occurring? Thanks in advance!