pvlib.iotools.get_meteonorm_observation_training#

pvlib.iotools.get_meteonorm_observation_training(latitude, longitude, start, end, api_key, parameters='all', *, surface_tilt=0, surface_azimuth=180, time_step='15min', horizon='auto', interval_index=False, map_variables=True, url='https://api.meteonorm.com/v1/')[source]#

Retrieve historical observational data from Meteonorm.

The Meteonorm data options are described in [1] and the API is described in [2]. A detailed list of API options can be found in [3].

Parameters:

latitude (float) – In decimal degrees, north is positive (ISO 19115).
longitude (float) – In decimal degrees, east is positive (ISO 19115).
start (datetime like) – First timestamp of the requested period. If a timezone is not specified, UTC is assumed.
end (datetime like) – Last timestamp of the requested period. If a timezone is not specified, UTC is assumed.
api_key (str) – Meteonorm API key.
parameters (list or 'all', default : 'all') – List of parameters to request or ‘all’ to get all parameters.
surface_tilt (float, default : 0) – Tilt angle from horizontal plane.
surface_azimuth (float, default : 180) – Orientation (azimuth angle) of the (fixed) plane. Clockwise from north (north=0, east=90, south=180, west=270).
time_step ({'1min', '15min', '1h'}, default : '15min') – Frequency of the time series.
horizon (str or list, default : 'auto') – Specification of the horizon line. Can be either ‘flat’, ‘auto’, or a list of 360 integer horizon elevation angles.
interval_index (bool, default : False) – Index is pd.DatetimeIndex when False, and pd.IntervalIndex when True. This is an experimental feature which may be removed without warning.
map_variables (bool, default : True) – When true, renames columns of the Dataframe to pvlib variable names where applicable. See variable VARIABLE_MAP.
url (str, optional) – Base URL of the Meteonorm API. The default is pvlib.iotools.meteonorm.URL.

Raises:

requests.HTTPError – Raises an error when an incorrect request is made.

Returns:

data (pd.DataFrame) – Time series data. The index corresponds to the middle of the interval unless interval_index is set to True.
meta (dict) – Metadata.

Examples

>>> # Retrieve historical time series data
>>> df, meta = pvlib.iotools.get_meteonorm_observation_training(  
...     latitude=50, longitude=10,  
...     start='2023-01-01', end='2025-01-01',  
...     api_key='redacted')  