pvlib.iotools.parse_psm3#
- pvlib.iotools.parse_psm3(filename, map_variables=True)#
- Deprecated since version 0.13.0: The parse_psm3 function was deprecated in pvlib 0.13.0 and will be removed soon. Use read_psm3 instead. - Read an NSRDB PSM3 weather file (formatted as SAM CSV). The NSRDB is described in [1] and the SAM CSV format is described in [2]. - Changed in version 0.9.0: The function now returns a tuple where the first element is a dataframe and the second element is a dictionary containing metadata. Previous versions of this function had the return values switched. - Parameters:
- Returns:
- data (pandas.DataFrame) – timeseries data from NREL PSM3 
- metadata (dict) – metadata from NREL PSM3 about the record, see notes for fields 
 
 - Notes - The return is a tuple with two items. The first item is a dataframe with the PSM3 timeseries data. - The second item is a dictionary with metadata from NREL PSM3 about the record containing the following fields: - Source 
- Location ID 
- City 
- State 
- Country 
- Latitude 
- Longitude 
- Time Zone 
- Elevation 
- Local Time Zone 
- Clearsky DHI Units 
- Clearsky DNI Units 
- Clearsky GHI Units 
- Dew Point Units 
- DHI Units 
- DNI Units 
- GHI Units 
- Solar Zenith Angle Units 
- Temperature Units 
- Pressure Units 
- Relative Humidity Units 
- Precipitable Water Units 
- Wind Direction Units 
- Wind Speed Units 
- Cloud Type -15 
- Cloud Type 0 
- Cloud Type 1 
- Cloud Type 2 
- Cloud Type 3 
- Cloud Type 4 
- Cloud Type 5 
- Cloud Type 6 
- Cloud Type 7 
- Cloud Type 8 
- Cloud Type 9 
- Cloud Type 10 
- Cloud Type 11 
- Cloud Type 12 
- Fill Flag 0 
- Fill Flag 1 
- Fill Flag 2 
- Fill Flag 3 
- Fill Flag 4 
- Fill Flag 5 
- Surface Albedo Units 
- Version 
 - Examples - >>> # Read a local PSM3 file: >>> df, metadata = iotools.read_psm3("data.csv") - >>> # Read a file object or an in-memory buffer: >>> with open(filename, 'r') as f: ... df, metadata = iotools.read_psm3(f) - See also - References 
