Lightweight Python package for editing EnergyPlus Weather (epw) files
EnergyPlus weather files or .epw files are comma separated variable (csv) files which contain weather and location information. They are used to provide climate data for the energy simulations of the EnergyPlus simulation software.
This package provides a epw class for reading, modifying and saving .epw files.
pip install git+https://github.com/building-energy/epw.git@master
Or save the entire package locally, and do a local pip install.
Reading a .epw file:
>>> from epw import epw
>>> a=epw()
>>> a.read(r'C:\EnergyPlusV8-9-0\WeatherData\USA_CA_San.Francisco.Intl.AP.724940_TMY3.epw')
>>> print(a)
<epw.epw.epw object at 0x00000155BBAB99E8>Viewing the header information:
>>> d=a.headers # this is a dictionary of the header information
>>> print(d)
{'LOCATION': ['San Francisco Intl Ap', 'CA', 'USA', 'TMY3', '724940', '37.62', '-122.40', '-8.0', '2.0'],
'DESIGN CONDITIONS': ['1', 'Climate Design Data 2009 ASHRAE Handbook', '', 'Heating', '1', '3.8', '4.9', '-3.7', '2.8', '10.7', '-1.2', '3.4', '11.2', '12.9', '12.1', '11.6', '12.2', '2.2', '150', 'Cooling', '8', '8.5', '28.3', '17.2', '25.7', '16.7', '23.6', '16.2', '18.6', '25.7', '17.8', '23.9', '17', '22.4', '5.9', '310', '16.1', '11.5', '19.9', '15.3', '10.9', '19.2', '14.7', '10.4', '18.7', '52.4', '25.8', '49.8', '23.8', '47.6', '22.4', '2038', 'Extremes', '12.8', '11.5', '10.6', '22.3', '1.8', '34.6', '1.5', '2.3', '0.8', '36.2', '-0.1', '37.5', '-0.9', '38.8', '-1.9', '40.5'],
'TYPICAL/EXTREME PERIODS': ['6', 'Summer - Week Nearest Max Temperature For Period', 'Extreme', '8/ 1', '8/ 7', 'Summer - Week Nearest Average Temperature For Period', 'Typical', '9/ 5', '9/11', 'Winter - Week Nearest Min Temperature For Period', 'Extreme', '2/ 1', '2/ 7', 'Winter - Week Nearest Average Temperature For Period', 'Typical', '2/15', '2/21', 'Autumn - Week Nearest Average Temperature For Period', 'Typical', '12/ 6', '12/12', 'Spring - Week Nearest Average Temperature For Period', 'Typical', '5/29', '6/ 4'],
'GROUND TEMPERATURES': ['3', '.5', '', '', '', '10.86', '10.57', '11.08', '11.88', '13.97', '15.58', '16.67', '17.00', '16.44', '15.19', '13.51', '11.96', '2', '', '', '', '11.92', '11.41', '11.51', '11.93', '13.33', '14.60', '15.61', '16.15', '16.03', '15.32', '14.17', '12.95', '4', '', '', '', '12.79', '12.27', '12.15', '12.31', '13.10', '13.96', '14.74', '15.28', '15.41', '15.10', '14.42', '13.60'],
'HOLIDAYS/DAYLIGHT SAVINGS': ['No', '0', '0', '0'],
'COMMENTS 1': ['Custom/User Format -- WMO#724940; NREL TMY Data Set (2008); Period of Record 1973-2005 (Generally)'],
'COMMENTS 2': [' -- Ground temps produced with a standard soil diffusivity of 2.3225760E-03 {m**2/day}'],
'DATA PERIODS': ['1', '1', 'Data', 'Sunday', ' 1/ 1', '12/31']}Viewing the climate data
>>> df=a.dataframe # this is pandas dataframe
>>> df1=df[['Year', 'Month', 'Day', 'Hour', 'Minute','Dry Bulb Temperature']]
>>> print(df1.head())
Year Month Day Hour Minute Dry Bulb Temperature
0 1999 1 1 1 0 7.2
1 1999 1 1 2 0 7.2
2 1999 1 1 3 0 6.7
3 1999 1 1 4 0 6.1
4 1999 1 1 5 0 4.4Modifying the header information:
>>> a.headers['LOCATION'][0]='New_location' # modifies the location city
>>> print(a.headers['LOCATION'])
['New_location', 'CA', 'USA', 'TMY3', '724940', '37.62', '-122.40', '-8.0', '2.0']Modifying the climate data:
>>> a.dataframe['Dry Bulb Temperature']=a.dataframe['Dry Bulb Temperature']+1.0 # increases dry bulb temperature by 1 degree C
>>> print(a.dataframe[['Year', 'Month', 'Day', 'Hour', 'Minute','Dry Bulb Temperature']].head())
Year Month Day Hour Minute Dry Bulb Temperature
0 1999 1 1 1 0 8.2
1 1999 1 1 2 0 8.2
2 1999 1 1 3 0 7.7
3 1999 1 1 4 0 7.1
4 1999 1 1 5 0 5.4Saving the modified .epw file:
>>> a.write('new_epw_file.epw')
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