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Lightweight Python package for editing EnergyPlus Weather (epw) files

epw 최신버젼 다운로드

최종 버전 다운로드 (.zip)

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# epw
Lightweight Python package for editing EnergyPlus Weather (epw) files

## Overview

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.

## Installation

`pip install git+https://github.com/building-energy/epw.git@master`

Or save the entire package locally, and do a local pip install.

## Usage

Reading a .epw file:

```python
>>> 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:

```python
>>> 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
```python
>>> 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                   4.4
```

Modifying the header information:

```python
>>> 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:

```python
>>> 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                   5.4

```

Saving the modified .epw file:

```python
>>> a.write('new_epw_file.epw')
```

epw

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