opyplus.WeatherData

class opyplus.WeatherData(weather_series, latitude, longitude, timezone_offset, elevation, city=None, state_province_region=None, country=None, source=None, wmo=None, design_conditions_source=None, design_conditions=None, typical_extreme_periods=None, ground_temperatures=None, leap_year_observed='yes', daylight_savings_start_day=0, daylight_savings_end_day=0, holidays=None, comments_1='', comments_2='', start_day_of_week=None)

Class describing E+ weather data.

For more information on following concepts, see EnergyPlus documentation : AuxiliaryPrograms.pdf: Weather Converter Program/EnergyPlus Weather File (EPW) Data Dictionary

Parameters:

weather_series: pandas.DataFrame

containing epw columns (some may be missing)
missing values may be None or E+ missing value

latitude

longitude

timezone_offset

elevation

city

state_province_region

country

source

wmo

design_conditions_source

design_conditions

typical_extreme_periods

ground_temperatures

leap_year_observed

daylight_savings_start_day

daylight_savings_end_day

holidays

comments_1

comments_2

start_day_of_week

Attributes:

has_datetime_instants: Check if datetime instants have been created.

Methods

`create_datetime_instants`([start_year])	Add a datetime index to the weather series data frame.
`from_epw`(buffer_or_path[, ...])	See load.
`get_bounds`([use_datetimes])	Get datetime instants of beginning and end of data.
`get_info`()	Get WeatherData info.
`get_weather_series`()	Get the weather series dataframe.
`load`(buffer_or_path[, ...])	Load weather data from an epw file.
`save`([buffer_or_path, use_datetimes])	Save weather data as an epw file.
`set_weather_series`(weather_series[, ...])	Set a new weather series dataframe.
`to_epw`([buffer_or_path, use_datetimes])	See save.

create_datetime_instants(start_year=None)

Add a datetime index to the weather series data frame.

Parameters:

start_year: int or None, default None: if given, will force year column with start_year (multi-year not supported for now)

classmethod from_epw(buffer_or_path, create_datetime_instants=False, start_year=None) → WeatherData: See load.

get_bounds(use_datetimes=True)

Get datetime instants of beginning and end of data. If no data, will be: (None, None).

Parameters:

use_datetimes: bool

Returns:

datetime.datetime or None: start
datetime.datetime or None: end

get_info()

Get WeatherData info.

Returns:

str

get_weather_series()

Get the weather series dataframe.

Returns:

pandas.DataFrame: weather series dataframe, which contains all the timeseries data. Will be a datetime series or a tuple instants series depending on current mode.

property has_datetime_instants

Check if datetime instants have been created.

Returns:

bool

classmethod load(buffer_or_path, create_datetime_instants=False, start_year=None) → WeatherData

Load weather data from an epw file.

Parameters:

buffer_or_path: str or typing.StringIO: buffer or path containing epw format.
create_datetime_instants: bool: set datetime instants index after file was loaded
start_year: int or None: only used if create_datetime_instants is True if given, will force year column with start_year (multi-year not supported for now)

Returns:

WeatherData instance.

save(buffer_or_path=None, use_datetimes=True)

Save weather data as an epw file.

Parameters:

buffer_or_path: str or typing.StringIO: Buffer or path to write into. If None, will return a string containing epw info.
use_datetimes: bool: if True and datetime index was created, will use this index to generate epw (start day and data) else: will use instant columns information

Returns:

str or None

set_weather_series(weather_series, start_day_of_week=None)

Set a new weather series dataframe.

Parameters:

weather_series: pandas.DataFrame: weather series dataframe, which contains all the timeseries data.
start_day_of_week: str, default None: “Sunday”, “Monday”, “Tuesday”, “Wednesday”, “Thursday”, “Friday”, “Saturday”

to_epw(buffer_or_path=None, use_datetimes=True): See save.