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Core Modules

core

Functions:

Attributes:

fileHandler module-attribute 

fileHandler = FileHandler(join(str(package_config['data_dir']), 'PPM.log'))

logFormatter module-attribute 

logFormatter = Formatter('%(asctime)s [%(threadName)-12.12s] [%(levelname)-5.5s]  %(message)s')

package_config module-attribute 

package_config = {'custom_config': join(expanduser('~'), '.powerplantmatching_config.yaml'), 'data_dir': _data_dir, 'repo_data_dir': join(dirname(__file__), 'package_data'), 'downloaders': {}}

get_config 

get_config(filename=None, **overrides)

Import the default configuration file and update custom settings.

Parameters:

  • filename (str, default: None ) –

    DESCRIPTION. The default is None.

  • **overrides (dict, default: {} ) –

    DESCRIPTION.

Returns:

  • config ( dict ) –

    The configuration dictionary

get_obj_if_Acc 

get_obj_if_Acc(obj)

duke

Functions:

  • add_geoposition_for_duke –

    Returns the same pandas.Dataframe with an additional column "Geoposition"

  • duke –

    Run duke in different modes (Deduplication or Record Linkage Mode) to

add_geoposition_for_duke 

add_geoposition_for_duke(df)

Returns the same pandas.Dataframe with an additional column "Geoposition" which concats the latitude and longitude of the powerplant in a string

duke 

duke(datasets, labels=['one', 'two'], singlematch=False, showmatches=False, keepfiles=False, showoutput=False, threads=1)

Run duke in different modes (Deduplication or Record Linkage Mode) to either locate duplicates in one database or find the similar entries in two different datasets. In RecordLinkagesMode (match two databases) please set singlematch=True and use best_matches() afterwards

Parameters:

  • datasets (DataFrame or [DataFrame]) –

    A single dataframe is run in deduplication mode, while multiple ones are linked

  • labels ([str], default: ['one', 'two'] ) –

    Labels for the linked dataframe

  • singlematch –

    Only in Record Linkage Mode. Only report the best match for each entry of the first named dataset. This does not guarantee a unique match in the second named dataset.

  • keepfiles (boolean, default: False ) –

    If true, do not delete temporary files

accessor

Classes:

PowerPlantAccessor 

PowerPlantAccessor(pandas_obj)

Accessor object for DataFrames created with powerplantmatching. This simplifies the access to common functions applicable to dataframes with powerplant data. Note even though this is a general DataFrame accessor, the functions will only work for powerplantmatching related DataFrames.

Examples:

import powerplantmatching as pm entsoe = pm.data.ENTSOE() entsoe.powerplant.plot_aggregated()

Methods:

get_name 

get_name()

match_with 

match_with(df, labels=None, config=None, reduced=True, **dukeargs)

plot_aggregated 

plot_aggregated(by=['Country', 'Fueltype'], figsize=(12, 20), **kwargs)

Plotting function for fast inspection of the capacity distribution. Returns figure and axes of a matplotlib barplot.

Parameters:

  • by (list, default: ['Country', 'Fueltype'] ) –

    Define the columns of the dataframe to be grouped on.

  • figsize (tuple, default: (12,20) ) –

    width and height of the figure

  • **kwargs –

    keywordargument for matplotlib plotting

set_name 

set_name(name)