momepy.AverageCharacter

class momepy.AverageCharacter(gdf, values, spatial_weights, unique_id, rng=None, mode='all', verbose=True)

Calculates the average of a character within a set neighbourhood defined in spatial_weights

Average value of the character within a set neighbourhood defined in spatial_weights. Can be set to mean, median or mode. mean is defined as:

\[\frac{1}{n}\left(\sum_{i=1}^{n} value_{i}\right)\]

Adapted from [HBP17].

Parameters

gdfGeoDataFrame

GeoDataFrame containing morphological tessellation

valuesstr, list, np.array, pd.Series

the name of the dataframe column, np.array, or pd.Series where is stored character value.

unique_idstr

name of the column with unique id used as spatial_weights index.

spatial_weightslibpysal.weights

spatial weights matrix

rngTwo-element sequence containing floats in range of [0,100], optional

Percentiles over which to compute the range. Each must be between 0 and 100, inclusive. The order of the elements is not important.

modestr (default ‘all’)

mode of average calculation. Can be set to all, mean, median or mode or list of any of the options.

verbosebool (default True)

if True, shows progress bars in loops and indication of steps

Examples

>>> sw = libpysal.weights.DistanceBand.from_dataframe(tessellation,
...                                                   threshold=100,
...                                                   silence_warnings=True,
...                                                   ids='uID')
>>> tessellation['mean_area'] = momepy.AverageCharacter(tessellation,
...                                                     values='area',
...                                                     spatial_weights=sw,
...                                                     unique_id='uID').mean
100%|██████████| 144/144 [00:00<00:00, 1433.32it/s]
>>> tessellation.mean_area[0]
4823.1334436678835

Attributes

seriesSeries

Series containing resulting mean values

meanSeries

Series containing resulting mean values

medianSeries

Series containing resulting median values

modeSeries

Series containing resulting mode values

gdfGeoDataFrame

original GeoDataFrame

valuesGeoDataFrame

Series containing used values

swlibpysal.weights

spatial weights matrix

idSeries

Series containing used unique ID

rngtuple

range

modesstr

mode

__init__(gdf, values, spatial_weights, unique_id, rng=None, mode='all', verbose=True)

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__(gdf, values, spatial_weights, unique_id)

Initialize self.

momepy.Area momepy.CourtyardArea