momepy.Range

class momepy.Range(gdf, values, spatial_weights, unique_id, rng=0, 100, **kwargs)[source]

Calculates the range of values within neighbours defined in spatial_weights.

Uses scipy.stats.iqr under the hood.

Adapted from [DPR+17].

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.

spatial_weightslibpysal.weights

spatial weights matrix

unique_idstr

name of the column with unique id used as spatial_weights index

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.

**kwargskeyword arguments

optional arguments for scipy.stats.iqr

Examples

>>> sw = momepy.sw_high(k=3, gdf=tessellation_df, ids='uID')
>>> tessellation_df['area_IQR_3steps'] = mm.Range(tessellation_df, 'area', sw, 'uID', rng=(25, 75)).series
100%|██████████| 144/144 [00:00<00:00, 722.50it/s]
Attributes
seriesSeries

Series containing resulting values

gdfGeoDataFrame

original GeoDataFrame

valuesSeries

Series containing used values

swlibpysal.weights

spatial weights matrix

idSeries

Series containing used unique ID

rngtuple

range

kwargsdict

kwargs

__init__(self, gdf, values, spatial_weights, unique_id, rng=0, 100, **kwargs)[source]

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

Methods

__init__(self, gdf, values, spatial_weights, …)

Initialize self.