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.
GeoDataFrame containing morphological tessellation
the name of the dataframe column, np.array, or pd.Series where is stored character value.
spatial weights matrix
name of the column with unique id used as spatial_weights index
Percentiles over which to compute the range. Each must be between 0 and 100, inclusive. The order of the elements is not important.
optional arguments for scipy.stats.iqr
References
Dibble J, Prelorendjos A, Romice O, et al. (2017) On the origin of spaces: Morphometric foundations of urban form evolution. Environment and Planning B: Urban Analytics and City Science 46(4): 707–730.
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
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Series containing resulting values
original GeoDataFrame
Series containing used values
spatial weights matrix
Series containing used unique ID
range
kwargs
__init__
(self, gdf, values, spatial_weights, unique_id, rng=(0, 100), \*\*kwargs)[source]¶Initialize self. See help(type(self)) for accurate signature.
Methods
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Initialize self. |