momepy.BlocksCount#

class momepy.BlocksCount(gdf, block_id, spatial_weights, unique_id, weighted=True, verbose=True)[source]#

Calculates the weighted number of blocks. The number of blocks within neighbours defined in spatial_weights divided by the area covered by the neighbours.

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Adapted from [Dibble et al., 2017].

Parameters
gdfGeoDataFrame

A GeoDataFrame containing morphological tessellation.

block_idstr, list, np.array, pd.Series
The name of the objects dataframe column, np.array,

or pd.Series where block IDs are stored.

spatial_weightslibpysal.weights

A spatial weights matrix.

unique_idstr

The name of the column with a unique ID used as the spatial_weights index.

weigtedbool, default True

Return value weighted by the analysed area (True) or pure count (False).

verbosebool (default True)

If True, shows progress bars in loops and indication of steps.

Examples

>>> sw4 = mm.sw_high(k=4, gdf='tessellation_df', ids='uID')
>>> tessellation_df['blocks_within_4'] = mm.BlocksCount(tessellation_df,
...                                                     'bID',
...                                                     sw4,
...                                                     'uID').series
Attributes
seriesSeries

A Series containing resulting values.

gdfGeoDataFrame

The original GeoDataFrame.

block_idSeries

A Series containing used block ID.

swlibpysal.weights

The spatial weights matrix

idSeries

A Series containing used unique ID.

weightedbool

True if the weighted value was used.

__init__(gdf, block_id, spatial_weights, unique_id, weighted=True, verbose=True)[source]#

Methods

__init__(gdf, block_id, spatial_weights, ...)