geosnap.data.Community.cluster_spatial¶
-
Community.
cluster_spatial
(self, n_clusters=6, spatial_weights='rook', method=None, best_model=False, columns=None, threshold_variable='count', threshold=10, return_model=False, scaler=None, **kwargs)[source]¶ Create a spatial geodemographic typology by running a cluster analysis on the metro area’s neighborhood attributes and including a contiguity constraint.
- Parameters
- gdfgeopandas.GeoDataFrame
long-form geodataframe holding neighborhood attribute and geometry data.
- n_clustersint
the number of clusters to model. The default is 6).
- weights_typestr ‘queen’ or ‘rook’
spatial weights matrix specification` (the default is “rook”).
- methodstr
the clustering algorithm used to identify neighborhood types
- best_modeltype
Description of parameter best_model (the default is False).
- columnslist-like
subset of columns on which to apply the clustering
- threshold_variablestr
for max-p, which variable should define p. The default is “count”, which will grow regions until the threshold number of polygons have been aggregated
- thresholdnumeric
threshold to use for max-p clustering (the default is 10).
- return_modelbool
whether to return the underlying cluster model instance for further analysis
- scaler: str or sklearn.preprocessing.Scaler
a scikit-learn preprocessing class that will be used to rescale the data. Defaults to StandardScaler
- Returns
- geopandas.GeoDataFrame with a column of neighborhood cluster labels
- appended as a new column. Will overwrite columns of the same name.