splot.esda.plot_moran

splot.esda.plot_moran(moran, zstandard=True, aspect_equal=True, scatter_kwds=None, fitline_kwds=None, **kwargs)[source]

Global Moran’s I simulated reference distribution and scatterplot.

Parameters
moranesda.moran.Moran instance

Values of Moran’s I Global Autocorrelation Statistics

zstandardbool, optional

If True, Moran Scatterplot will show z-standardized attribute and spatial lag values. Default =True.

aspect_equalbool, optional

If True, Axes of Moran Scatterplot will show the same aspect or visual proportions.

scatter_kwdskeyword arguments, optional

Keywords used for creating and designing the scatter points. Default =None.

fitline_kwdskeyword arguments, optional

Keywords used for creating and designing the moran fitline and vertical fitline. Default =None.

**kwargskeyword arguments, optional

Keywords used for creating and designing the figure, passed to seaborne.kdeplot.

Returns
figMatplotlib Figure instance

Moran scatterplot and reference distribution figure

axmatplotlib Axes instance

Axes in which the figure is plotted

Examples

Imports

>>> import matplotlib.pyplot as plt
>>> from libpysal.weights.contiguity import Queen
>>> from libpysal import examples
>>> import geopandas as gpd
>>> from esda.moran import Moran
>>> from splot.esda import plot_moran

Load data and calculate weights

>>> link_to_data = examples.get_path('Guerry.shp')
>>> gdf = gpd.read_file(link_to_data)
>>> y = gdf['Donatns'].values
>>> w = Queen.from_dataframe(gdf)
>>> w.transform = 'r'

Calculate Global Moran

>>> moran = Moran(y, w)

plot

>>> plot_moran(moran)
>>> plt.show()

customize plot

>>> plot_moran(moran, zstandard=False,
...            fitline_kwds=dict(color='#4393c3'))
>>> plt.show()

(Source code)