mapclassify.JenksCaspall

class mapclassify.JenksCaspall(y, k=5)

Jenks Caspall Map Classification.

Parameters:

ynumpy.array

\((n,1)\), values to classify.

kint (default 5)

The number of classes required.

Attributes:

ybnumpy.array

\((n,1)\), bin IDs for observations.

binsnumpy.array

\((k,1)\), the upper bounds of each class.

kint

The number of classes.

countsnumpy.array

\((k,1)\), the number of observations falling in each class.

Examples

>>> import mapclassify
>>> cal = mapclassify.load_example()
>>> jc = mapclassify.JenksCaspall(cal, k=5)
>>> jc.bins
array([1.81000e+00, 7.60000e+00, 2.98200e+01, 1.81270e+02, 4.11145e+03])

>>> jc.counts.tolist()
[14, 13, 14, 10, 7]

__init__(y, k=5)

Methods

__init__(y[, k])
find_bin(x)	Sort input or inputs according to the current bin estimate.
get_adcm()	Absolute deviation around class median (ADCM).
get_fmt()
get_gadf()	Goodness of absolute deviation of fit.
get_legend_classes([fmt])	Format the strings for the classes on the legend.
get_tss()	Returns sum of squares over all class means.
make(*args, **kwargs)	Configure and create a classifier that will consume data and produce classifications, given the configuration options specified by this function.
plot(gdf[, border_color, border_width, ...])	Plot a mapclassifier object.
plot_histogram([color, linecolor, ...])	Plot histogram of y with bin values superimposed
set_fmt(fmt)
table()
update([y, inplace])	Add data or change classification parameters.

Attributes

fmt