API reference


mapclassify.BoxPlot(y[, hinge])

BoxPlot Map Classification.

mapclassify.EqualInterval(y[, k])

Equal Interval Classification.

mapclassify.FisherJenks(y[, k])

Fisher Jenks optimal classifier - mean based.

mapclassify.FisherJenksSampled(y[, k, pct, ...])

Fisher Jenks optimal classifier - mean based using random sample.

mapclassify.greedy(gdf[, strategy, balance, ...])

Color GeoDataFrame using various strategies of greedy (topological) colouring.


Head/tail Breaks Map Classification for Heavy-tailed Distributions.

mapclassify.JenksCaspall(y[, k])

Jenks Caspall Map Classification.

mapclassify.JenksCaspallForced(y[, k])

Jenks Caspall Map Classification with forced movements.

mapclassify.JenksCaspallSampled(y[, k, pct])

Jenks Caspall Map Classification using a random sample.

mapclassify.MaxP(y[, k, initial, seed1, seed2])

MaxP Map Classification.

mapclassify.MaximumBreaks(y[, k, mindiff])

Maximum Breaks Map Classification.

mapclassify.NaturalBreaks(y[, k, initial])

Natural Breaks Map Classification.

mapclassify.Percentiles(y[, pct])

Percentiles Map Classification

mapclassify.PrettyBreaks(y[, k])

mapclassify.Quantiles(y[, k])

Quantile Map Classification.

mapclassify.StdMean(y[, multiples, anchor])

Standard Deviation and Mean Map Classification.

mapclassify.UserDefined(y, bins[, lowest])

User Specified Binning.


mapclassify.KClassifiers(y[, pct])

Evaluate all \(k\)-classifers and pick optimal based on \(k\) and GADF.

mapclassify.Pooled(Y[, classifier])

Applying global binning across columns.

mapclassify.classify(y, scheme[, k, pct, ...])

Classify your data with mapclassify.classify.

mapclassify.gadf(y[, method, maxk, pct])

Evaluate the Goodness of Absolute Deviation Fit (GADF) of a classifier and find the minimum value of \(k\) for which gadf > pct.