Continuous
Binning is the process of classifying a body of data into discrete breakpoints, or bins, to more easily understand and digest the data. Many online maps utilize unclassified scales -- continuous color gradients -- but we prefer and provide tools for a robust set of binning strategies.
You can specify binning strategy and number of bins for each of your variables in map-config.js by setting the binning and numberOfBins parameters. For a more in-depth look at binning strategies, refer to jsGeoDa docs.

Here are the different binning modes available in WebGeoDa:

This non-linear algorithm identifies natural groupings of values that highlight more intuitive breakpoints.
{
// some variable
binning: 'naturalBreaks',
numberOfBins:5, // 3 - 9
}

Quantile breaks create bins based on an equal number of entries in numerical order based on the given number of bins.
{
// some variable
binning: 'quantileBreaks',
numberOfBins:5, // 3 - 9
}

Percentile breaks identify bins at the 1% lowest percentile, 10th percentile, 50th percentile (median), 90th percentile, and 99% highest perceentile.
{
// some variable
binning: 'percentileBreaks'
}

Standard deviations are calculated from your given variable based on .... Standard Deviation breaks fall on less than -2 standard deviations, -1 to -2 standard deviations, 0 to -1 standard deviations, 0 to +1 standard deviations, +1 to +2 standard deviations and greater than +2 standard deviations.
{
// some variable
binning: 'stddev_breaks'
}

15/30
{
// some variable
binning: 'hingeBreaks15' // alternatively 'hingeBreaks30'
}

If you want to provide a custom or fixed binning scale for your data, such as a particular equal interval (eg. 5, 10, 15, 20, 25, etc.), you can provide a fixedScale parameter in your variable:
{
variable: 'Percent Vaccinated',
fixedScale: [20, 30, 40, 50, 60, 70],
colorScale: colors.colorBrewer.Greens
}
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Binning Modes
Natural Breaks
Quantiles
Percentiles
Standard Deviations
Hinge Breaks
Custom, Fixed Scales