# 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

}

Last modified 1yr ago