Quantitative Scales

Scales are functions that map from an input domain to an output range. Quantitative scales have a continuous domain, such as the set of real numbers, or dates. There are also ordinal scales, which have a discrete domain, such as a set of names or categories. Scales are an optional feature in D3; you don't have to use them, if you prefer to do the math yourself. However, using scales can greatly simplify the code needed to map a dimension of data to a visual representation.

Linear Scales

# d3.scale.linear()

# linear.invert(y)

# linear.domain([values])

# linear.range([values])

# linear.rangeRound(values)

# linear.interpolate([interpolator])

# linear.clamp([boolean])

# linear.ticks([count])

# linear.tickFormat([count])

Power Scales

# d3.scale.sqrt()

# d3.scale.pow()

# pow.invert(y)

# pow.domain([values])

# pow.range([values])

# pow.rangeRound(values)

# pow.interpolate([interpolator])

# pow.clamp([boolean])

# pow.ticks([count])

# pow.tickFormat([count])

Log Scales

# d3.scale.log()

# log.invert(y)

# log.domain([values])

# log.range([values])

# log.rangeRound(values)

# log.interpolate([interpolator])

# log.clamp([boolean])

# log.ticks()

# log.tickFormat()

Quantize Scales

# d3.scale.quantize()

# quantize.domain([values])

# quantize.range([values])

Quantile Scales

# d3.scale.quantile()

# quantile.domain([values])

# quantile.range([values])

# quantile.quantiles()