stephist ​

# Makie.stephistFunction.
julia
``stephist(values)``

Plot a step histogram of `values`.

Plot type

The plot type alias for the `stephist` function is `StepHist`.

source

Examples ​

julia
``````using GLMakie
data = randn(1000)

f = Figure()
stephist(f[1, 1], data, bins = 10)
stephist(f[1, 2], data, bins = 20, color = :red, linewidth = 3)
stephist(f[2, 1], data, bins = [-5, -2, -1, 0, 1, 2, 5], color = :gray)
stephist(f[2, 2], data, normalization = :pdf)
f``````

For more examples, see `hist`.

Attributes ​

bins ​

Defaults to `15`

Can be an `Int` to create that number of equal-width bins over the range of `values`. Alternatively, it can be a sorted iterable of bin edges.

color ​

Defaults to `@inherit patchcolor`

No docs available.

cycle ​

Defaults to `[:color => :patchcolor]`

No docs available.

linestyle ​

Defaults to `:solid`

No docs available.

linewidth ​

Defaults to `@inherit linewidth`

No docs available.

normalization ​

Defaults to `:none`

Allows to apply a normalization to the histogram. Possible values are:

• `:pdf`: Normalize by sum of weights and bin sizes. Resulting histogram

has norm 1 and represents a PDF.

• `:density`: Normalize by bin sizes only. Resulting histogram represents

count density of input and does not have norm 1. Will not modify the histogram if it already represents a density (`h.isdensity == 1`).

• `:probability`: Normalize by sum of weights only. Resulting histogram

represents the fraction of probability mass for each bin and does not have norm 1.

• `:none`: Do not normalize.

scale_to ​

Defaults to `nothing`

Allows to scale all values to a certain height.

weights ​

Defaults to `automatic`

Allows to provide statistical weights.