2D Histograms in Julia

How to make 2D Histograms in Julia with Plotly.

Plotly is known for its graphing libraries, but it's also a broader ecosystem for building interactive data apps, AI data analysis tools, and deploying and hosting Dash apps. Explore the full set of tools and platforms designed to help turn data into action. Discover Plotly.

Note: We are retiring documentation for R, MATLAB, Julia, and F#. Learn more about this change here.

2D Histograms or Density Heatmaps

A 2D histogram, also known as a density heatmap, is the 2-dimensional generalization of a histogram which resembles a heatmap but is computed by grouping a set of points specified by their x and y coordinates into bins, and applying an aggregation function such as count or sum (if z is provided) to compute the color of the tile representing the bin. This kind of visualization (and the related 2D histogram contour, or density contour) is often used to manage over-plotting, or situations where showing large data sets as scatter plots would result in points overlapping each other and hiding patterns.

Density Heatmaps

You can make a density heatmap using the histogram2d trace type and setting xbingroup="x" and ybingroup="y"

using PlotlyJS, CSV, DataFrames
df = dataset(DataFrame, "tips")
plot(df, x=:total_bill, y=:tip, xbingroyp="x", ybingroup="y", kind="histogram2d")

The number of bins can be controlled with nbinsx and nbinsy and the color scale with colorscale.

using PlotlyJS, CSV, DataFrames
df = dataset(DataFrame, "tips")
plot(
    df, x=:total_bill, y=:tip, xbingroyp="x", ybingroup="y", kind="histogram2d",
    nbinsx=20, nbinsy=20, colorscale="Viridis"
)

Density heatmaps can also be faceted:

using PlotlyJS, CSV, DataFrames
df = dataset(DataFrame, "tips")

plot(
    df, x=:total_bill, y=:tip, xbingroyp="x", ybingroup="y", kind="histogram2d",
    facet_row=:sex, facet_col=:smoker
)

2D Histogram of a Bivariate Normal Distribution

using PlotlyJS, Random
Random.seed!(41)
plot(histogram2d(x=randn(500), y=randn(500) .+ 1))

2D Histogram Overlaid with a Scatter Chart

using PlotlyJS, Random

x0 = randn(100) ./ 5. .+ 0.5  # 5. enforces float division
y0 = randn(100) ./ 5. .+ 0.5
x1 = rand(50)
y1 = rand(50) .+ 1.0

x = [x0; x1]
y = [y0; y1]

plot(
    [
        scatter(
            x=x0, y=y0, mode="markers",
            marker=attr(symbol="x", opacity=0.7, color="white", size=8, line_width=1)
        ),
        scatter(
            x=x1, y=y1, mode="markers",
            marker=attr(symbol="circle", opacity=0.7, color="white", size=8, line_width=1)
        ),
        histogram2d(x=x, y=y, colorscale="YlGnBu", zmax=10, nbinsx=14, nbinsy=14, zauto=false)
    ],
    Layout(
        xaxis=attr(ticks="", showgrid=false, zeroline=false, nticks=20),
        yaxis=attr(ticks="", showgrid=false, zeroline=false, nticks=20),
        autosize=false,
        height=550,
        width=550,
        hovermode="closest",
        showlegend=false,
    )
)

Reference

See https://plotly.com/julia/reference/histogram2d/ for more information and chart attribute options!