iris_splom.py

A scatter plot matrix (SPLOM) chart using Fisher’s Iris dataset. This example demonstrates sharing ranged between plots to acheive linked panning.

Note

This example is maintained for historical compatibility. Please consider alternatives to Iris, such as penguins.

Details

Sampledata

bokeh.sampledata.iris

Bokeh APIs

bokeh.models.Circle, bokeh.models.ColumnDataSource, bokeh.models.Plot, bokeh.models.LinearAxis, bokeh.models.Plot, bokeh.models.DataRange1d

More info

Linking behavior > Linked panning

Keywords

models, scatter, splom

from bokeh.document import Document
from bokeh.embed import file_html
from bokeh.layouts import gridplot
from bokeh.models import (BasicTicker, Circle, ColumnDataSource, DataRange1d,
                          Grid, LinearAxis, PanTool, Plot, WheelZoomTool)
from bokeh.resources import INLINE
from bokeh.sampledata.iris import flowers
from bokeh.util.browser import view

colormap = {'setosa': 'red', 'versicolor': 'green', 'virginica': 'blue'}

flowers['color'] = flowers['species'].map(lambda x: colormap[x])


source = ColumnDataSource(
    data=dict(
        petal_length=flowers['petal_length'],
        petal_width=flowers['petal_width'],
        sepal_length=flowers['sepal_length'],
        sepal_width=flowers['sepal_width'],
        color=flowers['color']
    )
)

xdr = DataRange1d(bounds=None)
ydr = DataRange1d(bounds=None)

def make_plot(xname, yname, xax=False, yax=False):
    mbl = 40 if yax else 0
    mbb = 40 if xax else 0
    plot = Plot(
        x_range=xdr, y_range=ydr, background_fill_color="#efe8e2",
        border_fill_color='white', width=200 + mbl, height=200 + mbb,
        min_border_left=2+mbl, min_border_right=2, min_border_top=2, min_border_bottom=2+mbb)

    circle = Circle(x=xname, y=yname, fill_color="color", fill_alpha=0.2, size=4, line_color="color")
    r = plot.add_glyph(source, circle)

    xdr.renderers.append(r)
    ydr.renderers.append(r)

    xticker = BasicTicker()
    if xax:
        xaxis = LinearAxis()
        xaxis.axis_label = xname
        plot.add_layout(xaxis, 'below')
        xticker = xaxis.ticker
    plot.add_layout(Grid(dimension=0, ticker=xticker))

    yticker = BasicTicker()
    if yax:
        yaxis = LinearAxis()
        yaxis.axis_label = yname
        yaxis.major_label_orientation = 'vertical'
        plot.add_layout(yaxis, 'left')
        yticker = yaxis.ticker
    plot.add_layout(Grid(dimension=1, ticker=yticker))

    plot.add_tools(PanTool(), WheelZoomTool())

    return plot

xattrs = ["petal_length", "petal_width", "sepal_width", "sepal_length"]
yattrs = list(reversed(xattrs))
plots = []

for y in yattrs:
    row = []
    for x in xattrs:
        xax = (y == yattrs[-1])
        yax = (x == xattrs[0])
        plot = make_plot(x, y, xax, yax)
        row.append(plot)
    plots.append(row)

grid = gridplot(plots)

doc = Document()
doc.add_root(grid)

if __name__ == "__main__":
    doc.validate()
    filename = "iris_splom.html"
    with open(filename, "w") as f:
        f.write(file_html(doc, INLINE, "Iris Data SPLOM"))
    print("Wrote %s" % filename)
    view(filename)