splom

使用 Palmer 企鹅数据集 的散点矩阵 (SPLOM) 图。此示例演示了在绘图之间共享范围以实现链接平移。

详细信息

示例数据:

bokeh.sampledata.penguins

Bokeh API:

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

更多信息:

SPLOM

关键词:

模型、散点图、splom

from itertools import product

from bokeh.io import show
from bokeh.layouts import gridplot
from bokeh.models import (BasicTicker, ColumnDataSource, DataRange1d,
                          Grid, LassoSelectTool, LinearAxis, PanTool,
                          Plot, ResetTool, Scatter, WheelZoomTool)
from bokeh.sampledata.penguins import data
from bokeh.transform import factor_cmap

df = data.copy()
df["body_mass_kg"] = df["body_mass_g"] / 1000

SPECIES = sorted(df.species.unique())
ATTRS = ("bill_length_mm", "bill_depth_mm", "body_mass_kg")
N = len(ATTRS)

source = ColumnDataSource(data=df)

xdrs = [DataRange1d(bounds=None) for _ in range(N)]
ydrs = [DataRange1d(bounds=None) for _ in range(N)]

plots = []

for i, (y, x) in enumerate(product(ATTRS, reversed(ATTRS))):
    p = Plot(x_range=xdrs[i%N], y_range=ydrs[i//N],
             background_fill_color="#fafafa",
             border_fill_color="white", width=200, height=200, min_border=5)

    if i % N == 0:  # first column
        p.min_border_left = p.min_border + 4
        p.width += 40
        yaxis = LinearAxis(axis_label=y)
        yaxis.major_label_orientation = "vertical"
        p.add_layout(yaxis, "left")
        yticker = yaxis.ticker
    else:
        yticker = BasicTicker()
    p.add_layout(Grid(dimension=1, ticker=yticker))

    if i >= N*(N-1):  # last row
        p.min_border_bottom = p.min_border + 40
        p.height += 40
        xaxis = LinearAxis(axis_label=x)
        p.add_layout(xaxis, "below")
        xticker = xaxis.ticker
    else:
        xticker = BasicTicker()
    p.add_layout(Grid(dimension=0, ticker=xticker))

    scatter = Scatter(x=x, y=y, fill_alpha=0.6, size=5, line_color=None,
                      fill_color=factor_cmap('species', 'Category10_3', SPECIES))
    r = p.add_glyph(source, scatter)
    p.x_range.renderers.append(r)
    p.y_range.renderers.append(r)

    # suppress the diagonal
    if (i%N) + (i//N) == N-1:
        r.visible = False
        p.grid.grid_line_color = None

    p.add_tools(PanTool(), WheelZoomTool(), ResetTool(), LassoSelectTool())

    plots.append(p)

show(gridplot(plots, ncols=N))