anscombe#
A reproduction of Anscombe’s Quartet using the low-level bokeh.models
API that also includes HTML content in a Div.
Details
- Sampledata:
- Bokeh APIs:
bokeh.layouts.column,bokeh.layouts.gridplot,bokeh.models.Plot,bokeh.models.LinearAxis- More info:
- Keywords:
column, gridplot
import numpy as np
from bokeh.io import show
from bokeh.layouts import column, gridplot
from bokeh.models import (ColumnDataSource, Div, Grid, Line,
LinearAxis, Plot, Range1d, Scatter)
from bokeh.sampledata.anscombe import data as df
circle_source = ColumnDataSource(data=df)
x = np.linspace(-0.5, 20.5, 10)
y = 3 + 0.5 * x
line_source = ColumnDataSource(data=dict(x=x, y=y))
rng = Range1d(start=-0.5, end=20.5)
def make_plot(title, xname, yname):
plot = Plot(x_range=rng, y_range=rng, width=400, height=400,
background_fill_color='#efefef')
plot.title.text = title
xaxis = LinearAxis(axis_line_color=None)
plot.add_layout(xaxis, 'below')
yaxis = LinearAxis(axis_line_color=None)
plot.add_layout(yaxis, 'left')
plot.add_layout(Grid(dimension=0, ticker=xaxis.ticker))
plot.add_layout(Grid(dimension=1, ticker=yaxis.ticker))
line = Line(x='x', y='y', line_color="#666699", line_width=2)
plot.add_glyph(line_source, line)
circle = Scatter(x=xname, y=yname, size=12, line_color="#cc6633",
fill_color="#cc6633", fill_alpha=0.5)
plot.add_glyph(circle_source, circle)
return plot
#where will this comment show up
I = make_plot('I', 'Ix', 'Iy')
II = make_plot('II', 'IIx', 'IIy')
III = make_plot('III', 'IIIx', 'IIIy')
IV = make_plot('IV', 'IVx', 'IVy')
grid = gridplot([[I, II], [III, IV]], toolbar_location=None)
div = Div(text="""
<h1>Anscombe's Quartet</h1>
<p>Anscombe's Quartet is a collection of four small datasets that have nearly
identical simple descriptive statistics (mean, variance, correlation, and
linear regression lines), yet appear very different when graphed.
</p>
""")
show(column(div, grid, sizing_mode="scale_width"))