anscombe.py

Anscombe's Quartet

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.

import numpy as np
import pandas as pd

from bokeh.document import Document
from bokeh.embed import file_html
from bokeh.layouts import column, gridplot
from bokeh.models import (Circle, ColumnDataSource, Div, Grid,
                          Line, LinearAxis, Plot, Range1d,)
from bokeh.resources import INLINE
from bokeh.util.browser import view

raw_columns=[
[10.0,   8.04,   10.0,   9.14,   10.0,   7.46,   8.0,    6.58],
[8.0,    6.95,   8.0,    8.14,   8.0,    6.77,   8.0,    5.76],
[13.0,   7.58,   13.0,   8.74,   13.0,   12.74,  8.0,    7.71],
[9.0,    8.81,   9.0,    8.77,   9.0,    7.11,   8.0,    8.84],
[11.0,   8.33,   11.0,   9.26,   11.0,   7.81,   8.0,    8.47],
[14.0,   9.96,   14.0,   8.10,   14.0,   8.84,   8.0,    7.04],
[6.0,    7.24,   6.0,    6.13,   6.0,    6.08,   8.0,    5.25],
[4.0,    4.26,   4.0,    3.10,   4.0,    5.39,   19.0,   12.5],
[12.0,   10.84,  12.0,   9.13,   12.0,   8.15,   8.0,    5.56],
[7.0,    4.82,   7.0,    7.26,   7.0,    6.42,   8.0,    7.91],
[5.0,    5.68,   5.0,    4.74,   5.0,    5.73,   8.0,    6.89]]

quartet = pd.DataFrame(data=raw_columns, columns=
                       ['Ix','Iy','IIx','IIy','IIIx','IIIy','IVx','IVy'])


circles_source = ColumnDataSource(
    data = dict(
        xi   = quartet['Ix'],
        yi   = quartet['Iy'],
        xii  = quartet['IIx'],
        yii  = quartet['IIy'],
        xiii = quartet['IIIx'],
        yiii = quartet['IIIy'],
        xiv  = quartet['IVx'],
        yiv  = quartet['IVy'],
    )
   )

x = np.linspace(-0.5, 20.5, 10)
y = 3 + 0.5 * x
lines_source = ColumnDataSource(data=dict(x=x, y=y))

xdr = Range1d(start=-0.5, end=20.5)
ydr = Range1d(start=-0.5, end=20.5)

def make_plot(title, xname, yname):
    plot = Plot(x_range=xdr, y_range=ydr, plot_width=400, plot_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(lines_source, line)

    circle = Circle(
        x=xname, y=yname, size=12,
        fill_color="#cc6633", line_color="#cc6633", fill_alpha=0.5
    )
    plot.add_glyph(circles_source, circle)

    return plot

#where will this comment show up
I   = make_plot('I',   'xi',   'yi')
II  = make_plot('II',  'xii',  'yii')
III = make_plot('III', 'xiii', 'yiii')
IV  = make_plot('IV',  'xiv',  'yiv')

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>
""")

doc = Document()
doc.add_root(column(div, grid, sizing_mode="scale_width"))

if __name__ == "__main__":
    doc.validate()
    filename = "anscombe.html"
    with open(filename, "w") as f:
        f.write(file_html(doc, INLINE, "Anscombe's Quartet"))
    print("Wrote %s" % filename)
    view(filename)