matplotlib: using a colormap to color table-cell background

Question

I have a Pandas dataframe, and i want to plot it as matplotlib table. So far i have that part working with following code:

import numpy as np
randn = np.rand         


        

Answer 1

The Andy's code working:

#!/usr/bin/env python
# -*- coding: utf-8 -*-

# sudo apt-get install python-pandas
# sudo apt-get install python-matplotlib
# 
# python teste.py

from matplotlib import pyplot
from matplotlib import cm

import numpy

from pandas import *

idx = Index(numpy.arange(1, 11))

df = DataFrame(
        numpy.random.randn(10, 5),
        index=idx,
        columns=['A', 'B', 'C', 'D', 'E']
    )

vals = numpy.around(df.values, 2)

normal = pyplot.normalize(vals.min()-1, vals.max()+1)

fig = pyplot.figure(figsize=(15, 8))

ax = fig.add_subplot(111, frameon=True, xticks=[], yticks=[])

the_table = pyplot.table(
                cellText=vals,
                rowLabels=df.index,
                colLabels=df.columns, 
                colWidths = [0.03]*vals.shape[1],
                loc='center', 
                cellColours=pyplot.cm.hot(normal(vals))
            )

pyplot.show()

Answer 2

You can use plt.Normalize() to normalize your data, and the pass the normalized data to a Colormap object, for example plt.cm.hot().

plt.table() has an argument cellColours, which will be used to set the cells' background color accordingly.

Because cm.hot maps black to the minimal value, I increased the value range when creating the normalization object.

Here is the code:

from matplotlib import pyplot as plt
import numpy as np
randn = np.random.randn
from pandas import *

idx = Index(np.arange(1,11))
df = DataFrame(randn(10, 5), index=idx, columns=['A', 'B', 'C', 'D', 'E'])
vals = np.around(df.values,2)
norm = plt.Normalize(vals.min()-1, vals.max()+1)
colours = plt.cm.hot(normal(vals))

fig = plt.figure(figsize=(15,8))
ax = fig.add_subplot(111, frameon=True, xticks=[], yticks=[])

the_table=plt.table(cellText=vals, rowLabels=df.index, colLabels=df.columns, 
                    colWidths = [0.03]*vals.shape[1], loc='center', 
                    cellColours=colours)
plt.show()