example of a corrplot

Links: notebook, html, PDF, python, slides, GitHub

Biokit proposes nice graphs for correlation: corrplot function in Python but it only works with Python 2.7. I took the code out and put a modified version of in pyensae.

%matplotlib inline

import pyensae
import matplotlib.pyplot as plt
plt.style.use('ggplot')

import pandas
import numpy
letters = "ABCDEFGHIJKLM"[0:10]
df = pandas.DataFrame(dict(( (k, numpy.random.random(10)+ord(k)-65) for k in letters)))
df.head()

	A	B	C	D	E	F	G	H	I	J
0	0.887637	1.486102	2.415496	3.781093	4.493253	5.084982	6.484193	7.650366	8.774344	9.898334
1	0.104720	1.779278	2.466874	3.189288	4.148460	5.127938	6.668241	7.770889	8.394404	9.206735
2	0.735222	1.593792	2.734176	3.739522	4.554242	5.513305	6.451066	7.477368	8.063440	9.937340
3	0.505974	1.119941	2.033909	3.945594	4.514602	5.271045	6.764156	7.095581	8.254990	9.599061
4	0.563323	1.001843	2.603700	3.199254	4.968366	5.720844	6.015494	7.629919	8.932106	9.229564

from pyensae.graphhelper import Corrplot

c = Corrplot(df)
c.plot(figsize=(12,6))

Computing correlation

<matplotlib.axes._subplots.AxesSubplot at 0x2149824cac8>

To avoid created another graph container:

fig = plt.figure(num=None, facecolor='white', figsize=(12,6))
ax = plt.subplot(1, 1, 1, aspect='equal', facecolor='white')
c = Corrplot(df)
c.plot(ax=ax)

Computing correlation

<matplotlib.axes._subplots.AxesSubplot at 0x21498a307f0>

<matplotlib.figure.Figure at 0x21498847fd0>

We compare it with seaborn and this example Discovering structure in heatmap data.

import seaborn as sns

cmap = sns.diverging_palette(h_neg=210, h_pos=350, s=90, l=30, as_cmap=True, center="light")
sns.clustermap(df.corr(), figsize=(10, 10), cmap=cmap)

c:python35_x64libsite-packagesmatplotlibcbook.py:137: MatplotlibDeprecationWarning: The axisbg attribute was deprecated in version 2.0. Use facecolor instead.
  warnings.warn(message, mplDeprecation, stacklevel=1)

<seaborn.matrix.ClusterGrid at 0x2149a0db160>