example of a corrplotΒΆ

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)))
```
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>
```