Correlation heatmap

Question

I want to represent correlation matrix using a heatmap. There is something called correlogram in R, but I don't think there's such a thing in Python.

How can I do this? The values go from -1 to 1, for example:

[[ 1.          0.00279981  0.95173379  0.02486161 -0.00324926 -0.00432099]  [ 0.00279981  1.          0.17728303  0.64425774  0.30735071  0.37379443]  [ 0.95173379  0.17728303  1.          0.27072266  0.02549031  0.03324756]  [ 0.02486161  0.64425774  0.27072266  1.          0.18336236  0.18913512]  [-0.00324926  0.30735071  0.02549031  0.18336236  1.          0.77678274]  [-0.00432099  0.37379443  0.03324756  0.18913512  0.77678274  1.        ]] 

I was able to produce the following heatmap based on another question, but the problem is that my values get 'cut' at 0, so I would like to have a map which goes from blue(-1) to red(1), or something like that, but here values below 0 are not presented in an adequate way.

Here's the code for that:

plt.imshow(correlation_matrix,cmap='hot',interpolation='nearest') 

Answer 1

Another alternative is to use the heatmap function in seaborn to plot the covariance. This example uses the Auto data set from the ISLR package in R (the same as in the example you showed).

import pandas.rpy.common as com import seaborn as sns %matplotlib inline  # load the R package ISLR infert = com.importr("ISLR")  # load the Auto dataset auto_df = com.load_data('Auto')  # calculate the correlation matrix corr = auto_df.corr()  # plot the heatmap sns.heatmap(corr,          xticklabels=corr.columns,         yticklabels=corr.columns) 

If you wanted to be even more fancy, you can use Pandas Style, for example:

cmap = cmap=sns.diverging_palette(5, 250, as_cmap=True)  def magnify():     return [dict(selector="th",                  props=[("font-size", "7pt")]),             dict(selector="td",                  props=[('padding', "0em 0em")]),             dict(selector="th:hover",                  props=[("font-size", "12pt")]),             dict(selector="tr:hover td:hover",                  props=[('max-width', '200px'),                         ('font-size', '12pt')]) ]  corr.style.background_gradient(cmap, axis=1)\     .set_properties(**{'max-width': '80px', 'font-size': '10pt'})\     .set_caption("Hover to magify")\     .set_precision(2)\     .set_table_styles(magnify())