How to plot confusion matrix with string axis rather than integer in python

Question

I am following a previous thread on how to plot confusion matrix in Matplotlib. The script is as follows:

from numpy import *
import matplotlib.pyplot as plt         


        

Answer 1

Here is what you want:

from string import ascii_uppercase
from pandas import DataFrame
import numpy as np
import seaborn as sn
from sklearn.metrics import confusion_matrix

y_test = np.array([1,2,3,4,5, 1,2,3,4,5, 1,2,3,4,5])
predic = np.array([1,2,4,3,5, 1,2,4,3,5, 1,2,3,4,4])

columns = ['class %s' %(i) for i in list(ascii_uppercase)[0:len(np.unique(y_test))]]

confm = confusion_matrix(y_test, predic)
df_cm = DataFrame(confm, index=columns, columns=columns)

ax = sn.heatmap(df_cm, cmap='Oranges', annot=True)

Example image output is here:

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If you want a more complete confusion matrix as the matlab default, with totals (last line and last column), and percents on each cell, see this module below.

Because I scoured the internet and didn't find a confusion matrix like this one on python and I developed one with theses improvements and shared on git.

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REF:

https://github.com/wcipriano/pretty-print-confusion-matrix

The output example is here: