Class mismatch in skplt.plot_confusion_matrix when test has fewer classes than training about scikit-plot HOT 4 CLOSED

from sklearn.datasets import load_digits
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
from scikitplot import plotters as skplt
import pandas as pd
digits = load_digits()
%matplotlib inline

X = digits.data
y = digits.target
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=42)
test = pd.DataFrame(X_test)
test['target'] = y_test

test_reduced = test.ix[test.target!=0,:]
X_test_reduced = test_reduced.drop('target',axis=1)
y_test_reduced = test_reduced.target
print(set(y_test_reduced)) # we removed 0 from test set. 
lr = LogisticRegression(tol=5) # i set high tolerance so that the classifier sitll predicts some 0's
lr.fit(X_train,y_train)


y_pred  = lr.predict(X_test_reduced)
skplt.plot_confusion_matrix(y_test_reduced, y_pred)