Plotting a bi-coloured feature space with Support Vector Machine in python

Question

After fitting a 2-class random-generated dataset with linear SVM this way:

np.random.seed(5)
X = np.random.randn(20,2)
y = np.repeat([1,-1], 10)
X[y == -1] = X[y == -1]+1

from sklearn.svm import SVC
svc = SVC(C=1, kernel='linear')
svc.fit(X, y)

I'd try to plot a convenient, nice and bicoloured feature space plot this way:

plot_svc(svc, X, y) 

where the plot_svc function is defined this way:

import pandas as pd
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt

%matplotlib inline

def plot_svc(svc, X, y, h=0.02, pad=0.25):
    x_min, x_max = X[:, 0].min()-pad, X[:, 0].max()+pad
    y_min, y_max = X[:, 1].min()-pad, X[:, 1].max()+pad
    xx, yy = np.meshgrid(np.arange(x_min, x_max, h), np.arange(y_min, y_max, h))
    Z = svc.predict(np.c_[xx.ravel(), yy.ravel()])
    Z = Z.reshape(xx.shape)
    plt.contourf(xx, yy, Z, cmap=plt.cm.Paired, alpha=0.2)

    plt.scatter(X[:,0], X[:,1], s=70, c=y, cmap=mpl.cm.Paired)
    # Support vectors indicated in plot by vertical lines
    sv = svc.support_vectors_
    plt.scatter(sv[:,0], sv[:,1], c='k', marker='x', s=100, linewidths='1')
    plt.xlim(x_min, x_max)
    plt.ylim(y_min, y_max)
    plt.xlabel('X1')
    plt.ylabel('X2')
    plt.show()
    print('Number of support vectors: ', svc.support_.size)

I get the following error:

TypeError: must be real number, not str

What does it mean? Many thanks indeed.