The following code tries to plot multivariate normal distribution using seaborn:
# Set the mean and covariance
mean1 = [0, 0]
mean2 = [2, 0]
cov1 = [[1, .7], [.7, 1]]
cov2 = [[.5, .4], [.4, .5]]
# Generate data from the mean and covariance
data1 = np.random.multivariate_normal(mean1, cov1, size=1000)
data2 = np.random.multivariate_normal(mean2, cov2, size=1000)
plt.figure(figsize=(10,6))
plt.scatter(data1[:,0],data1[:,1])
plt.scatter(data2[:,0],data2[:,1])
sns.kdeplot(data1[:, 0], data1[:, 1], levels=20, linewidth=10, color='k', alpha=0.2)
sns.kdeplot(data2[:, 0], data2[:, 1], levels=20, linewidth=10, color='k', alpha=0.2)
plt.grid(False)
plt.show()
it raises error:
TypeError: kdeplot() takes from 0 to 1 positional arguments but 2 positional arguments (and 2 keyword-only arguments) were given
Kindy advise how can this be achieved?
Best regards
>Solution :
The error tells you exactly what the problem is. Take a look at the function signature in the documentation:
seaborn.kdeplot(data=None, *, x=None, y=None, ...)
data can be passed as kwarg or positional argument, whereas arguments after * are kwargs only. You should therefore specify x= and y=:
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
# Set the mean and covariance
mean1 = [0, 0]
mean2 = [2, 0]
cov1 = [[1, .7], [.7, 1]]
cov2 = [[.5, .4], [.4, .5]]
# Generate data from the mean and covariance
data1 = np.random.multivariate_normal(mean1, cov1, size=1000)
data2 = np.random.multivariate_normal(mean2, cov2, size=1000)
plt.figure(figsize=(10,6))
plt.scatter(data1[:,0],data1[:,1])
plt.scatter(data2[:,0],data2[:,1])
sns.kdeplot(x=data1[:, 0], y=data1[:, 1], levels=20, linewidth=10, color='k', alpha=0.2)
sns.kdeplot(x=data2[:, 0], y=data2[:, 1], levels=20, linewidth=10, color='k', alpha=0.2)
plt.grid(False)
plt.show()