Distribution plot python

Plot distribution seaborn

x = np.random.normal(size=100)
sns.distplot(x);

Source: seaborn.pydata.org

Plot normal distribution python

import matplotlib.pyplot as plt
import numpy as np
import scipy.stats as stats
import math

mu = 0
variance = 1
sigma = math.sqrt(variance)
x = np.linspace(mu - 3 * sigma, mu + 3 * sigma, 100)
plt.plot(x, stats.norm.pdf(x, mu, sigma))
plt.show()

Source: stackoverflow.com

Distribution plot python

sns.distplot(df['Rating'], hist=True, kde=True, 
             bins=int(15), color = 'darkblue', 
             hist_kws={'edgecolor':'black'},
             kde_kws={'linewidth': 4})

Mean =[0,0] covariance = [[1,0],[0,100]] ds = np.random.multivariate_normal(mean,covariance,500) dframe = pd.DataFrame(ds, columns=['col1', 'col2']) fig = sns.kdeplot(dframe).get_figure() fig.savefig('kde1.png')

mean =[0,0]
covariance = [[1,0],[0,100]]

ds = np.random.multivariate_normal(mean,covariance,500)

dframe = pd.DataFrame(ds, columns=['col1', 'col2'])

fig = sns.kdeplot(dframe).get_figure()
fig.savefig('kde1.png')

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