Sns.distplot fit

from scipy import stats

ax = sns.distplot(e_t_hat, bins=20, kde=False, fit=stats.norm);
plt.title('Distribution of Cointegrating Spread for Brent and Gasoil')

# Get the fitted parameters used by sns
(mu, sigma) = stats.norm.fit(e_t_hat)
print "mu={0}, sigma={1}".format(mu, sigma)

# Legend and labels 
plt.legend(["normal dist. fit ($\mu=${0:.2g}, $\sigma=${1:.2f})".format(mu, sigma)])
plt.ylabel('Frequency')

# Cross-check this is indeed the case - should be overlaid over black curve
x_dummy = np.linspace(stats.norm.ppf(0.01), stats.norm.ppf(0.99), 100)
ax.plot(x_dummy, stats.norm.pdf(x_dummy, mu, sigma))
plt.legend(["normal dist. fit ($\mu=${0:.2g}, $\sigma=${1:.2f})".format(mu, sigma),
           "cross-check"])

Source: stackoverflow.com

Similar codes

1 vote202 views1 answer
Numpy divide array by scalar
Python
0 vote204 views1 answer
Swap case hackerrank solution
Python
2 votes233 views1 answer
Database default code in settings django
Python Django
1 vote194 views1 answer
Django sessions for beginners
Python
2 votes239 views2 answers
Background image in python
Python
10 votes203 views1 answer
Https://docs.djangoproject.com/en/2.0/howto/static-files/
Python
5 votes253 views6 answers
Plt.xticks
Python
15 votes205 views3 answers
Python get input from console
Python
1 vote221 views1 answer
Lecture de fichier python
Python
-1 vote201 views2 answers
Matrix diagonal sum Python
Python