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

2 votes263 views1 answer
Django empty queryset
Python Django
-1 vote139 views2 answers
Mro in python
Python
1 vote143 views1 answer
Django reverse queryset
Python
0 vote138 views1 answer
Python set workdir
Python
0 vote146 views4 answers
Boxplot python
Python
0 vote165 views1 answer
Python requests token x-www-form-urlencoded
Python
32 votes145 views6 answers
Add to list python
Python
0 vote204 views1 answer
Connect spark to postgres; connect spark to database
Python
2 votes142 views4 answers
ValueError: Input contains NaN, infinity or a value too large for dtype('float32'). site:stackoverflow.com
Python
0 vote173 views1 answer
Python flask models user
Python Flask