/Python/Logarithmic scale fitting python

Logarithmic scale fitting python

fig=plt.figure()
ax = fig.add_subplot(111)

z=np.arange(1, len(x)+1) #start at 1, to avoid error from log(0)

logA = np.log(z) #no need for list comprehension since all z values >= 1
logB = np.log(y)

m, c = np.polyfit(logA, logB, 1, w=np.sqrt(y)) # fit log(y) = m*log(x) + c
y_fit = np.exp(m*logA + c) # calculate the fitted values of y 

plt.plot(z, y, color = 'r')
plt.plot(z, y_fit, ':')

ax.set_yscale('symlog')
ax.set_xscale('symlog')
#slope, intercept = np.polyfit(logA, logB, 1)
plt.xlabel("Pre_referer")
plt.ylabel("Popularity")
ax.set_title('Pre Referral URL Popularity distribution')
plt.show()

Source: stackoverflow.com

Similar codes

105 votes124 views2 answers
Create react-app
Python
3 votes125 views1 answer
Python loop back to start
Python
1 vote129 views1 answer
Vector in python
Python
1 vote113 views1 answer
How to make a pythoon turtle follow another?
Python
-1 vote122 views1 answer
How to add a linebreak in python
Python
24 votes183 views3 answers
Ignore warnings python
Python
0 vote125 views1 answer
Df.fillna("tagline",inplace=True) in jupyter notebook
Python
0 vote109 views1 answer
Aggregate on the entire DataFrame without group
Python
0 vote135 views1 answer
Python numpy kurtosis
Python
0 vote129 views2 answers
Django admin image
Python