/Python/Best fit line python log log scale

Best fit line python log log scale

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

8 votes129 views3 answers
Export multiple python pandas dataframe to single excel file
Python
5 votes118 views4 answers
Append to a tuple
Python
8 votes115 views6 answers
Python tutorial
Python
2 votes115 views1 answer
Python recursive function return none
Python
2 votes152 views1 answer
Django get current date
Python Django
15 votes113 views3 answers
Get max value column pandas
Python
1 vote115 views1 answer
Numpy logspace
Python
0 vote135 views1 answer
Pandas group by concat
Python
0 vote128 views1 answer
\n vs \r python
Python
39 votes140 views4 answers
Round down number python
Python