Fit a gaussian function

Question

I have a histogram (see below) and I am trying to find the mean and standard deviation along with code which fits a curve to my histogram. I think there is something in SciP

Answer 1

I am not sure what your input is, but possibly your y-axis scale is too large (20000), try reducing this number. The following code works for me:

import matplotlib.pyplot as plt
import numpy as np

#created my variable
v = np.random.normal(0,1,1000)


fig, ax = plt.subplots()


plt.hist(v, bins=500, normed=1, color='#7F38EC', histtype='step')

#plot
plt.title("Gaussian")
plt.axis([-1, 2, 0, 1]) #changed 20000 to 1

plt.show()

Edit:

If you want the actual count of values on y-axis, you can set normed=0. And would just get rid of the plt.axis([-1, 2, 0, 1]).

import matplotlib.pyplot as plt
import numpy as np

#function
v = np.random.normal(0,1,500000)


fig, ax = plt.subplots()

# changed normed=1 to normed=0
plt.hist(v, bins=500, normed=0, color='#7F38EC', histtype='step')

#plot
plt.title("Gaussian")
#plt.axis([-1, 2, 0, 20000]) 

plt.show()