Python: Visualize a normal curve on data's histogram

Question

Thanks in advance for any assistance or tips.

I'm trying to visualize the fitted normal to one of my dataframe's column. So far, I've been able to plot the histogram by:

df.radon_adj.hist(bins=30)

I've this 'template', but I encounter errors.

import pylab as py
import numpy as np
from scipy import optimize

# Generate a 
y = df.radon_adj
data = py.hist(y, bins = 25)

# Equation for Gaussian
def f(x, a, b, c):
    return a * py.exp(-(x - b)**2.0 / (2 * c**2))

# Generate data from bins as a set of points 
x = [0.5 * (data[1][i] + data[1][i+1]) for i in xrange(len(data[1])-1)]
y = data[0]

popt, pcov = optimize.curve_fit(f, x, y)

x_fit = py.linspace(x[0], x[-1], 100)
y_fit = f(x_fit, *popt)

plot(x_fit, y_fit, lw=4, color="r")

Answer 1

I wouldn't reinvent the wheel by defining the equation for Gaussian. Stand on the shoulders of the scipy package:

from scipy.stats import norm  
df = pd.DataFrame({'A': np.random.normal(size=100)})

df.A.plot(kind='hist', normed=True)

range = np.arange(-4, 4, 0.001)
plt.plot(range, norm.pdf(range,0,1))

Note that the only 'magic' here is making sure the histogram is normed.