Un-normalized Gaussian curve on histogram

Question

I have data which is of the gaussian form when plotted as histogram. I want to plot a gaussian curve on top of the histogram to see how good the data is. I am using pyplot f

Answer 1

An old post I know, but wanted to contribute my code for doing this, which simply does the 'fix by area' trick:

from scipy.stats import norm
from numpy import linspace
from pylab import plot,show,hist

def PlotHistNorm(data, log=False):
    # distribution fitting
    param = norm.fit(data) 
    mean = param[0]
    sd = param[1]

    #Set large limits
    xlims = [-6*sd+mean, 6*sd+mean]

    #Plot histogram
    histdata = hist(data,bins=12,alpha=.3,log=log)

    #Generate X points
    x = linspace(xlims[0],xlims[1],500)

    #Get Y points via Normal PDF with fitted parameters
    pdf_fitted = norm.pdf(x,loc=mean,scale=sd)

    #Get histogram data, in this case bin edges
    xh = [0.5 * (histdata[1][r] + histdata[1][r+1]) for r in xrange(len(histdata[1])-1)]

    #Get bin width from this
    binwidth = (max(xh) - min(xh)) / len(histdata[1])           

    #Scale the fitted PDF by area of the histogram
    pdf_fitted = pdf_fitted * (len(data) * binwidth)

    #Plot PDF
    plot(x,pdf_fitted,'r-')