Fixed the y-scaling problem

normdist.py

@@ -20,6 +20,7 @@ fig, ax = plt.subplots()
 textstr = '\n'.join((
     r'$n=%d$' % (len(data)),
     r'$\mu=%.2f$' % (mean, ),
+    r'$\sigma=%.2f$' % (stddev, ),
     r'$P=%.2f$' % (prob, ),
     r'$I=%.2f$ bits' % (info, )))
 # these are matplotlib.patch.Patch properties
@@ -30,7 +31,7 @@ ax.text(0.05, 0.95, textstr, transform=ax.transAxes, fontsize=14,
         verticalalignment='top', bbox=props)
 
 x = np.linspace(mean-3*stddev, mean+3*stddev, 500)
-y = norm.pdf(x, mean, stddev)
+y = norm.pdf(x, loc=mean, scale=stddev) * stddev#rescale back to unity area
 plt.axvline(x=mean, color="green", linestyle="dashed", label="mean")
 plt.axvline(lowerbound, color="red")
 plt.axvline(upperbound, color="red")