Shadograms

The idea seems to have originated first(?) in Visual Statistics Book by Young and Vaeiro-Mora.

The idea is pretty simple: Overlay histograms of different widhts, in a way averaging them. The density is then gauged by the degree of "darkness" of the shade. Higher the density, higher is the shade at that point.



In [1]:

    
%pylab inline
import seaborn as sns









    



Populating the interactive namespace from numpy and matplotlib



In [2]:

    
x = np.random.normal(loc=3, scale=1, size=1000)
y = np.random.normal(loc=10, scale=1, size=1000)

z = np.concatenate([x, y])



In [3]:

    
sns.kdeplot(z)









    Out[3]:





<matplotlib.axes._subplots.AxesSubplot at 0x7fec3ad26f60>



In [4]:

    
fig, ax = plt.subplots()
for n_bins in range(10, 50):
    n, bins, patches = ax.hist(z, n_bins,
                               histtype = 'step', 
                               fill = 'green', 
                               density=1, 
                               facecolor='green',
                               alpha=0.1,
                               color='green')



In [ ]: