#!/usr/bin/env python
# coding: utf-8

# # Shadograms
# 
# The idea seems to have originated first(?) in [Visual Statistics](http://www.visualstats.org/) 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]:


get_ipython().run_line_magic('pylab', 'inline')
import seaborn as sns


# 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)


# 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[ ]: