How to color bars who make up 50% of the data? - matplotlib

Question

I am plotting a histogram for some data points with bar heights being the percentage of that bin from the whole data:
x = normal(size=1000)
hist, bins = np.histogram(x, bins=20)
plt.bar(bins[:-1], hist.astype(np.float32) / hist.sum(), width=(bins[1]-bins[0]), alpha=0.6)
The result is:
I would like all bars that sum up to be 50% of the data to be in a different color, for example:
(I selected the colored bars without actually checking whether their sum adds to 50%)
Any suggestions how to accomplish this?

Answer 1

Here is how you can plot the first half of the bins with a different color, this looks like your mock, but I am not sure it complies to %50 of the data (it is not clear to me what do you mean by that).
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.mlab as mlab
mu, sigma = 100, 15
x = mu + sigma * np.random.randn(10000)
fig = plt.figure()
ax = fig.add_subplot(111)
# the histogram of the data
n, bins, patches = ax.hist(x, 50, normed=1, facecolor='green', alpha=0.75)
# now that we found the index we color all the beans smaller than middle index
for p in patches[:len(bins)/2]:
p.set_facecolor('red')
# hist uses np.histogram under the hood to create 'n' and 'bins'.
# np.histogram returns the bin edges, so there will be 50 probability
# density values in n, 51 bin edges in bins and 50 patches. To get
# everything lined up, we'll compute the bin centers
bincenters = 0.5*(bins[1:]+bins[:-1])
# add a 'best fit' line for the normal PDF
y = mlab.normpdf( bincenters, mu, sigma)
l = ax.plot(bincenters, y, 'r--', linewidth=1)
ax.set_xlabel('Smarts')
ax.set_ylabel('Probability')
ax.set_xlim(40, 160)
ax.set_ylim(0, 0.03)
ax.grid(True)
plt.show()
And the output is:
update
The key method you want to look at is patch.set_set_facecolor. You have to understand that almost everything you plot inside the axes object is a Patch, and as such it has this method, here is another example, I arbitrary choose the first 3 bars to have another color, you can choose based on what ever you decide:
import numpy as np
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111)
## the data
N = 5
menMeans = [18, 35, 30, 35, 27]
## necessary variables
ind = np.arange(N) # the x locations for the groups
width = 0.35 # the width of the bars
## the bars
rects1 = ax.bar(ind, menMeans, width,
color='black',
error_kw=dict(elinewidth=2,ecolor='red'))
for patch in rects1.patches[:3]:
patch.set_facecolor('red')
ax.set_xlim(-width,len(ind)+width)
ax.set_ylim(0,45)
ax.set_ylabel('Scores')
xTickMarks = ['Group'+str(i) for i in range(1,6)]
ax.set_xticks(ind)
xtickNames = ax.set_xticklabels(xTickMarks)
plt.setp(xtickNames, rotation=45, fontsize=10)
plt.show()