import matplotlib.pyplot as plt
from scipy import stats
x = [1, 4, 2, 1, 3, 1]
res = stats.cumfreq(x, numbins=4, defaultreallimits=(1.5, 5))
res.cumcount
# array([ 1.,  2.,  3.,  3.])
res.extrapoints
# 3

# Create a normal distribution with 1000 random values

rng = np.random.RandomState(seed=12345)
samples = stats.norm.rvs(size=1000, random_state=rng)

# Calculate cumulative frequencies

res = stats.cumfreq(samples, numbins=25)

# Calculate space of values for x

x = res.lowerlimit + np.linspace(0, res.binsize*res.cumcount.size,
                                 res.cumcount.size)

# Plot histogram and cumulative histogram

fig = plt.figure(figsize=(10, 4))
ax1 = fig.add_subplot(1, 2, 1)
ax2 = fig.add_subplot(1, 2, 2)
ax1.hist(samples, bins=25)
ax1.set_title('Histogram')
ax2.bar(x, res.cumcount, width=res.binsize)
ax2.set_title('Cumulative histogram')
ax2.set_xlim([x.min(), x.max()])

plt.show()