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

  def hist(self, x, bins=None, range=None, density=None, weights=None,
       cumulative=False, bottom=None, histtype='bar', align='mid',
       orientation='vertical', rwidth=None, log=False,
       color=None, label=None, stacked=False, normed=None,
       **kwargs):

def histogram(a, bins=10, range=None, normed=False, weights=None,
     density=None)

def relfreq(a, numbins=10, defaultreallimits=None, weights=None)
Returns
-------
frequency : ndarray
  Binned values of relative frequency.
lowerlimit : float
  Lower real limit
binsize : float
  Width of each bin.
extrapoints : int
  Extra points.

rng = np.random.RandomState(seed=12345)
samples = stats.norm.rvs(size=1000, random_state=rng)
res = stats.relfreq(samples, numbins=25)
x = res.lowerlimit + np.linspace(0, res.binsize*res.frequency.size,res.frequency.size)
fig = plt.figure(figsize=(5, 4))
ax = fig.add_subplot(1, 1, 1)
ax.bar(x, res.frequency, width=res.binsize)
ax.set_title('Relative frequency histogram')
ax.set_xlim([x.min(), x.max()])
plt.show()

rng = np.random.RandomState(seed=12345)
samples = stats.norm.rvs(size=1000, random_state=rng)
res = stats.relfreq(samples, numbins=25)
x = res.lowerlimit + np.linspace(0, res.binsize*res.frequency.size,res.frequency.size)
y=np.cumsum(res.frequency)
plt.plot(x,y)
plt.title('Figure6 累积分布直方图')
plt.show()