问在python中绘制熊猫系列的CDF

EN

In [10]: import matplotlib.pyplot as plt

In [11]: plt.hist?
...
Plot a histogram.

Compute and draw the histogram of *x*. The return value is a
tuple (*n*, *bins*, *patches*) or ([*n0*, *n1*, ...], *bins*,
[*patches0*, *patches1*,...]) if the input contains multiple
data.
...
cumulative : boolean, optional, default : False
    If `True`, then a histogram is computed where each bin gives the
    counts in that bin plus all bins for smaller values. The last bin
    gives the total number of datapoints.  If `normed` is also `True`
    then the histogram is normalized such that the last bin equals 1.
    If `cumulative` evaluates to less than 0 (e.g., -1), the direction
    of accumulation is reversed.  In this case, if `normed` is also
    `True`, then the histogram is normalized such that the first bin
    equals 1.

...

In [12]: import pandas as pd

In [13]: import numpy as np

In [14]: ser = pd.Series(np.random.normal(size=1000))

In [15]: ser.hist(cumulative=True, density=1, bins=100)
Out[15]: <matplotlib.axes.AxesSubplot at 0x11469a590>

In [16]: plt.show()

import pandas as pd
import numpy as np
ser = pd.Series(np.random.normal(size=100))

ser = ser.sort_values()

ser[len(ser)] = ser.iloc[-1]

cum_dist = np.linspace(0.,1.,len(ser))
ser_cdf = pd.Series(cum_dist, index=ser)

ser_cdf.plot(drawstyle='steps')

import pandas as pd
df = pd.Series([i for i in range(100)])
df.hist( cumulative = True )