import pandas as pd
import numpy as np
from pandas import DataFrame

plot_df = DataFrame(np.random.randn(100,2), columns=['x','y'])
plot_df.head(20)

	x	y
0	-0.859584	0.756336
1	-0.128614	0.244516
2	-0.180215	0.262050
3	0.076480	-0.789597
4	-0.459032	-0.691748
5	0.451849	-1.087149
6	-1.280314	-0.189647
7	-0.074831	1.391770
8	0.345652	1.317929
9	-2.536633	0.646222
10	1.572306	-0.584983
11	-0.022376	0.308307
12	1.675047	0.532822
13	-1.683904	0.609653
14	1.870078	-0.975634
15	1.638483	-1.442473
16	-1.530614	-0.204387
17	-1.216783	0.930962
18	-0.730724	-0.382810
19	1.549956	1.065209

%pylab inline
plot_df.plot()

Populating the interactive namespace from numpy and matplotlib

<matplotlib.axes._subplots.AxesSubplot at 0x106ba9450>

%pylab inline
plot_df2 = plot_df
plot_df2['y'] = plot_df2['y'].map(lambda x : x+1)
plot_df2.plot()

Populating the interactive namespace from numpy and matplotlib

<matplotlib.axes._subplots.AxesSubplot at 0x106c01cd0>

%pylab inline
plot_df2.hist()

Populating the interactive namespace from numpy and matplotlib

array([[<matplotlib.axes._subplots.AxesSubplot object at 0x106d768d0>,
        <matplotlib.axes._subplots.AxesSubplot object at 0x10710ab90>]], dtype=object)

%pylab inline
pd.Series([0,2,4,3,8]).plot()

Populating the interactive namespace from numpy and matplotlib

<matplotlib.axes._subplots.AxesSubplot at 0x106b242d0>