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>