Essential Basic Functionality

Here we discuss a lot of the essential functionality common to the pandas data structures. Here’s how to create some of the objects used in the examples from the previous section:

>>> import pandas as pd
>>> index = pd.date_range('1/1/2000', periods=8)
>>> s = pd.Series(np.random.randn(5), index=['a', 'b', 'c', 'd', 'e'])
>>> df = pd.DataFrame(np.random.randn(8, 3), index=index,
>>>                   columns=['A', 'B', 'C'])
>>> wp = pd.Panel(np.random.randn(2, 5, 4), items=['Item1', 'Item2'],
>>>               major_axis=pd.date_range('1/1/2000', periods=5),
>>>               minor_axis=['A', 'B', 'C', 'D'])

In [1]: index
Out[1]: 
DatetimeIndex(['2000-01-01', '2000-01-02', '2000-01-03', '2000-01-04',
               '2000-01-05', '2000-01-06', '2000-01-07', '2000-01-08'],
              dtype='datetime64[ns]', freq='D')

In [2]: df
Out[2]: 
                   A         B         C
2000-01-01  0.112246  0.871721 -0.816064
2000-01-02 -0.784880  1.030659  0.187483
2000-01-03 -1.933946  0.377312  0.734122
2000-01-04  2.141616 -0.011225  0.048869
2000-01-05 -1.360687 -0.479010 -0.859661
2000-01-06 -0.231595 -0.527750 -1.296337
2000-01-07  0.150680  0.123836  0.571764
2000-01-08  1.555563 -0.823761  0.535420

In [3]: s
Out[3]: 
a   -1.032853
b    1.469725
c    1.304124
d    1.449735
e    0.203109
dtype: float64

In [4]: wp
Out[4]: 
<class 'pandas.core.panel.Panel'>
Dimensions: 2 (items) x 5 (major_axis) x 4 (minor_axis)
Items axis: Item1 to Item2
Major_axis axis: 2000-01-01 00:00:00 to 2000-01-05 00:00:00
Minor_axis axis: A to D