A PeriodIndex function, which is an index type for a Period object, can be created in two ways:

1. You can do it from a series of Period objects using the period_range function to create an analogue of date_range: 

    In [305]: perRng=pd.period_range('02/01/2014','02/06/2014',freq='D')
              perRng
    Out[305]: <class 'pandas.tseries.period.PeriodIndex'>
              freq: D
              [2014-02-01, ..., 2014-02-06]
              length: 6
    
    In [306]: type(perRng[:2])
    Out[306]: pandas.tseries.period.PeriodIndex
    
    In [307]: perRng[:2]
    Out[307]: <class 'pandas.tseries.period.PeriodIndex'>
              freq: D
             [2014-02-01, 2014-02-02]
  

As we can confirm from the preceding command, when you pull the covers, a PeriodIndex function is really an ndarray of Period objects.

2. It can also be done through a direct call to the Period constructor:

    In [312]: JulyPeriod=pd.PeriodIndex(['07/01/2014','07/31/2014'], freq='D')
        JulyPeriod
    Out[312]: <class 'pandas.tseries.period.PeriodIndex'>
        freq: D
        [2014-07-01, 2014-07-31]

The difference between the two approaches, as can be seen from the preceding output, is that period_range fills in the resulting ndarray, but the Period constructor does not, and you have to specify all the values that should be in the index.