Multi-indexing

We'll now turn to the topic of multi-indexing. Multi-level or hierarchical indexing is useful because it enables pandas users to select and massage data in multiple dimensions by using data structures such as Series and DataFrames. In order to start, let's save the following data to a file, stock_index_prices.csv, and read it in:

    In[950]:sharesIndexDataDF=pd.read_csv('./stock_index_prices.csv')
    In [951]: sharesIndexDataDF
    Out[951]:
      TradingDate  PriceType  Nasdaq     S&P 500  Russell 2000
    0   2014/02/21   open     4282.17  1841.07  1166.25
    1   2014/02/21   close     4263.41  1836.25  1164.63
    2   2014/02/21   high     4284.85  1846.13  1168.43
    3   2014/02/24   open     4273.32  1836.78  1166.74
    4   2014/02/24   close     4292.97  1847.61  1174.55
    5   2014/02/24   high      4311.13  1858.71  1180.29
...