MulSeries.nloc#

MulSeries.nloc#

Flexible hierachical indexing on the index dataframe using positions.

The slicer can be a list or a dict. Check introduction to mloc ??? for detailed usage.

If a list is used, it behaves exactly like MulSeries.mloc.

If a dict is used, it behaves similarly to MulSeries.mloc except that instead of using column names as keys, it uses the numeric positions of the columns as keys.

Examples#

Dictionary indexing:

>>> import pandas as pd
>>> import muldataframe as md
>>> index = pd.DataFrame([['a','b','c'],
                          [ 'g','b','f'],
                          [ 'b','g','h']],
                   columns=['x','y','y'])
>>> name = pd.Series(['a','b'],index=['e','f'],name='cc')
>>> ms = md.MulSeries([1,2,3],index=index,name=name)
>>> ms.nloc[{1:['b','g'],0:['b','a']}]
(2,)        e   a
            f   b
               cc
----------  ------
   x  y  y     cc
2  b  g  h  2   3
0  a  b  c  0   1

Note that with a dict in MulSeries.mloc, you can only select the last y column in the index dataframe. Using nloc you are able to select the first y column.