Pandas dataframe multi-index selecting first index first element

Question

This must be a simple question, but its taking too much time to slice a pandas multi-index dataframe for me. So I seek for help.

I have a dataframe like this: (incomplete)

Product_Category  Category_001  Category_002  Category_003  Category_004  \
Warehouse Year                                                             
Whse_A    2011             NaN           NaN    108.000000           NaN   
          2012             NaN           NaN     70.685714           NaN   
          2013       10.086957           NaN     58.475138           NaN   
          2014       18.564516           NaN     71.526316           NaN   
          2015        7.125000           NaN     73.397260           NaN   
          2016        9.212121           NaN     65.900391           NaN   
Whse_C    2011       17.909091           NaN           NaN           NaN   
          2012       36.653374           NaN           NaN           NaN   
          2013       29.292553           NaN           NaN           NaN   
          2014       27.556098           NaN           NaN           NaN   
          2015       28.470356           NaN           NaN           NaN   
          2016       20.480734           NaN           NaN           NaN   
          2017             NaN           NaN           NaN           NaN   
Whse_J    2011       13.000000           NaN           NaN           NaN   
          2012       15.282823           NaN     33.446154           NaN   
          2013       15.574038           NaN     33.181518           NaN   
          2014       17.537404           NaN     23.289256           NaN   
          2015       17.950261           NaN     21.353760           NaN   
          2016       20.335565           NaN     32.150418           NaN   
          2017        7.250000           NaN           NaN           NaN 

It has two index columns: Warehouse and Year.
It has 33 original columns: Category_001 to Category_33.

df1.index
MultiIndex(levels=[[2011, 2012, 2013, 2014, 2015, 2016, 2017], ['Whse_A', 'Whse_C', 'Whse_J', 'Whse_S']],
           codes=[[0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4], [0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3, 0, 1, 2, 3]],
           names=['Year', 'Warehouse'])

I can slice Warehouse 'Whse_A' and year 2011 like this:

df.loc[('Whse_A',2011)]

But I am struggling how to select all Years for 'Whse_A' ?

Related links: https://pandas-docs.github.io/pandas-docs-travis/user_guide/advanced.html

Help is appreciated.

Update
One idea is slicing:

df.loc[('Whse_A',2011):('Whse_A',2017)]

But, can we do it if we don't know the start and end years?

Something like:

df.loc[('Whse_A',:)] 

Answer 1

尝试使用.loc

df.loc[['Whse_A']]