Filtering multiple items in a multi-index Python Panda dataframe

You can get_level_values in conjunction with Boolean slicing.

In [50]:

print df[np.in1d(df.index.get_level_values(1), ['Lake', 'River', 'Upland'])]
                          Area
NSRCODE PBL_AWI               
CM      Lake      57124.819333
        River      1603.906642
LBH     Lake     258046.508310
        River     44262.807900

The same idea can be expressed in many different ways, such as df[df.index.get_level_values('PBL_AWI').isin(['Lake', 'River', 'Upland'])]

Note that you have 'upland' in your data instead of 'Upland'

Another (maybe cleaner) way might be this one:

print(df[df.index.isin(['Lake', 'River', 'Upland'], level=1)])

The parameter level specifies the index number (starting with 0) or index name (here: level='PBL_AWI')