Select rows from a DataFrame based on presence of null value in specific column or columns
I think you need isnull for checking NaN values with boolean indexing:
df[df['Easting'].isnull()]Docs:
Warning
One has to be mindful that in python (and numpy), the nan's don’t compare equal, but None's do. Note that Pandas/numpy uses the fact that np.nan != np.nan, and treats None like np.nan.
In [11]: None == NoneOut[11]: TrueIn [12]: np.nan == np.nanOut[12]: FalseSo as compared to above, a scalar equality comparison versus a None/np.nan doesn’t provide useful information.
In [13]: df2['one'] == np.nanOut[13]: a Falseb Falsec Falsed Falsee Falsef Falseg Falseh FalseName: one, dtype: bool