Pandas slicing FutureWarning with 0.21.0

Question

I'm trying to select a subset of a subset of a dataframe, selecting only some columns, and filtering on the rows.

df.loc[df.a.isin(['Apple', 'Pear', 'Mango']), ['a', 'b', 'f', 'g']]

However, I'm getting the error:

Passing list-likes to .loc or [] with any missing label will raise
KeyError in the future, you can use .reindex() as an alternative.

What 's the correct way to slice and filter now?

Answer 1

This is a change introduced in v0.21.1, and has been explained in the docs at length -

Previously, selecting with a list of labels, where one or more labels were missing would always succeed, returning NaN for missing labels. This will now show a FutureWarning. In the future this will raise a KeyError (GH15747). This warning will trigger on a DataFrame or a Series for using .loc[] or [[]] when passing a list-of-labels with at least 1 missing label.

For example,

df

     A    B  C
0  7.0  NaN  8
1  3.0  3.0  5
2  8.0  1.0  7
3  NaN  0.0  3
4  8.0  2.0  7

Try some kind of slicing as you're doing -

df.loc[df.A.gt(6), ['A', 'C']]

     A  C
0  7.0  8
2  8.0  7
4  8.0  7

No problem. Now, try replacing C with a non-existent column label -

df.loc[df.A.gt(6), ['A', 'D']]
FutureWarning: Passing list-likes to .loc or [] with any missing label will raise
KeyError in the future, you can use .reindex() as an alternative.

     A   D
0  7.0 NaN
2  8.0 NaN
4  8.0 NaN

So, in your case, the error is because of the column labels you pass to loc. Take another look at them.