Pandas slicing FutureWarning with 0.21.0

TL;DR: There is likely a typo or spelling error in the column header names.

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.

This error also occurs with .append call when the list contains new columns. To avoid this

Use:

df=df.append(pd.Series({'A':i,'M':j}), ignore_index=True)

Instead of,

df=df.append([{'A':i,'M':j}], ignore_index=True)

Full error message:

C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:1472: FutureWarning: Passing list-likes to .loc or with any missing label will raise KeyError in the future, you can use .reindex() as an alternative.

Thanks to https://stackoverflow.com/a/50230080/207661

If you want to retain the index you can pass list comprehension instead of a column list:

loan_data_inputs_train.loc[:,[i for i in List_col_without_reference_cat]]