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How to drop rows of Pandas DataFrame whose value in a certain column is NaN

I have this DataFrame and want only the records whose EPS column is not NaN:

>>> df
                 STK_ID  EPS  cash
STK_ID RPT_Date                   
601166 20111231  601166  NaN   NaN
600036 20111231  600036  NaN    12
600016 20111231  600016  4.3   NaN
601009 20111231  601009  NaN   NaN
601939 20111231  601939  2.5   NaN
000001 20111231  000001  NaN   NaN

…i.e. something like df.drop(....) to get this resulting dataframe:

                  STK_ID  EPS  cash
STK_ID RPT_Date                   
600016 20111231  600016  4.3   NaN
601939 20111231  601939  2.5   NaN

How do I do that?

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Answer

Don’t drop, just take the rows where EPS is not NA:

df = df[df['EPS'].notna()]
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