Pandas drop duplicates ignoring NaN

问题

In a Pandas df, I am trying to drop duplicates across multiple columns. Lots of data per row is NaN.

This is only an example, the data is a mixed bag, so many different combinations exist.

df.drop_duplicates()

    IDnum       name            formNumber
1   NaN         AP GROUP        028-11964
2   1364615.0   AP GROUP        NaN
3   NaN         AP GROUP        NaN

Hopeful Output:

    IDnum       name            formNumber
1   1364615.0   AP GROUP        028-11964

EDIT:

If the df.drop_duplicates() looks like this, would it change the solution? :

df.drop_duplicates()

    IDnum       name            formNumber
0   NaN         AP GROUP        028-11964
1   1364615.0   AP GROUP        028-11964
2   1364615.0   AP GROUP        NaN
3   NaN         AP GROUP        NaN

回答1:

You can using groupby + first

df.groupby('name',as_index=False).first()
Out[206]: 
      name      IDnum formNumber
0  APGROUP  1364615.0  028-11964

回答2:

You need:

df.bfill().ffill().drop_duplicates()

Output:

IDnum   name    formNumber
0   1364615.0   AP GROUP    028-11964

来源：https://stackoverflow.com/questions/51217780/pandas-drop-duplicates-ignoring-nan