Applying multiple functions to pandas column

Question

I am attempting to sort by the maximum value of a column such as:

    dfWinners = df_new_out['Margin'].apply[max().sort_values(ascending=False)]

But am unsure of how to use the apply function for multiple methods such as max and sort. I'm sure it's a very simple problem but I cannot for the life of me find it through searching on here. Thank you!

Sorting will give you the max value anyways, so calling sort_values(ascending=False) should be enough. — Carlo Mazzaferro
– Carlo Mazzaferro, Commented Sep 14, 2017 at 16:06
You haven't sufficiently described your problem. Sort what? Do you want to place columns in the order of which column has the largest max for that column? — piRSquared
– piRSquared, Commented Sep 14, 2017 at 16:10
Sorry I should have clarified more. I need to apply the maximum function, and then sort that new maximum functioned column in descending order (If that makes sense) I can clarify more if needed — andrew fay
– andrew fay, Commented Sep 14, 2017 at 16:21

A.Kot · Accepted Answer · 2017-09-14 16:22:50Z

1

It's not clear what you're trying to do by assigning to dfWinners

If you intend dfWinners to be a list of sorted maximum to minimum values as you've described above then you can use the native sorted() method of python.

dfWinners = sorted(df_new_out['Margin'])

Else, you can sort your dataframe in place

df_new_out.sort_values(by = ['Margin'], ascending=False, inplace=True)

edited Sep 14, 2017 at 16:22

answered Sep 14, 2017 at 16:12

A.Kot

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2 Comments

andrew fay Over a year ago

Not really necessary I guess, could use the second option. My problem is I'm getting errors as such: Cannot access callable attribute 'sort_values' of 'SeriesGroupBy' objects, try using the 'apply' method

A.Kot Over a year ago

@andrewfay Sorry, edited. the columns are parameters

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