How to apply a function on a specific Pandas column that requires the creation of a new column in Python

Question

I have a pandas DataFrame with three columns:

x = [4,2,4,-4,-80,1]
y = [1,2,3,-10,50,1]
z = [3,4,-1,-3,0,-1]
df = pd.DataFrame({'x': x,'y': y, 'z':z})

And I need to create a function that returns the maximum value reached by the accumulative max function. In order to do this I try:

def get_max(DataFrame):
    DataFrame['CumSum'] = DataFrame.cumsum()
    print(max(DataFrame['CumSum']))

If I apply this function for the first time, by writing for example:

get_max(df['x'] )

it works correctly and it returns 10, but if I try to apply it a second time on df['x'] I get an error: ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

Not sure about the error, I think that perhaps the problem occurs because I am trying to create a new column that already has been created thru this line:

DataFrame['CumSum'] = DataFrame.cumsum()

I would appreciate if someone could tell me if there is any way of solving this.

Thanks a lot in advance.

kynnemall · Accepted Answer · 2020-04-21 11:41:04Z

1

You haven't created a new column through this line:

DataFrame['CumSum'] = DataFrame.cumsum()

If you change your function to:

def get_max(Series):
    print(max(Series.cumsum()))

It will work on a column of the data, as you want it to

answered Apr 21, 2020 at 11:41

kynnemall

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