How do I add a column with the value being the result of a function including max( )?

Question

If I have a data frame consisting of the following values (exact values don’t matter):

    import pandas as pd
    import bumpy as np
    df = pd.DataFrame(np.random.randint(0,100,size=(5, 4)), columns=list('ABCD'))
    df

How do I add a fifth column ‘E’ and have the values in column E compare the value A to values B,C,D? I want to have the result be 1 if Column A is greater than the max value of B, C, D column values and 0 if Column A is less than the max value of B, C, D column values.

I tried the following:

    df['E']= np.where( df['A'] > max(df['B'],df['C'],df['D'], 1, 0)

I receive the following error:

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

Thanks in advance!

Asked By: connorc

||

Source

Answer 1

here is one way to do it, using pandas max

df['E']=np.where(df['A']> df[['B','C','D']].max(axis=1),
                 1,
                 0)
df

    A   B   C   D   E
0   92  23  7   68  1
1   23  79  79  38  0
2   66  19  29  92  0
3   13  40  4   36  0
4   39  28  51  90  0

Answered By: Naveed

Answer 2

alternate way


compare and convert the boolean to int

df['E']=(df['A']> df[['B','C','D']].max(axis=1)).astype(int)
df

    A   B   C   D   E
0   94  8   31  82  1
1   68  23  9   76  0
2   52  66  42  78  0
3   43  18  21  3   1
4   21  39  95  29  0

df

    A   B   C   D
0   94  8   31  82
1   68  23  9   76
2   52  66  42  78
3   43  18  21  3
4   21  39  95  29

Answered By: Naveed

How do I add a column with the value being the result of a function including max( )?

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