Comparing Row Values Between Columns Pair by Pair

Question

I have a dataframe with two columns of values by ID. I want to compare col_1 and col_2 to see if any col_1 value by IDs bigger than the whole values of col_2 by ID. How can i achieve this? Dataframe looks like this;

data = {'ID': [0, 1, 1, 2, 2, 2, 3],  
        'col_1': [5,15,35,50,55,55,75],
        'col_2': [10,20,30,40,50,60,70]}

I want to create a new column based on the results as 0 and 1. — ninu, Mar 12 '19 at 18:26
do want to check row by row, or every possible pair? any example would help — Maria Nazari, Mar 12 '19 at 18:26
Possible duplicate of [Compare two columns using pandas](https://stackoverflow.com/questions/27474921/compare-two-columns-using-pandas) — G. Anderson, Mar 12 '19 at 18:26
Yes i want to compare every possible pair by ID, and if there is one bigger value result would be 1. — ninu, Mar 12 '19 at 18:28

score 2 · Answer 1 · answered Mar 12 '19 at 18:28

2

IIUC, use:

df['new']=df.col_1.gt(df.col_2).astype(int)
print(df)

   ID  col_1  col_2  new
0   0      5     10    0
1   1     15     20    0
2   1     35     30    1
3   2     50     40    1
4   2     55     50    1
5   2     55     60    0
6   3     75     70    1

answered Mar 12 '19 at 18:28

anky

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70

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I like this, super clean :) – Maria Nazari Mar 12 '19 at 18:30

score 1 · Accepted Answer · answered Mar 12 '19 at 18:28

1

try:

df['result'] = np.where(df['col_1'] > df.groupby('ID')['col_2'].transform('max'), 1, 0)

out:
ID  col_1   col_2   result
0   0   5   10  0
1   1   15  20  0
2   1   35  30  1
3   2   50  40  0
4   2   55  50  0
5   2   55  60  0
6   3   75  70  1

answered Mar 12 '19 at 18:28

Terry

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`(df['col_1'] > df.groupby('ID')['col_2'].transform('max').astype(int)` would have worked also. – Scott Boston Mar 12 '19 at 19:05

Comparing Row Values Between Columns Pair by Pair

2 Answers2