Split Columns with Condition in Pandas Data frame

Question

I have a "Code" and "Amount column. I need to split both of them into three different columns based on the condition. Example:

Code	Amount
1	$40.00
1	$20.00

Condition: First $5.00 goes to Code1, $10.00 goes to Code2 and

Output:

Code	Amount	Code1	Amount1	Code2	Amount2	Code3	Amount3
1	$40.00	1.1	$5.00	1.2	$10.00	1.3	$25.00
1	$20.00	1.1	$5.00	1.2	$10.00	1.3	$5.00

I tried apply function but I am not getting any desired results.

Asked By: S_Python

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Source

Answer 1

You can use a loop:

subamounts = [5, 10, 1000]

l = [df]
remainder = df['Amount']
for i, x in enumerate(subamounts, start=1):
    remainder = remainder.sub(x)
    l.append(pd.DataFrame({f'Code{i}': df['Code'].astype(str).add(f'.{i}'),
                           f'Amount {i}': x+remainder.clip(upper=0)
                          }))
    remainder = remainder.clip(lower=0)

out = pd.concat(l, axis=1)

Output (with more examples):

   Code  Amount Code1  Amount 1 Code2  Amount 2 Code3  Amount 3
0     1    40.0   1.1       5.0   1.2      10.0   1.3      25.0
1     1    20.0   1.1       5.0   1.2      10.0   1.3       5.0
2     1     7.0   1.1       5.0   1.2       2.0   1.3       0.0
3     1     3.0   1.1       3.0   1.2       0.0   1.3       0.0

Answered By: mozway

Split Columns with Condition in Pandas Data frame

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