How to use numpy arange with pandas Series?

Question

I'm currently trying to calculate the new DataFrame column. It should equal the sum from 0 to the value of the existing column. For example, I have such DataFrame df:

And now, I want to calculate the second column as a sum from 0 to the first column value.

   col1  col2
0     1     1
1     2     3
2     3     6
3     4    10
4     5    15

I tried this code

df['col2'] = np.arange(0,df['col1']+1,1).sum()

But get the error

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

Any suggestions?

As an aside, your question was unnecessarily difficult to understand because you used a degenerate example input [1,2,3,4,5], leading to an intuitive but wrong solution using cumsum(). An example input like [3, 5, 2] would not have had this problem. — John Zwinck
– John Zwinck, Commented Dec 24, 2022 at 10:03
@JohnZwinck I see, I misunderstood the question, bad example indeed — mozway
– mozway, Commented Dec 24, 2022 at 10:35

John Zwinck · Accepted Answer · 2022-12-24 10:02:03Z

2

What you want is the sum of the first N positive integers. That has a closed form solution: N(N + 1)/2. The advantage of using such a solution is that you don't need to iterate over a sequence.

Using your example, the solution is:

df['col1'] * (df['col1'] + 1) // 2

answered Dec 24, 2022 at 10:02

John Zwinck

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