I have a simple pandas.DataFrame

    A
0   1
1   2
2   3
3   4
4   5
5   6

I am trying to calculate the standard deviation on a rolling basis, all starting from the first row. So it would be standard deviation from rows 1-4, then rows 1-5, then rows 1-6, etc. I could easily do this iteratively but I'd prefer to do it with pandas functionality.

The final output should be

    A   Standard Deviation
0   1
1   2
2   3
3   4   1.581
4   5   1.870
5   6   2.160

Is there an appropriate method to do so?

CodePudding user response：

You can use expanding.std:

df['A'].expanding(min_periods=4).std()

Output:

0         NaN
1         NaN
2         NaN
3    1.290994
4    1.581139
5    1.870829
Name: A, dtype: float64