On Tuesday, 30 May 2017 22:33:50 UTC+2, Peter Otten wrote:
> z...@gmail.com wrote:
>
> > I have a dataframe:
> >
> >
> > df = pd.DataFrame({
> > 'x': [3,4,5,8,10,11,12,13,15,16,18,21,24,25],
> > 'a': [10,9,16,4,21,5,3,17,11,5,21,19,3,9]
> > })
> >
> > df
> > Out[30]:
> > a x
> > 0 10 3
> > 1 9 4
> > 2 16 5
> > 3 4 8
> > 4 21 10
> > 5 5 11
> > 6 3 12
> > 7 17 13
> > 8 11 15
> > 9 5 16
> > 10 21 18
> > 11 19 21
> > 12 3 24
> >
> >
> > for every "x" value I should subtract a certain number (say 3), and then
> > find a maximum "a" value where x is in a range from x-3 to x.
> >
> > For example:
> > index, x, x-3, max(a) where x is between x-3 and x
> > 0, 3, 0, 10
> > 1, 4, 1, 10
> > 2, 5, 2, 16
> > 3, 8, 5, 16
> > 4, 10, 7, 21
> > ...
> >
> > "x" is incremental, "a" is random
> > How to find max "a" values?
>
> I have no idea how you'd do that in pandas.
> Here's generic Python:
>
> >>> m = df.as_matrix()
> >>> pd.DataFrame(
> ... [[x, x-3, max(aa for aa, xx in m if x-3<=xx<=x)] for a, x in m],
> ... columns=["x", "x-3", "max(a)..."]
> ... )
> x x-3 max(a)...
> 0 3 0 10
> 1 4 1 10
> 2 5 2 16
> 3 8 5 16
> 4 10 7 21
> 5 11 8 21
> 6 12 9 21
> 7 13 10 21
> 8 15 12 17
> 9 16 13 17
> 10 18 15 21
> 11 21 18 21
> 12 24 21 19
> 13 25 22 9
>
> [14 rows x 3 columns]
> >>>
Hi,
this is exactly what I wanted to accomplish.
Thank you very very much. You helped a lot.
Have a great day. Thanks again.
Best regards.
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