Pandas dataframe, how to find a very specific max values?

[zljubisic at gmail.com]

On Tuesday, 30 May 2017 22:33:50 UTC+2, Peter Otten  wrote:
> zlj at 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.