Compute the evolution of several quanties from a data file

Question

This question is somehow a part II of this: Part I.

Here comes a small data sample as a minimal working example:

{{-5.`, -3, 24.89`, 
0.8079019748736321`, -1, -1}, {-4.977477477477477`, -3, 24.72`, 
0.8100409238103935`, -1, 1}, {-4.954954954954955`, -3, 24.54`, 
0.8122953345427153`, -1, 2}, {-4.932432432432432`, -3, 24.36`, 
0.8145539903185015`, -1, 0}, {-4.90990990990991`, -3, 24.19`, 
0.8167060089472148`, -1, -1}, {-4.887387387387387`, -3, 24.01`, 
0.8189737833735357`, -1, -1}, {-4.864864864864865`, -3, 23.84`, 
0.8211357279224385`, -1, -1}, {-4.842342342342342`, -3, 23.67`, 
0.823303331789986`, -1, 0}, {-4.81981981981982`, -2, 23.5`, 
0.8254770541856945`, -1, -1}, {-4.797297297297297`, -2, 23.32`, 
0.8277682452908253`, -1, 2}, {-4.774774774774775`, -2, 23.15`, 
0.8299553813547601`, -1, 1}, {-4.752252252252252`, -2, 22.98`, 
0.8321495854317591`, -1, 2}, {-4.72972972972973`, -2, 22.82`, 
0.8342399060011664`, -1, -1}, {-4.707207207207207`, -2, 22.65`, 
0.8364482241698246`, -1, 2}, {-4.684684684684685`, -2, 22.48`, 
0.8386633336338121`, -1, -1}, {-4.662162162162162`, -1, 22.31`, 
0.8408848961319084`, -1, 0}, {-4.63963963963964`, -1, 22.15`, 
0.843001699453557`, -1, 1}, {-4.617117117117117`, -1, 21.98`, 
0.8452350102456677`, -1, 1}, {-4.594594594594595`, -1, 21.81`, 
0.8474735570160751`, -1, 2}, {-4.572072072072072`, -1, 21.65`, 
0.8496066341065539`, -1, 0}, {-4.54954954954955`, -1, 21.49`, 
0.8517447815274005`, -1, 2}, {-4.527027027027027`, 0, 21.32`, 
0.8539977804973352`, -1, -1}, {-4.504504504504505`, 0, 21.16`, 
0.8561457246831677`, -1, 2}, {-4.481981981981982`, 0, 21.`, 
0.8582989136727225`, -1, 1}, {-4.45945945945946`, 0, 20.83`, 
0.8605668266689402`, -1, 0}, {-4.436936936936937`, 0, 20.67`, 
0.862731269804195`, -1, -1}, {-4.414414414414415`, 1, 20.51`, 
0.8649021245634532`, -1, 2}, {-4.391891891891892`, 1, 20.35`, 
0.8670798666925034`, -1, -1}, {-4.36936936936937`, 1, 20.19`, 
0.8692649521543424`, -1, 2}, {-4.346846846846847`, 1, 20.03`, 
0.8714577803779188`, -1, 1}, {-4.324324324324325`, 1, 19.88`, 
0.873550635695638`, -1, 0}, {-4.301801801801802`, 1, 19.72`, 
0.8757599471643019`, -1, 0}, {-4.27927927927928`, 1, 19.56`, 
0.8779776273998509`, -1, 1}}

This time we need only columns 1, 2, 3 and 6. The first column contains the x position, the second column the corresponding energy E, the third the time, while the sixth column has only integers regarding a classification.

Now I want to do the following. For every value of E we have several values of x with different classification. The possible integers of the sixth column are: {-1, 0, 1, 2}.

(a). I want to compute the mean value of the third column for the first value of E when the six column is either 1 or 2 (not -1 and 0). Then go to the next value of E and repeat the procedure. Thus we can follow the evolution of the mean value as a function of E.

(b). For the first value of E compute how many (the percentage) 1 and 2 with time (third column) < 23 exist. Then repeat this calculation for all the other values of E, so as to create a plot showing the evolution of this percentage as a function of E.

Any suggestions?

Answer 1

(a)

Mean[Cases[Data, {_, e_, x_, _, _, i_} /; e == # && (i == 1 || i == 2) -> {e, x}]] & /@ 
  Range[-3, 1]
(* {{-3, 24.63}, {-2, 23.025}, {-1, 21.8575}, {0, 21.08}, {1, 20.0725}} *)

(b)

lyes = Count[Data, {_, e_, t_, _, _, i_} /; e == # && t < 23 && (i == 1 || i == 2)]& /@ 
  Range[-3, 1]    
ltot = Count[Data, {_, e_, t_, _, _, i_} /; e == #]& /@ Range[-3, 1]
N[lyes/ltot]
(* {0., 0.285714, 0.666667, 0.4, 0.571429} *)

If, as indicated in a Comment, the values of e are not regularly spaced, they can be extracted directly from Data.

energies = Union[Cases[Data, {_, e_, t_, _, _, i_} -> e]]
(* {-3, -2, -1, 0, 1} *)

and Range[-3, 1] replaced by energies in the expressions above.