I have a list of data some rows need to be filtered.
I have some criteria to extract those rows which I called them crit
. For each crit
that qualifies data, I want to get sub-set of data as output.
Sometimes there is a set of functions that can extract a group of data from a larger data set based on specific criteria that you set.
I think one of the best option would be dplyr
. Although, I have watched some of dplyr
package videos they are mainly focusing on sorting and selecting of rows on some simple examples.
Sometimes, though, we need to be able to pull a set of criteria dynamically that change.
Thus, I need an expert consideration to dplyr
functionality to my data.frame
.
here is the reproducible example of my data
set.seed(1)
data.list <- lapply(1:3, function(x) {
nrep <- 3
time <- rep(seq(90,54000,length.out=12),times=nrep)
Mx <- c(replicate(nrep,sort(runif(12,-0.014,0.012),decreasing=TRUE)))
My <- c(replicate(nrep,sort(runif(12,-0.02,0.02),decreasing=TRUE)))
Mz <- c(replicate(nrep,sort(runif(12,-1,1),decreasing=TRUE)))
df <- data.frame(time,Mx,My,Mz,set_nbr=x)
})
from inside of this data.list
I want to extract some unique groups
that matches a condition.
Matching condition is defined from
crit
output.
> crit
time Mz set_nbr
1 24594.55 -0.04729751 1
2 29495.45 -0.50902297 1
3 24594.55 -0.04376393 1
4 39297.27 -0.22218980 2
5 24594.55 -0.36407263 2
6 34396.36 -0.38341534 2
7 19693.64 -0.34597255 3
8 14792.73 -0.01480776 3
9 29495.45 -0.00999671 3
I find the first observation of negative Mz
value inside of each data.list
group
. Here group
means the values in between 90:54000 in time
column that is one group. so each data.list[[1]] 3 group, data.list[[2]] 3 group data.list[[3]] 3 group.
I want to:
- Find
min
, andmax
time
value ofMz
grouped_byset_nbr
in thecrit
output.
UPDATE
with the answer of @akrun this task is done by the following code
min_time<- crit %>%
group_by(set_nbr) %>%
filter(time==min(time))
max_time<- crit %>%
group_by(set_nbr) %>%
filter(time==max(time))
- Filter out these cases inside of
data.list
within thegroups
.
As for example, inside of data.list[[2]]
if we want to extract min
time value of Mz
as concluded in crit
output
> data.list[[2]]
time Mx My Mz set_nbr
1 90.000 0.0113804381 0.0145817980 0.887449637 2
2 4990.909 0.0100259362 0.0098679308 0.772901887 2
3 9891.818 0.0050266053 0.0091723849 0.754115086 2
4 14792.727 0.0046047177 0.0045857989 0.516206105 2
5 19693.636 0.0026426272 0.0022863816 0.448997785 2
6 24594.545 0.0015677851 0.0000176389 0.423487735 2
7 29495.455 -0.0023966069 -0.0018747422 0.095293174 2
8 34396.364 -0.0027816840 -0.0018971667 0.006678971 2
9 39297.273 -0.0047251003 -0.0068489072 -0.222189800 2
10 44198.182 -0.0101464994 -0.0127653456 -0.412539690 2
11 49099.091 -0.0113172099 -0.0129949293 -0.617479780 2
12 54000.000 -0.0136599830 -0.0158004944 -0.621612755 2
13 90.000 0.0117878041 0.0158037641 0.854604177 2
14 4990.909 0.0056253446 0.0152247614 0.681014064 2
15 9891.818 0.0014885119 0.0111993956 0.565702674 2
16 14792.727 0.0009466772 0.0011852241 0.181146318 2
17 19693.636 -0.0007095856 -0.0021505871 0.033593673 2
18 24594.545 -0.0011145670 -0.0034750316 -0.364072631 2
19 29495.455 -0.0014069124 -0.0065805003 -0.433534999 2
20 34396.364 -0.0021987173 -0.0086083808 -0.462098816 2
21 39297.273 -0.0080548883 -0.0088897627 -0.464983585 2
22 44198.182 -0.0086038271 -0.0114920192 -0.562709430 2
23 49099.091 -0.0094904993 -0.0169889702 -0.779278790 2
24 54000.000 -0.0119963261 -0.0174476608 -0.798253748 2
25 90.000 0.0116124758 0.0161232645 0.922819873 2
26 4990.909 0.0101439952 0.0158178170 0.895932709 2
27 9891.818 0.0037524900 0.0142452666 0.637269377 2
28 14792.727 0.0027126828 0.0136245822 0.526445379 2
29 19693.636 0.0016400717 0.0096431459 0.435870552 2
30 24594.545 0.0015504030 0.0089490379 0.125565872 2
31 29495.455 0.0005834194 0.0057726305 0.037152275 2
32 34396.364 -0.0003232792 0.0052165649 -0.383415339 2
33 39297.273 -0.0008013126 0.0042121379 -0.487264792 2
34 44198.182 -0.0072876859 -0.0043456288 -0.637663345 2
35 49099.091 -0.0077894144 -0.0047802446 -0.741686291 2
36 54000.000 -0.0130759449 -0.0064953867 -0.799718307 2
we would find the output like below:
> min_setnbr 2
13 90.000 0.0117878041 0.0158037641 0.854604177 2
14 4990.909 0.0056253446 0.0152247614 0.681014064 2
15 9891.818 0.0014885119 0.0111993956 0.565702674 2
16 14792.727 0.0009466772 0.0011852241 0.181146318 2
17 19693.636 -0.0007095856 -0.0021505871 0.033593673 2
18 24594.545 -0.0011145670 -0.0034750316 -0.364072631 2
19 29495.455 -0.0014069124 -0.0065805003 -0.433534999 2
20 34396.364 -0.0021987173 -0.0086083808 -0.462098816 2
21 39297.273 -0.0080548883 -0.0088897627 -0.464983585 2
22 44198.182 -0.0086038271 -0.0114920192 -0.562709430 2
23 49099.091 -0.0094904993 -0.0169889702 -0.779278790 2
24 54000.000 -0.0119963261 -0.0174476608 -0.798253748 2
finally, can we bind res
outputs with ordering set_nbr=1
group_min
-> group_max
, set_nbr=2
group_min
-> group_max
..... and so on
time Mx My Mz set_nbr group_min
##1 90.000 0.0105615570 0.0128378518 0.92123599 1 1
##2 4990.909 0.0096134025 0.0117695944 0.78439667 1 1
##3 9891.818 0.0093581318 0.0115742493 0.72867894 1 1
##4 14792.727 0.0031807426 0.0113173105 0.55464140 1 1
##5 19693.636 0.0023569651 0.0089484378 0.42502936 1 1
##6 24594.545 0.0008941874 0.0058824078 -0.04729751 1 1
##7 29495.455 -0.0043247786 0.0021214525 -0.13068103 1 1
##8 34396.364 -0.0070967748 0.0011887832 -0.20001126 1 1
##9 39297.273 -0.0086446611 -0.0009107974 -0.22002091 1 1
##10 44198.182 -0.0087562698 -0.0035490228 -0.30663302 1 1
##11 49099.091 -0.0094095244 -0.0156822550 -0.33245014 1 1
##12 54000.000 -0.0123935570 -0.0190667519 -0.34929570 1 1
time Mx My Mz set_nbr group_max
##13 90.000 0.0105615570 0.0128378518 0.92123599 1 3
##14 4990.909 0.0096134025 0.0117695944 0.78439667 1 3
##15 9891.818 0.0093581318 0.0115742493 0.72867894 1 3
##16 14792.727 0.0031807426 0.0113173105 0.55464140 1 3
##17 19693.636 0.0023569651 0.0089484378 0.42502936 1 3
##18 24594.545 0.0008941874 0.0058824078 0.04729751 1 3
##19 29495.455 -0.0043247786 0.0021214525 0.13068103 1 3
##20 34396.364 -0.0070967748 0.0011887832 -0.20001126 1 3
##21 39297.273 -0.0086446611 -0.0009107974 -0.22002091 1 3
##22 44198.182 -0.0087562698 -0.0035490228 -0.30663302 1 3
##23 49099.091 -0.0094095244 -0.0156822550 -0.33245014 1 3
##24 54000.000 -0.0123935570 -0.0190667519 -0.34929570 1 3
> set_nbr 2 group_min
group_max
> set_nbr 3 group_min
group_max
..
UPDATE
in addition to @akrun answer, it is useful to use
Rows <- x[ceiling(x$Mz-y$Mz)==0,]
in case of you have different length of datasets.
Try