I have a list (my.list) that looks like this:
> my.list
$S1
A B C D
1 101027 NA C1 NA
2 101031 1.5 PTA 0.8666667
3 101032 1.4 C1 0.5571429
4 101127 NA PTA NA
5 101220 9.3 C1 0.7849462
$S2
A B C D
1 102142 NA C1 NA
2 102143 0.70 PTA 1.7142857
3 102144 NA C1 2.7257000
4 102148 0.45 PTA NA
5 102151 0.91 C1 0.7032967
6 102152 0.78 PTA NA
I want to remove the rows that are 'NA' in column D, but only if they are also 'PTA' in Column C.
My desired output would look like this:
> my.list
$S1
A B C D
1 101027 NA C1 NA
2 101031 1.5 PTA 0.8666667
3 101032 1.4 C1 0.5571429
4 101220 9.3 C1 0.7849462
$S2
A B C D
1 102142 NA C1 NA
2 102143 0.70 PTA 1.7142857
3 102144 NA C1 2.7257000
4 102151 0.91 C1 0.7032967
How can I go about doing this?
Reproducible Data:
my.list <- structure(list(S1 = structure(list(A = c(101027L, 101031L, 101032L,
101127L, 101220L), B = c(NA, 1.5, 1.4, NA, 9.3), C = c("C1", "PTA", "C1", "PTA", "C1", "PTA"), D = c(NA, 0.8666667, 0.5571429, NA, 0.7849462
)), .Names = c("A", "B", "C", "D"), class = "data.frame", row.names = c("1",
"2", "3", "4", "5")), S2 = structure(list(A = c(102142L, 102143L,
102144L, 102148L, 102151L, 102152L), B = c(NA, 0.7, NA, 0.45,
0.91, 0.78), C = c("C1", "PTA", "C1", "PTA", "C1", "PTA"), D = c(NA,
1.7142857, 2.7257, NA, 0.7032967, NA)), .Names = c("A", "B", "C",
"D"), class = "data.frame", row.names = c("1", "2", "3", "4",
"5", "6"))), .Names = c("S1", "S2"))
CodePudding user response:
Using lapply
, and subsetting with simple logical tests:
lapply(my.list, function(x) x[!(is.na(x$D) & x$C == "PTA"),])
#> $S1
#> A B C D
#> 1 101027 NA C1 NA
#> 2 101031 1.5 PTA 0.8666667
#> 3 101032 1.4 C1 0.5571429
#> 5 101220 9.3 C1 0.7849462
#>
#> $S2
#> A B C D
#> 1 102142 NA C1 NA
#> 2 102143 0.70 PTA 1.7142857
#> 3 102144 NA C1 2.7257000
#> 5 102151 0.91 C1 0.7032967
Created on 2022-06-16 by the reprex package (v2.0.1)
CodePudding user response:
Or with subset
lapply(my.list, subset, subset = !(is.na(D) & C == 'PTA'))
-output
$S1
A B C D
1 101027 NA C1 NA
2 101031 1.5 PTA 0.8666667
3 101032 1.4 C1 0.5571429
5 101220 9.3 C1 0.7849462
$S2
A B C D
1 102142 NA C1 NA
2 102143 0.70 PTA 1.7142857
3 102144 NA C1 2.7257000
5 102151 0.91 C1 0.7032967