Subseting multiple object in R without specifying all of them - r

Question

Let's assume we somehow ended up with data frame object (T2 in below example) and we want to subset our original data with that dataframe. Is there a way to do without using | in subset object?
Here is a dataset I was playing but failed
education = read.csv("https://vincentarelbundock.github.io/Rdatasets/csv/robustbase/education.csv", stringsAsFactors = FALSE)
colnames(education) = c("X", "State", "Region", "Urban.Population", "Per.Capita.Income", "Minor.Population", "Education.Expenditures")
head(education)
T1 = c(1,4,13,15,17,23,33,38)
T2 = education[T1,]$State
subset(education, State=="ME"| State=="MA" | State=="MI" | State=="MN" | State=="MO" | State=="MD" | State=="MS" | State=="MT")
subset(education, State==T2[3])
subset(education, State==T2)
PS: I created T2 as states starting with M but I don't want using string or anything. Just assume we somehow ended up with T2 in which outputs are some states.

Answer 1

I'm not quite sure what would be an acceptable answer but subset(education, State %in% T2) uses T2 as is and does not use |. Does this solve your problem? It's almost the same approach as Jon Spring points out in the comments, but instead of specifying a vector we can just use T2 with %in%. You say T2 is a data.frame object, but in the data you provided it turns out to be a character vector.
education = read.csv("https://vincentarelbundock.github.io/Rdatasets/csv/robustbase/education.csv", stringsAsFactors = FALSE)
colnames(education) = c("X", "State", "Region", "Urban.Population", "Per.Capita.Income", "Minor.Population", "Education.Expenditures")
T1 = c(1,4,13,15,17,23,33,38)
T2 = education[T1,]$State
T2 # T2 is not a data.frame object (R 4.0)
#> [1] "ME" "MA" "MI" "MN" "MO" "MD" "MS" "MT"
subset(education, State %in% T2)
#> X State Region Urban.Population Per.Capita.Income Minor.Population
#> 1 1 ME 1 508 3944 325
#> 4 4 MA 1 846 5233 305
#> 13 13 MI 2 738 5439 337
#> 15 15 MN 2 664 4921 330
#> 17 17 MO 2 701 4672 309
#> 23 23 MD 3 766 5331 323
#> 33 33 MS 3 445 3448 358
#> 38 38 MT 4 534 4418 335
#> Education.Expenditures
#> 1 235
#> 4 261
#> 13 379
#> 15 378
#> 17 231
#> 23 330
#> 33 215
#> 38 302
But lets say T2 would be an actual data.frame:
T2 = education[T1,]["State"]
T2 #check
#> State
#> 1 ME
#> 4 MA
#> 13 MI
#> 15 MN
#> 17 MO
#> 23 MD
#> 33 MS
#> 38 MT
Then we could coerce it into a vector by subsetting it with drop = TRUE.
subset(education, State %in% T2[, , drop = TRUE])
#> X State Region Urban.Population Per.Capita.Income Minor.Population
#> 1 1 ME 1 508 3944 325
#> 4 4 MA 1 846 5233 305
#> 13 13 MI 2 738 5439 337
#> 15 15 MN 2 664 4921 330
#> 17 17 MO 2 701 4672 309
#> 23 23 MD 3 766 5331 323
#> 33 33 MS 3 445 3448 358
#> 38 38 MT 4 534 4418 335
#> Education.Expenditures
#> 1 235
#> 4 261
#> 13 379
#> 15 378
#> 17 231
#> 23 330
#> 33 215
#> 38 302
Created on 2021-06-12 by the reprex package (v0.3.0)