The question is how to use a column on a tibble to select the whole row. The code below shows what I normally do using basic R functions to index rows I want to eliminate form the data frame dataMet. I was wondering if I can use tidyverse functions on a tibble to get the same results. Thanks!
outL <- c("S11", "S156", "S302")
index <- match(outL, rownames(dataMet))
# Print Outliers
outL
dataMet[index,]
# Remove Outliers
dataMet <- dataMet[-index,]
EDIT: to clarify, I want to conduct this operation without using rownames. Instead, I want to subset the data according to matches between a vector and a column.
More options
library(dplyr)
mydata <- data.frame(col1 = letters[1:10],
col2 = 1:10)
slice(mydata, c(1, 3, 5))
#> col1 col2
#> 1 a 1
#> 2 c 3
#> 3 e 5
slice(mydata, c(-1, -3, -5))
#> col1 col2
#> 1 b 2
#> 2 d 4
#> 3 f 6
#> 4 g 7
#> 5 h 8
#> 6 i 9
#> 7 j 10
mydata$rownumber <- 1:nrow(mydata)
mydata$crownumber <- as.character(1:nrow(mydata))
str(mydata)
#> 'data.frame': 10 obs. of 4 variables:
#> $ col1 : chr "a" "b" "c" "d" ...
#> $ col2 : int 1 2 3 4 5 6 7 8 9 10
#> $ rownumber : int 1 2 3 4 5 6 7 8 9 10
#> $ crownumber: chr "1" "2" "3" "4" ...
myvector <- c(1, 2, 5)
mycvector <- c("6", "4", "8")
mydata %>% filter(col2 %in% myvector)
#> col1 col2 rownumber crownumber
#> 1 a 1 1 1
#> 2 b 2 2 2
#> 3 e 5 5 5
mydata %>% filter(col2 %in% mycvector)
#> col1 col2 rownumber crownumber
#> 1 d 4 4 4
#> 2 f 6 6 6
#> 3 h 8 8 8