Using Row-Wise Column Indices in a Vector to Extract Values from Data Frame

Using row-wise column indices in a vector to extract values from data frame

Just use matrix indexing, like this:

dframe[cbind(seq_along(i), i)]
# [1] "g" "b" "f"

The cbind(seq_along(i), i) part creates a two column matrix of the relevant row and column that you want to extract.

Extract different col in every row of an R data.frame

x <- data.frame(a=c(1,2,3), b=c(3,2,1), c=c(5,6,4))
cols <- c("c", "a", "b")

sapply(1:length(cols),function(i){x[i,cols[i]]})
[1] 5 2 1

Using row-wise column indices in a vector to extract values from data frame

Just use matrix indexing, like this:

dframe[cbind(seq_along(i), i)]
# [1] "g" "b" "f"

The cbind(seq_along(i), i) part creates a two column matrix of the relevant row and column that you want to extract.

Index values from a matrix using row, col indices

Almost. Needs to be offered to "[" as a two column matrix:

dat$matval <- mat[ cbind(dat$I, dat$J) ] # should do it.

There is a caveat: Although this also works for dataframes, they are first coerced to matrix-class and if any are non-numeric, the entire matrix becomes the "lowest denominator" class.

Column-wise element selection in R

We can use :

df[cbind(vec, 1:ncol(df))]
#[1] 1 4 5

Using cbind, we create a row and column index to subset values from df.

cbind(vec, 1:ncol(df))
      vec  
#[1,]   1 1
#[2,]   2 2
#[3,]   1 3

Using this matrix, we subset values from (row 1, column1), (row2, column2) and row(1, column3).

Extract all column values row-wise by a particular row name in R

We can use == to return a logical vector and then it can be used to subset the rows.

M[rownames(M)=='B00813GRG4',, drop=FALSE]
#            V1              
# B00813GRG4 "A1D87F6ZCVE5NK"
# B00813GRG4 "ABXLMWJIXXAIN" 

using the 'B00813GRG4' as row index will return only the first matching element similar to using match.

 M[match('B00813GRG4', rownames(M)),, drop=FALSE]
 #           V1              
 #B00813GRG4 "A1D87F6ZCVE5NK"

Selecting data frame value basing on the vectors

apply family in base R

One way to do it is to use sapply to go through all rows in your query data frame, and use the row and col info of each row to index the mtcars dataset.

EDIT: Credit to @Darren Tsai for providing the mapply solution.

library(dplyr)

data.frame(row = c(1, 3, 5),
                 col = c('mpg', 'cyl', 'disp')) %>% 
  mutate(value = sapply(1:nrow(.), \(x) mtcars[.[x, 1], .[x, 2]]))
  # or mapply
  mutate(value = mapply(\(x, y) mtcars[x, y], row, col))

rowwise() from dplyr

Another way of doing it is to use rowwise():

library(dplyr)

data.frame(row = c(1, 3, 5),
           col = c('mpg', 'cyl', 'disp')) %>% 
  rowwise() %>% 
  mutate(value = mtcars[row, col]) %>%
  ungroup()

Output

    row col   value
1     1 mpg      21
2     3 cyl       4
3     5 disp    360

Extract columns using int array values as index from a data

Following worked for me diabetes_test[,model,with=FALSE]. Read https://cran.r-project.org/web/packages/data.table/vignettes/datatable-faq.html and the help page of the data.table package ?data.table

accessing the first value of the vector in dataframe R

You could loop through the vector using sapply and extracting the first value:

df$Fees <- sapply(df$Fees, "[[", 1)

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