R How to Extract First Row of Each Matrix Within a List

R How do I extract first row of each matrix within a list?

Or,

lapply(mylist_1, `[`,1,)
lapply(mylist_1, `[`,2,)

Get access to the first row of a list in R

 A=list()
 A[[1]]=c(1,2)
 A[[2]]=c(3,4)
 A[[3]]=c(5,6)

 A
 # [[1]]
 # [1] 1 2

 # [[2]]
 # [1] 3 4

 # [[3]]
 # [1] 5 6

I. First Solution using sapply() function for just first elements

 sapply(A,'[[',1)
 # [1] 1 3 5

For Getting lets say 1st, 3rd, 4th elements of each nested list. Not applicable in this example

 sapply(A,`[`,c(1,3,4))

II. Second Solution using for loop

 for(i in 1:length(A)){
 print (A[[i]][1])
 }
 # [1] 1
 # [1] 3
 # [1] 5

Extract row from a matrix in a list in R

Or like this?

set.seed(123)
list1 <- list(replicate(4,rnorm(2)))
l<-rep(list1,3)
lapply(l,function(x) x[2,])

Select n first rows of a matrix

Use the head function:

head(mat, 100)

Extract the first TRUE per row in logical matrix efficiently in R

We can use max.col

colnames(m)[max.col(m, "first")]
#[1] "A" "B" "C" "B" "B" "A"

If there are no TRUE in a row, then we can change it to NA (if needed)

colnames(m)[max.col(m, "first")*NA^!rowSums(m)]

Or with ifelse

colnames(m)[ifelse(rowSums(m)==0, NA, max.col(m, "first"))]

extract one element/data frame from a list of lists

So after messing around, the answer seems to be very simple: `results1<-cj1["coefficients",]. This creates the list that I want. Akrun, if you read this, thank you for your support.

Select the first row by group

You can use duplicated to do this very quickly.

test[!duplicated(test$id),]

Benchmarks, for the speed freaks:

ju <- function() test[!duplicated(test$id),]
gs1 <- function() do.call(rbind, lapply(split(test, test$id), head, 1))
gs2 <- function() do.call(rbind, lapply(split(test, test$id), `[`, 1, ))
jply <- function() ddply(test,.(id),function(x) head(x,1))
jdt <- function() {
  testd <- as.data.table(test)
  setkey(testd,id)
  # Initial solution (slow)
  # testd[,lapply(.SD,function(x) head(x,1)),by = key(testd)]
  # Faster options :
  testd[!duplicated(id)]               # (1)
  # testd[, .SD[1L], by=key(testd)]    # (2)
  # testd[J(unique(id)),mult="first"]  # (3)
  # testd[ testd[,.I[1L],by=id] ]      # (4) needs v1.8.3. Allows 2nd, 3rd etc
}

library(plyr)
library(data.table)
library(rbenchmark)

# sample data
set.seed(21)
test <- data.frame(id=sample(1e3, 1e5, TRUE), string=sample(LETTERS, 1e5, TRUE))
test <- test[order(test$id), ]

benchmark(ju(), gs1(), gs2(), jply(), jdt(),
    replications=5, order="relative")[,1:6]
#     test replications elapsed relative user.self sys.self
# 1   ju()            5    0.03    1.000      0.03     0.00
# 5  jdt()            5    0.03    1.000      0.03     0.00
# 3  gs2()            5    3.49  116.333      2.87     0.58
# 2  gs1()            5    3.58  119.333      3.00     0.58
# 4 jply()            5    3.69  123.000      3.11     0.51

Let's try that again, but with just the contenders from the first heat and with more data and more replications.

set.seed(21)
test <- data.frame(id=sample(1e4, 1e6, TRUE), string=sample(LETTERS, 1e6, TRUE))
test <- test[order(test$id), ]
benchmark(ju(), jdt(), order="relative")[,1:6]
#    test replications elapsed relative user.self sys.self
# 1  ju()          100    5.48    1.000      4.44     1.00
# 2 jdt()          100    6.92    1.263      5.70     1.15

extract specific rows from nested lists of class dist in r

Here is an example using minimal sample data based on mtcars

lst <- lapply(1:3, function(x) dist(mtcars[, 1:3]))

We now extract the last row of every distance matrix from lst

lapply(lst, function(x) { mat <- as.matrix(x); mat[nrow(mat), ] })
#[[1]]
#          Mazda RX4       Mazda RX4 Wag          Datsun 710      Hornet 4 Drive
#         39.0532969          39.0532969          13.0751673         137.0145978
#  Hornet Sportabout             Valiant          Duster 360           Merc 240D
#        239.0487189         104.0715619         239.1388927          25.8745048
#           Merc 230            Merc 280           Merc 280C          Merc 450SE
#         19.8494332          46.6947535          46.7816203         154.9323723
#         Merc 450SL         Merc 450SLC  Cadillac Fleetwood Lincoln Continental
#        154.9059392         154.9757400         351.1951025         339.2020047
#  Chrysler Imperial            Fiat 128         Honda Civic      Toyota Corolla
#        319.0954246          43.7068644          46.1853873          51.4418118
#      Toyota Corona    Dodge Challenger         AMC Javelin          Camaro Z28
#          0.9055385         197.1289172         183.1486828         229.1781185
#   Pontiac Firebird           Fiat X1-9       Porsche 914-2        Lotus Europa
#        279.0373452          42.4123803           4.6529560          27.4191539
#     Ford Pantera L        Ferrari Dino       Maserati Bora          Volvo 142E
#        230.1029335          24.1431150         180.1581527           0.0000000
#
#[[2]]
#          Mazda RX4       Mazda RX4 Wag          Datsun 710      Hornet 4 Drive
#         39.0532969          39.0532969          13.0751673         137.0145978
#  Hornet Sportabout             Valiant          Duster 360           Merc 240D
#        239.0487189         104.0715619         239.1388927          25.8745048
#           Merc 230            Merc 280           Merc 280C          Merc 450SE
#         19.8494332          46.6947535          46.7816203         154.9323723
#         Merc 450SL         Merc 450SLC  Cadillac Fleetwood Lincoln Continental
#        154.9059392         154.9757400         351.1951025         339.2020047
#  Chrysler Imperial            Fiat 128         Honda Civic      Toyota Corolla
#        319.0954246          43.7068644          46.1853873          51.4418118
#      Toyota Corona    Dodge Challenger         AMC Javelin          Camaro Z28
#          0.9055385         197.1289172         183.1486828         229.1781185
#   Pontiac Firebird           Fiat X1-9       Porsche 914-2        Lotus Europa
#        279.0373452          42.4123803           4.6529560          27.4191539
#     Ford Pantera L        Ferrari Dino       Maserati Bora          Volvo 142E
#        230.1029335          24.1431150         180.1581527           0.0000000
#
#[[3]]
#          Mazda RX4       Mazda RX4 Wag          Datsun 710      Hornet 4 Drive
#         39.0532969          39.0532969          13.0751673         137.0145978
#  Hornet Sportabout             Valiant          Duster 360           Merc 240D
#        239.0487189         104.0715619         239.1388927          25.8745048
#           Merc 230            Merc 280           Merc 280C          Merc 450SE
#         19.8494332          46.6947535          46.7816203         154.9323723
#         Merc 450SL         Merc 450SLC  Cadillac Fleetwood Lincoln Continental
#        154.9059392         154.9757400         351.1951025         339.2020047
#  Chrysler Imperial            Fiat 128         Honda Civic      Toyota Corolla
#        319.0954246          43.7068644          46.1853873          51.4418118
#      Toyota Corona    Dodge Challenger         AMC Javelin          Camaro Z28
#          0.9055385         197.1289172         183.1486828         229.1781185
#   Pontiac Firebird           Fiat X1-9       Porsche 914-2        Lotus Europa
#        279.0373452          42.4123803           4.6529560          27.4191539
#     Ford Pantera L        Ferrari Dino       Maserati Bora          Volvo 142E
#        230.1029335          24.1431150         180.1581527           0.0000000

Extract the first, second and last row that meets a criterion

Data table can help with this.
This is an edit off of Davids comment to move it into the answers as his approach is the correct way to do this.

library(data.table)
DT <- as.data.table(db)
DT[Weight >= 10][, .SD[c(1, 2, .N)], by = Class]

As as faster alternative also from David look at

 indx <- DT[Weight >= 10][, .I[c(1, 2, .N)], by = Class]$V1 ; DT[indx]

Which creates the wanted index using .I and then subsets DT based on those rows.