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问题:
rbind does not check for column names when binding together vectors:
l = list(row1 = c(10, 20), row2 = c(20, 10))
names(l$row1) = c("A", "B")
names(l$row2) = c("B", "A")
l
$row1
A B
10 20
$row2
B A
20 10
rbind(l$row1, l$row2)
A B
[1,] 10 20
[2,] 20 10
How can I produce this matrix from a number of list elements, insuring the column names are correctly matched across rows:
A B
[1,] 10 20
[2,] 10 20
回答1:
You can use match
:
l <- list(row1 = setNames(1:3, c("A", "B", "C")),
row2 = setNames(1:3, c("B", "C", "A")),
row3 = setNames(1:3, c("C", "A", "B")))
do.call(rbind, lapply(l, function(x) x[match(names(l[[1]]), names(x))]))
The result:
A B C
row1 1 2 3
row2 3 1 2
row3 2 3 1
回答2:
smartbind()
will match column names and tolerates missing ones:
library(gtools)
do.call(smartbind,l)
A B
row1 10 20
row2 10 20
回答3:
It seems that in current versions of R (I have version 3.3.0), rbind
has the capacity to to join two data sets with the same name columns even if they are in different order.
df1 <- data.frame(a = c(1:5), c = c(LETTERS[1:5]),b=c(11:15))
df2 <- data.frame(a = c(6:10), b = c(16:20),c=c(LETTERS[6:10]))
rbind(df1,df2)
a c b
1 1 A 11
2 2 B 12
3 3 C 13
4 4 D 14
5 5 E 15
6 6 F 16
7 7 G 17
8 8 H 18
9 9 I 19
10 10 J 20
回答4:
rbind
will work if you first change each element of l to a data frame:
do.call("rbind", lapply(l, function(x) data.frame(as.list(x))))
A B
row1 10 20
row2 10 20
回答5:
do.call(rbind, lapply(l, function(row) row[order(names(row))]))
回答6:
Why not just rbind(l$row1, l$row2[names(l$row1)])
. Also works well for data frames. Note that this will discard columns from l$row2
that don't appear in l$row1
.
回答7:
Reduce is a powerful function, but some how not frequently used ; here's an alternate implementation
This will create a rbind where if there are columns that don't match "NA" will be generated for them.
rbindedFrame = Reduce(custom_rbind,listofDataframes)
custom_rbind = function(x1,x2){
c1 = setdiff(colnames(x1),colnames(x2))
c2 = setdiff(colnames(x2),colnames(x1))
for(c in c2){##Adding missing columns from 2 in 1
x1[[c]]=NA
}
for(c in c1){##Similiarly ading missing from 1 in 2
x2[[c]]=NA
}
x2 = x2[colnames(x1)]
rbind(x1,x2)
}
}