Paste multiple columns (strange behaviour)
3
I'm trying to paste several columns with the same name each into a new row but I get some strange behaviour. Example:
x <- data.frame(x = 1:10, y= 2:11, z= 11:20)
colnames(x) <- c("x", "y", "x")
x
> x
x y x
1 1 2 11
2 2 3 12
3 3 4 13
4 4 5 14
5 5 6 15
6 6 7 16
7 7 8 17
8 8 9 18
9 9 10 19
10 10 11 20
# now I try to paste columns to rows
> x2 <- data.frame(columns = unique(colnames(x)),
+ values = sapply(1:length(unique(colnames(x))), function(i)
+ paste(x[,(which(unique(colnames(x))[i]==colnames(x)))], collapse = ", ")))
> x2
columns values
1 x 1:10, 11:20
2 y 2, 3, 4, 5, 6, 7, 8, 9, 10, 11
What I wanted to have is just
> x2
columns values
1 x 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20
2 y 2, 3, 4, 5, 6, 7, 8, 9, 10, 11
Could somebody help me preventing this behaviour?
r
edited Nov 13 '18 at 5:10
Cœur
17.6k9105145
asked Mar 6 '17 at 18:36
JBGruberJBGruber
1,580620
add a comment |
3
I'm trying to paste several columns with the same name each into a new row but I get some strange behaviour. Example:
x <- data.frame(x = 1:10, y= 2:11, z= 11:20)
colnames(x) <- c("x", "y", "x")
x
> x
x y x
1 1 2 11
2 2 3 12
3 3 4 13
4 4 5 14
5 5 6 15
6 6 7 16
7 7 8 17
8 8 9 18
9 9 10 19
10 10 11 20
# now I try to paste columns to rows
> x2 <- data.frame(columns = unique(colnames(x)),
+ values = sapply(1:length(unique(colnames(x))), function(i)
+ paste(x[,(which(unique(colnames(x))[i]==colnames(x)))], collapse = ", ")))
> x2
columns values
1 x 1:10, 11:20
2 y 2, 3, 4, 5, 6, 7, 8, 9, 10, 11
What I wanted to have is just
> x2
columns values
1 x 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20
2 y 2, 3, 4, 5, 6, 7, 8, 9, 10, 11
Could somebody help me preventing this behaviour?
r
edited Nov 13 '18 at 5:10
Cœur
17.6k9105145
asked Mar 6 '17 at 18:36
JBGruberJBGruber
1,580620
1
As a note, there is no need to callunique(colnames(x))so many times; you could save in a variable instead. Also, if you don't need this task for a specific formatting, you might consider avoiding coercing to "character" andpasteing --aggregate(cbind(values = unlist(x, use.names = FALSE)) ~ rep(names(x), each = nrow(x)), FUN = c). Finally, you are passing a "list" of "integer"s (columns named "x") topastewhich, implicitly, usesas.characteron this "list" and the result is because of howas.charactertreats "list" arguments --as.character(list(1:5))
– alexis_laz
Mar 6 '17 at 20:22
Thanks that was a really helpful explanation! I use paste since my real data is actually text but it still makes sense.
– JBGruber
Mar 9 '17 at 8:20
add a comment |
3
3
3
I'm trying to paste several columns with the same name each into a new row but I get some strange behaviour. Example:
x <- data.frame(x = 1:10, y= 2:11, z= 11:20)
colnames(x) <- c("x", "y", "x")
x
> x
x y x
1 1 2 11
2 2 3 12
3 3 4 13
4 4 5 14
5 5 6 15
6 6 7 16
7 7 8 17
8 8 9 18
9 9 10 19
10 10 11 20
# now I try to paste columns to rows
> x2 <- data.frame(columns = unique(colnames(x)),
+ values = sapply(1:length(unique(colnames(x))), function(i)
+ paste(x[,(which(unique(colnames(x))[i]==colnames(x)))], collapse = ", ")))
> x2
columns values
1 x 1:10, 11:20
2 y 2, 3, 4, 5, 6, 7, 8, 9, 10, 11
What I wanted to have is just
> x2
columns values
1 x 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20
2 y 2, 3, 4, 5, 6, 7, 8, 9, 10, 11
Could somebody help me preventing this behaviour?
r
edited Nov 13 '18 at 5:10
Cœur
17.6k9105145
asked Mar 6 '17 at 18:36
JBGruberJBGruber
1,580620
I'm trying to paste several columns with the same name each into a new row but I get some strange behaviour. Example:
x <- data.frame(x = 1:10, y= 2:11, z= 11:20)
colnames(x) <- c("x", "y", "x")
x
> x
x y x
1 1 2 11
2 2 3 12
3 3 4 13
4 4 5 14
5 5 6 15
6 6 7 16
7 7 8 17
8 8 9 18
9 9 10 19
10 10 11 20
# now I try to paste columns to rows
> x2 <- data.frame(columns = unique(colnames(x)),
+ values = sapply(1:length(unique(colnames(x))), function(i)
+ paste(x[,(which(unique(colnames(x))[i]==colnames(x)))], collapse = ", ")))
> x2
columns values
1 x 1:10, 11:20
2 y 2, 3, 4, 5, 6, 7, 8, 9, 10, 11
What I wanted to have is just
> x2
columns values
1 x 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20
2 y 2, 3, 4, 5, 6, 7, 8, 9, 10, 11
Could somebody help me preventing this behaviour?
r
r
edited Nov 13 '18 at 5:10
Cœur
17.6k9105145
asked Mar 6 '17 at 18:36
JBGruberJBGruber
1,580620
edited Nov 13 '18 at 5:10
Cœur
17.6k9105145
asked Mar 6 '17 at 18:36
JBGruberJBGruber
1,580620
edited Nov 13 '18 at 5:10
Cœur
17.6k9105145
edited Nov 13 '18 at 5:10
Cœur
17.6k9105145
edited Nov 13 '18 at 5:10
Cœur
17.6k9105145
17.6k9105145
asked Mar 6 '17 at 18:36
JBGruberJBGruber
1,580620
asked Mar 6 '17 at 18:36
JBGruberJBGruber
1,580620
asked Mar 6 '17 at 18:36
JBGruberJBGruber
1,580620
1,580620
1
As a note, there is no need to callunique(colnames(x))so many times; you could save in a variable instead. Also, if you don't need this task for a specific formatting, you might consider avoiding coercing to "character" andpasteing --aggregate(cbind(values = unlist(x, use.names = FALSE)) ~ rep(names(x), each = nrow(x)), FUN = c). Finally, you are passing a "list" of "integer"s (columns named "x") topastewhich, implicitly, usesas.characteron this "list" and the result is because of howas.charactertreats "list" arguments --as.character(list(1:5))
– alexis_laz
Mar 6 '17 at 20:22
Thanks that was a really helpful explanation! I use paste since my real data is actually text but it still makes sense.
– JBGruber
Mar 9 '17 at 8:20
add a comment |
1
As a note, there is no need to callunique(colnames(x))so many times; you could save in a variable instead. Also, if you don't need this task for a specific formatting, you might consider avoiding coercing to "character" andpasteing --aggregate(cbind(values = unlist(x, use.names = FALSE)) ~ rep(names(x), each = nrow(x)), FUN = c). Finally, you are passing a "list" of "integer"s (columns named "x") topastewhich, implicitly, usesas.characteron this "list" and the result is because of howas.charactertreats "list" arguments --as.character(list(1:5))
– alexis_laz
Mar 6 '17 at 20:22
Thanks that was a really helpful explanation! I use paste since my real data is actually text but it still makes sense.
– JBGruber
Mar 9 '17 at 8:20
1
1
As a note, there is no need to call
unique(colnames(x)) so many times; you could save in a variable instead. Also, if you don't need this task for a specific formatting, you might consider avoiding coercing to "character" and pasteing -- aggregate(cbind(values = unlist(x, use.names = FALSE)) ~ rep(names(x), each = nrow(x)), FUN = c). Finally, you are passing a "list" of "integer"s (columns named "x") to paste which, implicitly, uses as.character on this "list" and the result is because of how as.character treats "list" arguments -- as.character(list(1:5))– alexis_laz
Mar 6 '17 at 20:22
As a note, there is no need to call
unique(colnames(x)) so many times; you could save in a variable instead. Also, if you don't need this task for a specific formatting, you might consider avoiding coercing to "character" and pasteing -- aggregate(cbind(values = unlist(x, use.names = FALSE)) ~ rep(names(x), each = nrow(x)), FUN = c). Finally, you are passing a "list" of "integer"s (columns named "x") to paste which, implicitly, uses as.character on this "list" and the result is because of how as.character treats "list" arguments -- as.character(list(1:5))– alexis_laz
Mar 6 '17 at 20:22
Thanks that was a really helpful explanation! I use paste since my real data is actually text but it still makes sense.
– JBGruber
Mar 9 '17 at 8:20
Thanks that was a really helpful explanation! I use paste since my real data is actually text but it still makes sense.
– JBGruber
Mar 9 '17 at 8:20
add a comment |
1 Answer
1
active
oldest
votes
0
x <- data.frame(x = 1:10, y= 2:11, z= 11:20)
colnames(x) <- c("x", "y", "x")
unique_cols <- unique(colnames(x))
x2 <- sapply(unique_cols, function(s) unlist(x[, unique_cols == s], use.names = F))
x2
$x
[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
$y
[1] 2 3 4 5 6 7 8 9 10 11
and
typeof(x2)
[1] "list"
in case you need a dataframe with the collapsed values:
df <- data.frame(columns = unique_cols,
value = as.character(sapply(x2, function(s) paste(s, collapse = ","), USE.NAMES = F)))
df
columns value
1 x 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20
2 y 2,3,4,5,6,7,8,9,10,11
answered Mar 6 '17 at 18:55
CodutieCodutie
806414
Worked like a charm :)
– JBGruber
Mar 9 '17 at 8:16
add a comment |
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x <- data.frame(x = 1:10, y= 2:11, z= 11:20)
colnames(x) <- c("x", "y", "x")
unique_cols <- unique(colnames(x))
x2 <- sapply(unique_cols, function(s) unlist(x[, unique_cols == s], use.names = F))
x2
$x
[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
$y
[1] 2 3 4 5 6 7 8 9 10 11
and
typeof(x2)
[1] "list"
in case you need a dataframe with the collapsed values:
df <- data.frame(columns = unique_cols,
value = as.character(sapply(x2, function(s) paste(s, collapse = ","), USE.NAMES = F)))
df
columns value
1 x 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20
2 y 2,3,4,5,6,7,8,9,10,11
answered Mar 6 '17 at 18:55
CodutieCodutie
806414
Worked like a charm :)
– JBGruber
Mar 9 '17 at 8:16
add a comment |
0
x <- data.frame(x = 1:10, y= 2:11, z= 11:20)
colnames(x) <- c("x", "y", "x")
unique_cols <- unique(colnames(x))
x2 <- sapply(unique_cols, function(s) unlist(x[, unique_cols == s], use.names = F))
x2
$x
[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
$y
[1] 2 3 4 5 6 7 8 9 10 11
and
typeof(x2)
[1] "list"
in case you need a dataframe with the collapsed values:
df <- data.frame(columns = unique_cols,
value = as.character(sapply(x2, function(s) paste(s, collapse = ","), USE.NAMES = F)))
df
columns value
1 x 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20
2 y 2,3,4,5,6,7,8,9,10,11
answered Mar 6 '17 at 18:55
CodutieCodutie
806414
Worked like a charm :)
– JBGruber
Mar 9 '17 at 8:16
add a comment |
0
0
0
x <- data.frame(x = 1:10, y= 2:11, z= 11:20)
colnames(x) <- c("x", "y", "x")
unique_cols <- unique(colnames(x))
x2 <- sapply(unique_cols, function(s) unlist(x[, unique_cols == s], use.names = F))
x2
$x
[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
$y
[1] 2 3 4 5 6 7 8 9 10 11
and
typeof(x2)
[1] "list"
in case you need a dataframe with the collapsed values:
df <- data.frame(columns = unique_cols,
value = as.character(sapply(x2, function(s) paste(s, collapse = ","), USE.NAMES = F)))
df
columns value
1 x 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20
2 y 2,3,4,5,6,7,8,9,10,11
answered Mar 6 '17 at 18:55
CodutieCodutie
806414
x <- data.frame(x = 1:10, y= 2:11, z= 11:20)
colnames(x) <- c("x", "y", "x")
unique_cols <- unique(colnames(x))
x2 <- sapply(unique_cols, function(s) unlist(x[, unique_cols == s], use.names = F))
x2
$x
[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
$y
[1] 2 3 4 5 6 7 8 9 10 11
and
typeof(x2)
[1] "list"
in case you need a dataframe with the collapsed values:
df <- data.frame(columns = unique_cols,
value = as.character(sapply(x2, function(s) paste(s, collapse = ","), USE.NAMES = F)))
df
columns value
1 x 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20
2 y 2,3,4,5,6,7,8,9,10,11
answered Mar 6 '17 at 18:55
CodutieCodutie
806414
edited Mar 6 '17 at 19:10
answered Mar 6 '17 at 18:55
CodutieCodutie
806414
answered Mar 6 '17 at 18:55
CodutieCodutie
806414
answered Mar 6 '17 at 18:55
CodutieCodutie
806414
806414
Worked like a charm :)
– JBGruber
Mar 9 '17 at 8:16
add a comment |
Worked like a charm :)
– JBGruber
Mar 9 '17 at 8:16
Worked like a charm :)
– JBGruber
Mar 9 '17 at 8:16
Worked like a charm :)
– JBGruber
Mar 9 '17 at 8:16
add a comment |
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1
As a note, there is no need to call
unique(colnames(x))so many times; you could save in a variable instead. Also, if you don't need this task for a specific formatting, you might consider avoiding coercing to "character" andpasteing --aggregate(cbind(values = unlist(x, use.names = FALSE)) ~ rep(names(x), each = nrow(x)), FUN = c). Finally, you are passing a "list" of "integer"s (columns named "x") topastewhich, implicitly, usesas.characteron this "list" and the result is because of howas.charactertreats "list" arguments --as.character(list(1:5))– alexis_laz
Mar 6 '17 at 20:22
Thanks that was a really helpful explanation! I use paste since my real data is actually text but it still makes sense.
– JBGruber
Mar 9 '17 at 8:20