R data.table list output vs vector output
2
d <- structure(list(Name = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L), .Label = c("Aira", "Ben", "Cat"), class = "factor"), Month = c(1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L), Rate1 = c(12L, 18L, 19L, 53L, 22L, 19L, 22L, 67L, 45L), Rate2 = c(23L, 73L, 45L, 19L, 87L, 45L, 87L, 43L, 32L)), .Names = c("Name", "Month", "Rate1", "Rate2"), class = c("data.table", "data.frame"), row.names = c(NA, -9L))
> d
Name Month Rate1 Rate2
1: Aira 1 12 23
2: Aira 2 18 73
3: Aira 3 19 45
4: Ben 1 53 19
5: Ben 2 22 87
6: Ben 3 19 45
7: Cat 1 22 87
8: Cat 2 67 43
9: Cat 3 45 32
I have the above data.table and want to know the difference between the following two operations. I know .() is short for list and c() is a vector. What does data.table do with these two different syntax? All I can observe is that the first case resulted in two variables and the second case resulted in a single variable.
> d[, .(mean(Rate1), mean(Rate2)), by = Name]
Name V1 V2
1: Aira 16.33 47.00
2: Ben 31.33 50.33
3: Cat 44.67 54.00
and
> d[, c(mean(Rate1), mean(Rate2)), by = Name]
Name V1
1: Aira 16.33
2: Aira 47.00
3: Ben 31.33
4: Ben 50.33
5: Cat 44.67
6: Cat 54.00
r list data.table grouping aggregation
edited Nov 14 '18 at 22:45
Henrik
42.3k994110
asked Nov 14 '18 at 22:12
rosepark222rosepark222
1916
add a comment |
2
d <- structure(list(Name = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L), .Label = c("Aira", "Ben", "Cat"), class = "factor"), Month = c(1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L), Rate1 = c(12L, 18L, 19L, 53L, 22L, 19L, 22L, 67L, 45L), Rate2 = c(23L, 73L, 45L, 19L, 87L, 45L, 87L, 43L, 32L)), .Names = c("Name", "Month", "Rate1", "Rate2"), class = c("data.table", "data.frame"), row.names = c(NA, -9L))
> d
Name Month Rate1 Rate2
1: Aira 1 12 23
2: Aira 2 18 73
3: Aira 3 19 45
4: Ben 1 53 19
5: Ben 2 22 87
6: Ben 3 19 45
7: Cat 1 22 87
8: Cat 2 67 43
9: Cat 3 45 32
I have the above data.table and want to know the difference between the following two operations. I know .() is short for list and c() is a vector. What does data.table do with these two different syntax? All I can observe is that the first case resulted in two variables and the second case resulted in a single variable.
> d[, .(mean(Rate1), mean(Rate2)), by = Name]
Name V1 V2
1: Aira 16.33 47.00
2: Ben 31.33 50.33
3: Cat 44.67 54.00
and
> d[, c(mean(Rate1), mean(Rate2)), by = Name]
Name V1
1: Aira 16.33
2: Aira 47.00
3: Ben 31.33
4: Ben 50.33
5: Cat 44.67
6: Cat 54.00
r list data.table grouping aggregation
edited Nov 14 '18 at 22:45
Henrik
42.3k994110
asked Nov 14 '18 at 22:12
rosepark222rosepark222
1916
I'm still learningdata.table, but I had never thought to usec(...). Interesting to see that a summarizing function would return more than one row per group, I can see that as very useful in some circumstances. I'm not certain where your question is, though: your code is good at demonstrating the difference: in the.(...)case you get one row per group. I suspect the equivalent of your second command isd[, .(c(mean(Rate1), mean(Rate2))), by = Name], which might clear up why it returns a single column, each group with two rows.
– r2evans
Nov 14 '18 at 22:40
2
Please have a look at the nice vignette Introduction todata.table: "As long asjreturns a list, each element of the list becomes a column in the resultingdata.table"; "When there’s only one column or expression to refer to inj[...], we can drop the.()notation. This is purely for convenience." In your case, thec()concatenates the two means to one column.
– Henrik
Nov 14 '18 at 22:42
1
@r2evans - I supposej+by=are not strictly a summarizing function, but rather a flexible grouping capability. You can even return more rows than are in the original data.
– thelatemail
Nov 15 '18 at 0:04
Yes, @thelatemail, I'm gathering that. This is one key difference betweendata.tablesummarizing anddplyr::summarize, where it fails if the returned summary is other than length 1. Indplyr-land, I would have summarized with ado(...)block so that I can return more than 1, it's nice to not have to do something similar here.
– r2evans
Nov 15 '18 at 0:06
add a comment |
2
2
2
d <- structure(list(Name = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L), .Label = c("Aira", "Ben", "Cat"), class = "factor"), Month = c(1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L), Rate1 = c(12L, 18L, 19L, 53L, 22L, 19L, 22L, 67L, 45L), Rate2 = c(23L, 73L, 45L, 19L, 87L, 45L, 87L, 43L, 32L)), .Names = c("Name", "Month", "Rate1", "Rate2"), class = c("data.table", "data.frame"), row.names = c(NA, -9L))
> d
Name Month Rate1 Rate2
1: Aira 1 12 23
2: Aira 2 18 73
3: Aira 3 19 45
4: Ben 1 53 19
5: Ben 2 22 87
6: Ben 3 19 45
7: Cat 1 22 87
8: Cat 2 67 43
9: Cat 3 45 32
I have the above data.table and want to know the difference between the following two operations. I know .() is short for list and c() is a vector. What does data.table do with these two different syntax? All I can observe is that the first case resulted in two variables and the second case resulted in a single variable.
> d[, .(mean(Rate1), mean(Rate2)), by = Name]
Name V1 V2
1: Aira 16.33 47.00
2: Ben 31.33 50.33
3: Cat 44.67 54.00
and
> d[, c(mean(Rate1), mean(Rate2)), by = Name]
Name V1
1: Aira 16.33
2: Aira 47.00
3: Ben 31.33
4: Ben 50.33
5: Cat 44.67
6: Cat 54.00
r list data.table grouping aggregation
edited Nov 14 '18 at 22:45
Henrik
42.3k994110
asked Nov 14 '18 at 22:12
rosepark222rosepark222
1916
d <- structure(list(Name = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L), .Label = c("Aira", "Ben", "Cat"), class = "factor"), Month = c(1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L), Rate1 = c(12L, 18L, 19L, 53L, 22L, 19L, 22L, 67L, 45L), Rate2 = c(23L, 73L, 45L, 19L, 87L, 45L, 87L, 43L, 32L)), .Names = c("Name", "Month", "Rate1", "Rate2"), class = c("data.table", "data.frame"), row.names = c(NA, -9L))
> d
Name Month Rate1 Rate2
1: Aira 1 12 23
2: Aira 2 18 73
3: Aira 3 19 45
4: Ben 1 53 19
5: Ben 2 22 87
6: Ben 3 19 45
7: Cat 1 22 87
8: Cat 2 67 43
9: Cat 3 45 32
I have the above data.table and want to know the difference between the following two operations. I know .() is short for list and c() is a vector. What does data.table do with these two different syntax? All I can observe is that the first case resulted in two variables and the second case resulted in a single variable.
> d[, .(mean(Rate1), mean(Rate2)), by = Name]
Name V1 V2
1: Aira 16.33 47.00
2: Ben 31.33 50.33
3: Cat 44.67 54.00
and
> d[, c(mean(Rate1), mean(Rate2)), by = Name]
Name V1
1: Aira 16.33
2: Aira 47.00
3: Ben 31.33
4: Ben 50.33
5: Cat 44.67
6: Cat 54.00
r list data.table grouping aggregation
r list data.table grouping aggregation
edited Nov 14 '18 at 22:45
Henrik
42.3k994110
asked Nov 14 '18 at 22:12
rosepark222rosepark222
1916
edited Nov 14 '18 at 22:45
Henrik
42.3k994110
asked Nov 14 '18 at 22:12
rosepark222rosepark222
1916
edited Nov 14 '18 at 22:45
Henrik
42.3k994110
edited Nov 14 '18 at 22:45
Henrik
42.3k994110
edited Nov 14 '18 at 22:45
Henrik
42.3k994110
42.3k994110
asked Nov 14 '18 at 22:12
rosepark222rosepark222
1916
asked Nov 14 '18 at 22:12
rosepark222rosepark222
1916
asked Nov 14 '18 at 22:12
rosepark222rosepark222
1916
1916
I'm still learningdata.table, but I had never thought to usec(...). Interesting to see that a summarizing function would return more than one row per group, I can see that as very useful in some circumstances. I'm not certain where your question is, though: your code is good at demonstrating the difference: in the.(...)case you get one row per group. I suspect the equivalent of your second command isd[, .(c(mean(Rate1), mean(Rate2))), by = Name], which might clear up why it returns a single column, each group with two rows.
– r2evans
Nov 14 '18 at 22:40
2
Please have a look at the nice vignette Introduction todata.table: "As long asjreturns a list, each element of the list becomes a column in the resultingdata.table"; "When there’s only one column or expression to refer to inj[...], we can drop the.()notation. This is purely for convenience." In your case, thec()concatenates the two means to one column.
– Henrik
Nov 14 '18 at 22:42
1
@r2evans - I supposej+by=are not strictly a summarizing function, but rather a flexible grouping capability. You can even return more rows than are in the original data.
– thelatemail
Nov 15 '18 at 0:04
Yes, @thelatemail, I'm gathering that. This is one key difference betweendata.tablesummarizing anddplyr::summarize, where it fails if the returned summary is other than length 1. Indplyr-land, I would have summarized with ado(...)block so that I can return more than 1, it's nice to not have to do something similar here.
– r2evans
Nov 15 '18 at 0:06
add a comment |
I'm still learningdata.table, but I had never thought to usec(...). Interesting to see that a summarizing function would return more than one row per group, I can see that as very useful in some circumstances. I'm not certain where your question is, though: your code is good at demonstrating the difference: in the.(...)case you get one row per group. I suspect the equivalent of your second command isd[, .(c(mean(Rate1), mean(Rate2))), by = Name], which might clear up why it returns a single column, each group with two rows.
– r2evans
Nov 14 '18 at 22:40
2
Please have a look at the nice vignette Introduction todata.table: "As long asjreturns a list, each element of the list becomes a column in the resultingdata.table"; "When there’s only one column or expression to refer to inj[...], we can drop the.()notation. This is purely for convenience." In your case, thec()concatenates the two means to one column.
– Henrik
Nov 14 '18 at 22:42
1
@r2evans - I supposej+by=are not strictly a summarizing function, but rather a flexible grouping capability. You can even return more rows than are in the original data.
– thelatemail
Nov 15 '18 at 0:04
Yes, @thelatemail, I'm gathering that. This is one key difference betweendata.tablesummarizing anddplyr::summarize, where it fails if the returned summary is other than length 1. Indplyr-land, I would have summarized with ado(...)block so that I can return more than 1, it's nice to not have to do something similar here.
– r2evans
Nov 15 '18 at 0:06
I'm still learning
data.table, but I had never thought to use c(...). Interesting to see that a summarizing function would return more than one row per group, I can see that as very useful in some circumstances. I'm not certain where your question is, though: your code is good at demonstrating the difference: in the .(...) case you get one row per group. I suspect the equivalent of your second command is d[, .(c(mean(Rate1), mean(Rate2))), by = Name], which might clear up why it returns a single column, each group with two rows.– r2evans
Nov 14 '18 at 22:40
I'm still learning
data.table, but I had never thought to use c(...). Interesting to see that a summarizing function would return more than one row per group, I can see that as very useful in some circumstances. I'm not certain where your question is, though: your code is good at demonstrating the difference: in the .(...) case you get one row per group. I suspect the equivalent of your second command is d[, .(c(mean(Rate1), mean(Rate2))), by = Name], which might clear up why it returns a single column, each group with two rows.– r2evans
Nov 14 '18 at 22:40
2
2
Please have a look at the nice vignette Introduction to
data.table: "As long as j returns a list, each element of the list becomes a column in the resulting data.table"; "When there’s only one column or expression to refer to in j [...], we can drop the .() notation. This is purely for convenience." In your case, the c() concatenates the two means to one column.– Henrik
Nov 14 '18 at 22:42
Please have a look at the nice vignette Introduction to
data.table: "As long as j returns a list, each element of the list becomes a column in the resulting data.table"; "When there’s only one column or expression to refer to in j [...], we can drop the .() notation. This is purely for convenience." In your case, the c() concatenates the two means to one column.– Henrik
Nov 14 '18 at 22:42
1
1
@r2evans - I suppose
j + by= are not strictly a summarizing function, but rather a flexible grouping capability. You can even return more rows than are in the original data.– thelatemail
Nov 15 '18 at 0:04
@r2evans - I suppose
j + by= are not strictly a summarizing function, but rather a flexible grouping capability. You can even return more rows than are in the original data.– thelatemail
Nov 15 '18 at 0:04
Yes, @thelatemail, I'm gathering that. This is one key difference between
data.table summarizing and dplyr::summarize, where it fails if the returned summary is other than length 1. In dplyr-land, I would have summarized with a do(...) block so that I can return more than 1, it's nice to not have to do something similar here.– r2evans
Nov 15 '18 at 0:06
Yes, @thelatemail, I'm gathering that. This is one key difference between
data.table summarizing and dplyr::summarize, where it fails if the returned summary is other than length 1. In dplyr-land, I would have summarized with a do(...) block so that I can return more than 1, it's nice to not have to do something similar here.– r2evans
Nov 15 '18 at 0:06
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I'm still learning
data.table, but I had never thought to usec(...). Interesting to see that a summarizing function would return more than one row per group, I can see that as very useful in some circumstances. I'm not certain where your question is, though: your code is good at demonstrating the difference: in the.(...)case you get one row per group. I suspect the equivalent of your second command isd[, .(c(mean(Rate1), mean(Rate2))), by = Name], which might clear up why it returns a single column, each group with two rows.– r2evans
Nov 14 '18 at 22:40
2
Please have a look at the nice vignette Introduction to
data.table: "As long asjreturns a list, each element of the list becomes a column in the resultingdata.table"; "When there’s only one column or expression to refer to inj[...], we can drop the.()notation. This is purely for convenience." In your case, thec()concatenates the two means to one column.– Henrik
Nov 14 '18 at 22:42
1
@r2evans - I suppose
j+by=are not strictly a summarizing function, but rather a flexible grouping capability. You can even return more rows than are in the original data.– thelatemail
Nov 15 '18 at 0:04
Yes, @thelatemail, I'm gathering that. This is one key difference between
data.tablesummarizing anddplyr::summarize, where it fails if the returned summary is other than length 1. Indplyr-land, I would have summarized with ado(...)block so that I can return more than 1, it's nice to not have to do something similar here.– r2evans
Nov 15 '18 at 0:06