What's the difference between using select + unlist from dplyr package and using the dollar sign?
I've been taking an online course in which the instructor always does the following to obtain, say, the column Col1 from a data.frame object Dat:
library(dplyr)
unlist(select(Dat, Col1))
Why not simply run Dat$Col1? I notice a difference in the "presentation" of both results, but is there any other significant divergence between the two forms? Any operation will result in the same product for both?
r dplyr
edited Jan 5 at 21:10
Ben Bolker
133k11222310
asked Jan 5 at 20:46
G. MonteiroG. Monteiro
513
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G. Monteiro is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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I've been taking an online course in which the instructor always does the following to obtain, say, the column Col1 from a data.frame object Dat:
library(dplyr)
unlist(select(Dat, Col1))
Why not simply run Dat$Col1? I notice a difference in the "presentation" of both results, but is there any other significant divergence between the two forms? Any operation will result in the same product for both?
r dplyr
edited Jan 5 at 21:10
Ben Bolker
133k11222310
asked Jan 5 at 20:46
G. MonteiroG. Monteiro
513
New contributor
G. Monteiro is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
8
Your instructor is probably just a fan of the tidyverse.Dat$Col1is my preferred method for getting a column.
– Rich Scriven
Jan 5 at 20:48
9
...but not well-versed enough to know ofpull.
– Henrik
Jan 5 at 20:51
4
Touche. Maybe OP can take the instructor to school.
– Rich Scriven
Jan 5 at 20:53
3
Wow, he loads an entire new library for that?
– cory
Jan 5 at 21:05
6
The rumours about the SO incidentspread, and the instructor decided togathereverystudent.todayhe had started toselectcigarettes withoutfilter, and took a long, deeppulltocomposehimself for aminute. It was a mare’snest. “Well, I have a crow topluckwith you,whodid this?”, the teacher started. "betweenyou and me: this is nofuns. You better notcrossme, or I willreduceyour grades,everygrade. Whichever way yousliceit -period!" The students looked at each other. Acompletefarce. Happy newyeareveryone -tally-ho!
– Henrik
Jan 5 at 22:33
|
show 1 more comment
I've been taking an online course in which the instructor always does the following to obtain, say, the column Col1 from a data.frame object Dat:
library(dplyr)
unlist(select(Dat, Col1))
Why not simply run Dat$Col1? I notice a difference in the "presentation" of both results, but is there any other significant divergence between the two forms? Any operation will result in the same product for both?
r dplyr
edited Jan 5 at 21:10
Ben Bolker
133k11222310
asked Jan 5 at 20:46
G. MonteiroG. Monteiro
513
New contributor
G. Monteiro is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
I've been taking an online course in which the instructor always does the following to obtain, say, the column Col1 from a data.frame object Dat:
library(dplyr)
unlist(select(Dat, Col1))
Why not simply run Dat$Col1? I notice a difference in the "presentation" of both results, but is there any other significant divergence between the two forms? Any operation will result in the same product for both?
r dplyr
r dplyr
edited Jan 5 at 21:10
Ben Bolker
133k11222310
asked Jan 5 at 20:46
G. MonteiroG. Monteiro
513
New contributor
G. Monteiro is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
edited Jan 5 at 21:10
Ben Bolker
133k11222310
asked Jan 5 at 20:46
G. MonteiroG. Monteiro
513
New contributor
G. Monteiro is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
edited Jan 5 at 21:10
Ben Bolker
133k11222310
edited Jan 5 at 21:10
Ben Bolker
133k11222310
edited Jan 5 at 21:10
Ben Bolker
133k11222310
133k11222310
asked Jan 5 at 20:46
G. MonteiroG. Monteiro
513
New contributor
G. Monteiro is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked Jan 5 at 20:46
G. MonteiroG. Monteiro
513
asked Jan 5 at 20:46
G. MonteiroG. Monteiro
513
513
New contributor
G. Monteiro is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
G. Monteiro is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
G. Monteiro is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
8
Your instructor is probably just a fan of the tidyverse.Dat$Col1is my preferred method for getting a column.
– Rich Scriven
Jan 5 at 20:48
9
...but not well-versed enough to know ofpull.
– Henrik
Jan 5 at 20:51
4
Touche. Maybe OP can take the instructor to school.
– Rich Scriven
Jan 5 at 20:53
3
Wow, he loads an entire new library for that?
– cory
Jan 5 at 21:05
6
The rumours about the SO incidentspread, and the instructor decided togathereverystudent.todayhe had started toselectcigarettes withoutfilter, and took a long, deeppulltocomposehimself for aminute. It was a mare’snest. “Well, I have a crow topluckwith you,whodid this?”, the teacher started. "betweenyou and me: this is nofuns. You better notcrossme, or I willreduceyour grades,everygrade. Whichever way yousliceit -period!" The students looked at each other. Acompletefarce. Happy newyeareveryone -tally-ho!
– Henrik
Jan 5 at 22:33
|
show 1 more comment
8
Your instructor is probably just a fan of the tidyverse.Dat$Col1is my preferred method for getting a column.
– Rich Scriven
Jan 5 at 20:48
9
...but not well-versed enough to know ofpull.
– Henrik
Jan 5 at 20:51
4
Touche. Maybe OP can take the instructor to school.
– Rich Scriven
Jan 5 at 20:53
3
Wow, he loads an entire new library for that?
– cory
Jan 5 at 21:05
6
The rumours about the SO incidentspread, and the instructor decided togathereverystudent.todayhe had started toselectcigarettes withoutfilter, and took a long, deeppulltocomposehimself for aminute. It was a mare’snest. “Well, I have a crow topluckwith you,whodid this?”, the teacher started. "betweenyou and me: this is nofuns. You better notcrossme, or I willreduceyour grades,everygrade. Whichever way yousliceit -period!" The students looked at each other. Acompletefarce. Happy newyeareveryone -tally-ho!
– Henrik
Jan 5 at 22:33
8
8
Your instructor is probably just a fan of the tidyverse.
Dat$Col1 is my preferred method for getting a column.– Rich Scriven
Jan 5 at 20:48
Your instructor is probably just a fan of the tidyverse.
Dat$Col1 is my preferred method for getting a column.– Rich Scriven
Jan 5 at 20:48
9
9
...but not well-
versed enough to know of pull.– Henrik
Jan 5 at 20:51
...but not well-
versed enough to know of pull.– Henrik
Jan 5 at 20:51
4
4
Touche. Maybe OP can take the instructor to school.
– Rich Scriven
Jan 5 at 20:53
Touche. Maybe OP can take the instructor to school.
– Rich Scriven
Jan 5 at 20:53
3
3
Wow, he loads an entire new library for that?
– cory
Jan 5 at 21:05
Wow, he loads an entire new library for that?
– cory
Jan 5 at 21:05
6
6
The rumours about the SO incident
spread, and the instructor decided to gather every student. today he had started to select cigarettes without filter, and took a long, deep pull to compose himself for a minute. It was a mare’s nest. “Well, I have a crow to pluck with you, who did this?”, the teacher started. "between you and me: this is no funs. You better not cross me, or I will reduce your grades, every grade. Whichever way you slice it - period!" The students looked at each other. A complete farce. Happy new year every one - tally-ho!– Henrik
Jan 5 at 22:33
The rumours about the SO incident
spread, and the instructor decided to gather every student. today he had started to select cigarettes without filter, and took a long, deep pull to compose himself for a minute. It was a mare’s nest. “Well, I have a crow to pluck with you, who did this?”, the teacher started. "between you and me: this is no funs. You better not cross me, or I will reduce your grades, every grade. Whichever way you slice it - period!" The students looked at each other. A complete farce. Happy new year every one - tally-ho!– Henrik
Jan 5 at 22:33
|
show 1 more comment
1 Answer
1
active
oldest
votes
(Posting comments as community wiki.)
These are not quite equivalent - unlist(select(.)) keeps (probably unwanted) names.
dd <- data.frame(Col1=c("abc","def"))
str(unlist(select(dd,Col1)))
## Factor w/ 2 levels "abc","def": 1 2
## - attr(*, "names")= chr [1:2] "Col11" "Col12"
str(dd$Col1)
## Factor w/ 2 levels "abc","def": 1 2
Your instructor is probably just a fan of the tidyverse (@RichScriven); pull(Dat, Col1) or (for extreme "tidiness") Dat %>% pull(Col1) would be more idiomatic (@Henrik). Dat$Col1 or Dat[["Col1"]] would be the base-R equivalents (the former is more convenient for interactive use, the latter is marginally safer for programming purposes since it won't do name-completion).
It hardly matters, but the tidyverse approaches are much slower.
microbenchmark(dd$Col1,dd[["Col1"]],pull(dd,Col1),unlist(select(dd,Col1)))
Unit: microseconds
expr min lq mean median uq
dd$Col1 5.296 10.9630 14.86871 13.4040 17.160
dd[["Col1"]] 7.870 9.6535 15.18874 11.8270 16.635
pull(dd, Col1) 44.160 108.7625 128.89342 117.8415 136.890
unlist(select(dd, Col1)) 601.480 1132.8240 1436.44178 1214.4420 1378.141
max neval cld
31.036 100 a
88.842 100 a
422.462 100 a
8796.964 100 b
2
Since you mentioned it,pull(dd, Col1)is twice as fast asdd %>% pull(Col1). Tested with a much largerdd <- data.frame(Col1 = sample(c("abc", "def"), 1e6, TRUE)).
– Rui Barradas
Jan 5 at 22:37
1
Just to note, there's always the use.names argument to the base R function,unlistwhich will drop any unwanted names:unlist(select(.), use.names=FALSE).
– lmo
Jan 5 at 23:26
add a comment |
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(Posting comments as community wiki.)
These are not quite equivalent - unlist(select(.)) keeps (probably unwanted) names.
dd <- data.frame(Col1=c("abc","def"))
str(unlist(select(dd,Col1)))
## Factor w/ 2 levels "abc","def": 1 2
## - attr(*, "names")= chr [1:2] "Col11" "Col12"
str(dd$Col1)
## Factor w/ 2 levels "abc","def": 1 2
Your instructor is probably just a fan of the tidyverse (@RichScriven); pull(Dat, Col1) or (for extreme "tidiness") Dat %>% pull(Col1) would be more idiomatic (@Henrik). Dat$Col1 or Dat[["Col1"]] would be the base-R equivalents (the former is more convenient for interactive use, the latter is marginally safer for programming purposes since it won't do name-completion).
It hardly matters, but the tidyverse approaches are much slower.
microbenchmark(dd$Col1,dd[["Col1"]],pull(dd,Col1),unlist(select(dd,Col1)))
Unit: microseconds
expr min lq mean median uq
dd$Col1 5.296 10.9630 14.86871 13.4040 17.160
dd[["Col1"]] 7.870 9.6535 15.18874 11.8270 16.635
pull(dd, Col1) 44.160 108.7625 128.89342 117.8415 136.890
unlist(select(dd, Col1)) 601.480 1132.8240 1436.44178 1214.4420 1378.141
max neval cld
31.036 100 a
88.842 100 a
422.462 100 a
8796.964 100 b
2
Since you mentioned it,pull(dd, Col1)is twice as fast asdd %>% pull(Col1). Tested with a much largerdd <- data.frame(Col1 = sample(c("abc", "def"), 1e6, TRUE)).
– Rui Barradas
Jan 5 at 22:37
1
Just to note, there's always the use.names argument to the base R function,unlistwhich will drop any unwanted names:unlist(select(.), use.names=FALSE).
– lmo
Jan 5 at 23:26
add a comment |
(Posting comments as community wiki.)
These are not quite equivalent - unlist(select(.)) keeps (probably unwanted) names.
dd <- data.frame(Col1=c("abc","def"))
str(unlist(select(dd,Col1)))
## Factor w/ 2 levels "abc","def": 1 2
## - attr(*, "names")= chr [1:2] "Col11" "Col12"
str(dd$Col1)
## Factor w/ 2 levels "abc","def": 1 2
Your instructor is probably just a fan of the tidyverse (@RichScriven); pull(Dat, Col1) or (for extreme "tidiness") Dat %>% pull(Col1) would be more idiomatic (@Henrik). Dat$Col1 or Dat[["Col1"]] would be the base-R equivalents (the former is more convenient for interactive use, the latter is marginally safer for programming purposes since it won't do name-completion).
It hardly matters, but the tidyverse approaches are much slower.
microbenchmark(dd$Col1,dd[["Col1"]],pull(dd,Col1),unlist(select(dd,Col1)))
Unit: microseconds
expr min lq mean median uq
dd$Col1 5.296 10.9630 14.86871 13.4040 17.160
dd[["Col1"]] 7.870 9.6535 15.18874 11.8270 16.635
pull(dd, Col1) 44.160 108.7625 128.89342 117.8415 136.890
unlist(select(dd, Col1)) 601.480 1132.8240 1436.44178 1214.4420 1378.141
max neval cld
31.036 100 a
88.842 100 a
422.462 100 a
8796.964 100 b
2
Since you mentioned it,pull(dd, Col1)is twice as fast asdd %>% pull(Col1). Tested with a much largerdd <- data.frame(Col1 = sample(c("abc", "def"), 1e6, TRUE)).
– Rui Barradas
Jan 5 at 22:37
1
Just to note, there's always the use.names argument to the base R function,unlistwhich will drop any unwanted names:unlist(select(.), use.names=FALSE).
– lmo
Jan 5 at 23:26
add a comment |
(Posting comments as community wiki.)
These are not quite equivalent - unlist(select(.)) keeps (probably unwanted) names.
dd <- data.frame(Col1=c("abc","def"))
str(unlist(select(dd,Col1)))
## Factor w/ 2 levels "abc","def": 1 2
## - attr(*, "names")= chr [1:2] "Col11" "Col12"
str(dd$Col1)
## Factor w/ 2 levels "abc","def": 1 2
Your instructor is probably just a fan of the tidyverse (@RichScriven); pull(Dat, Col1) or (for extreme "tidiness") Dat %>% pull(Col1) would be more idiomatic (@Henrik). Dat$Col1 or Dat[["Col1"]] would be the base-R equivalents (the former is more convenient for interactive use, the latter is marginally safer for programming purposes since it won't do name-completion).
It hardly matters, but the tidyverse approaches are much slower.
microbenchmark(dd$Col1,dd[["Col1"]],pull(dd,Col1),unlist(select(dd,Col1)))
Unit: microseconds
expr min lq mean median uq
dd$Col1 5.296 10.9630 14.86871 13.4040 17.160
dd[["Col1"]] 7.870 9.6535 15.18874 11.8270 16.635
pull(dd, Col1) 44.160 108.7625 128.89342 117.8415 136.890
unlist(select(dd, Col1)) 601.480 1132.8240 1436.44178 1214.4420 1378.141
max neval cld
31.036 100 a
88.842 100 a
422.462 100 a
8796.964 100 b
(Posting comments as community wiki.)
These are not quite equivalent - unlist(select(.)) keeps (probably unwanted) names.
dd <- data.frame(Col1=c("abc","def"))
str(unlist(select(dd,Col1)))
## Factor w/ 2 levels "abc","def": 1 2
## - attr(*, "names")= chr [1:2] "Col11" "Col12"
str(dd$Col1)
## Factor w/ 2 levels "abc","def": 1 2
Your instructor is probably just a fan of the tidyverse (@RichScriven); pull(Dat, Col1) or (for extreme "tidiness") Dat %>% pull(Col1) would be more idiomatic (@Henrik). Dat$Col1 or Dat[["Col1"]] would be the base-R equivalents (the former is more convenient for interactive use, the latter is marginally safer for programming purposes since it won't do name-completion).
It hardly matters, but the tidyverse approaches are much slower.
microbenchmark(dd$Col1,dd[["Col1"]],pull(dd,Col1),unlist(select(dd,Col1)))
Unit: microseconds
expr min lq mean median uq
dd$Col1 5.296 10.9630 14.86871 13.4040 17.160
dd[["Col1"]] 7.870 9.6535 15.18874 11.8270 16.635
pull(dd, Col1) 44.160 108.7625 128.89342 117.8415 136.890
unlist(select(dd, Col1)) 601.480 1132.8240 1436.44178 1214.4420 1378.141
max neval cld
31.036 100 a
88.842 100 a
422.462 100 a
8796.964 100 b
edited Jan 5 at 21:13
community wiki
2 revs
Ben Bolker
2
Since you mentioned it,pull(dd, Col1)is twice as fast asdd %>% pull(Col1). Tested with a much largerdd <- data.frame(Col1 = sample(c("abc", "def"), 1e6, TRUE)).
– Rui Barradas
Jan 5 at 22:37
1
Just to note, there's always the use.names argument to the base R function,unlistwhich will drop any unwanted names:unlist(select(.), use.names=FALSE).
– lmo
Jan 5 at 23:26
add a comment |
2
Since you mentioned it,pull(dd, Col1)is twice as fast asdd %>% pull(Col1). Tested with a much largerdd <- data.frame(Col1 = sample(c("abc", "def"), 1e6, TRUE)).
– Rui Barradas
Jan 5 at 22:37
1
Just to note, there's always the use.names argument to the base R function,unlistwhich will drop any unwanted names:unlist(select(.), use.names=FALSE).
– lmo
Jan 5 at 23:26
2
2
Since you mentioned it,
pull(dd, Col1) is twice as fast as dd %>% pull(Col1). Tested with a much larger dd <- data.frame(Col1 = sample(c("abc", "def"), 1e6, TRUE)).– Rui Barradas
Jan 5 at 22:37
Since you mentioned it,
pull(dd, Col1) is twice as fast as dd %>% pull(Col1). Tested with a much larger dd <- data.frame(Col1 = sample(c("abc", "def"), 1e6, TRUE)).– Rui Barradas
Jan 5 at 22:37
1
1
Just to note, there's always the use.names argument to the base R function,
unlist which will drop any unwanted names: unlist(select(.), use.names=FALSE).– lmo
Jan 5 at 23:26
Just to note, there's always the use.names argument to the base R function,
unlist which will drop any unwanted names: unlist(select(.), use.names=FALSE).– lmo
Jan 5 at 23:26
add a comment |
G. Monteiro is a new contributor. Be nice, and check out our Code of Conduct.
G. Monteiro is a new contributor. Be nice, and check out our Code of Conduct.
G. Monteiro is a new contributor. Be nice, and check out our Code of Conduct.
G. Monteiro is a new contributor. Be nice, and check out our Code of Conduct.
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8
Your instructor is probably just a fan of the tidyverse.
Dat$Col1is my preferred method for getting a column.– Rich Scriven
Jan 5 at 20:48
9
...but not well-
versed enough to know ofpull.– Henrik
Jan 5 at 20:51
4
Touche. Maybe OP can take the instructor to school.
– Rich Scriven
Jan 5 at 20:53
3
Wow, he loads an entire new library for that?
– cory
Jan 5 at 21:05
6
The rumours about the SO incident
spread, and the instructor decided togathereverystudent.todayhe had started toselectcigarettes withoutfilter, and took a long, deeppulltocomposehimself for aminute. It was a mare’snest. “Well, I have a crow topluckwith you,whodid this?”, the teacher started. "betweenyou and me: this is nofuns. You better notcrossme, or I willreduceyour grades,everygrade. Whichever way yousliceit -period!" The students looked at each other. Acompletefarce. Happy newyeareveryone -tally-ho!– Henrik
Jan 5 at 22:33