Using purrr::pmap() in a rowwise manner outside of mutate()
I am trying to use purrr::pmap() to apply a custom function in a rowwise fashion along some dataframe rows. I can achieve my desired end result with a for-loop and with apply(), but when I try to use pmap() I can only get the result I want in combination with mutate(), which in my real-life applied case will be insufficient.
Is there a way to use pmap() to apply my custom function and just have the output print rather than be stored in a new column?
library(dplyr)
library(purrr)
library(tibble)
Create demo data & custom function
set.seed(57)
ds_mt <-
mtcars %>%
rownames_to_column("model") %>%
mutate(
am = factor(am, labels = c("auto", "manual")),
vs = factor(vs, labels = c("V", "S"))
) %>%
select(model, mpg, wt, cyl, am, vs) %>%
sample_n(3)
foo <- function(model, am, mpg){
print(
paste("The", model, "has a", am, "transmission and gets", mpg, "mpgs.")
)
}
Successful example of rowwise for-loop:
for (row in 1:nrow(ds_mt)) {
foo(
model = ds_mt[row, "model"],
am = ds_mt[row, "am"],
mpg = ds_mt[row, "mpg"]
)
}
Successful example using apply():
row.names(ds_mt) <- NULL # to avoid named vector as output
apply(
ds_mt,
MARGIN = 1,
FUN = function(ds)
foo(
model = ds["model"],
am = ds["am"],
mpg = ds["mpg"]
)
)
Example using pmap() within mutate() that is almost what I need.
ds_mt %>%
mutate(new_var =
pmap(
.l =
list(
model = model,
am = am,
mpg = mpg
),
.f = foo
))
FAILING CODE: Why doesn't this work?
ds_mt %>%
pmap(
.l =
list(
model = model,
am = am,
mpg = mpg
),
.f = foo
)
r purrr pmap
asked Nov 20 at 23:27
Joe
683514
add a comment |
I am trying to use purrr::pmap() to apply a custom function in a rowwise fashion along some dataframe rows. I can achieve my desired end result with a for-loop and with apply(), but when I try to use pmap() I can only get the result I want in combination with mutate(), which in my real-life applied case will be insufficient.
Is there a way to use pmap() to apply my custom function and just have the output print rather than be stored in a new column?
library(dplyr)
library(purrr)
library(tibble)
Create demo data & custom function
set.seed(57)
ds_mt <-
mtcars %>%
rownames_to_column("model") %>%
mutate(
am = factor(am, labels = c("auto", "manual")),
vs = factor(vs, labels = c("V", "S"))
) %>%
select(model, mpg, wt, cyl, am, vs) %>%
sample_n(3)
foo <- function(model, am, mpg){
print(
paste("The", model, "has a", am, "transmission and gets", mpg, "mpgs.")
)
}
Successful example of rowwise for-loop:
for (row in 1:nrow(ds_mt)) {
foo(
model = ds_mt[row, "model"],
am = ds_mt[row, "am"],
mpg = ds_mt[row, "mpg"]
)
}
Successful example using apply():
row.names(ds_mt) <- NULL # to avoid named vector as output
apply(
ds_mt,
MARGIN = 1,
FUN = function(ds)
foo(
model = ds["model"],
am = ds["am"],
mpg = ds["mpg"]
)
)
Example using pmap() within mutate() that is almost what I need.
ds_mt %>%
mutate(new_var =
pmap(
.l =
list(
model = model,
am = am,
mpg = mpg
),
.f = foo
))
FAILING CODE: Why doesn't this work?
ds_mt %>%
pmap(
.l =
list(
model = model,
am = am,
mpg = mpg
),
.f = foo
)
r purrr pmap
asked Nov 20 at 23:27
Joe
683514
Please note thatpasteis vectorized, so no need for various row-wise operations.with(mtcars[1:3, ], paste("The", vs, "has a", am, "transmission and gets", mpg, "mpgs.")). Perhaps this was a toy example and you have a 'real' function which isn't vectorized?
– Henrik
Nov 20 at 23:35
1
You are passingds_mtto any of the arguments inpmap()in your current code. You could select the columns you want and then pass that object to.l. Likeds_mt %>% select(model, am, mpg) %>% pmap(foo)(although as others have pointed out you don't need this for this particular task.)
– aosmith
Nov 20 at 23:54
add a comment |
I am trying to use purrr::pmap() to apply a custom function in a rowwise fashion along some dataframe rows. I can achieve my desired end result with a for-loop and with apply(), but when I try to use pmap() I can only get the result I want in combination with mutate(), which in my real-life applied case will be insufficient.
Is there a way to use pmap() to apply my custom function and just have the output print rather than be stored in a new column?
library(dplyr)
library(purrr)
library(tibble)
Create demo data & custom function
set.seed(57)
ds_mt <-
mtcars %>%
rownames_to_column("model") %>%
mutate(
am = factor(am, labels = c("auto", "manual")),
vs = factor(vs, labels = c("V", "S"))
) %>%
select(model, mpg, wt, cyl, am, vs) %>%
sample_n(3)
foo <- function(model, am, mpg){
print(
paste("The", model, "has a", am, "transmission and gets", mpg, "mpgs.")
)
}
Successful example of rowwise for-loop:
for (row in 1:nrow(ds_mt)) {
foo(
model = ds_mt[row, "model"],
am = ds_mt[row, "am"],
mpg = ds_mt[row, "mpg"]
)
}
Successful example using apply():
row.names(ds_mt) <- NULL # to avoid named vector as output
apply(
ds_mt,
MARGIN = 1,
FUN = function(ds)
foo(
model = ds["model"],
am = ds["am"],
mpg = ds["mpg"]
)
)
Example using pmap() within mutate() that is almost what I need.
ds_mt %>%
mutate(new_var =
pmap(
.l =
list(
model = model,
am = am,
mpg = mpg
),
.f = foo
))
FAILING CODE: Why doesn't this work?
ds_mt %>%
pmap(
.l =
list(
model = model,
am = am,
mpg = mpg
),
.f = foo
)
r purrr pmap
asked Nov 20 at 23:27
Joe
683514
I am trying to use purrr::pmap() to apply a custom function in a rowwise fashion along some dataframe rows. I can achieve my desired end result with a for-loop and with apply(), but when I try to use pmap() I can only get the result I want in combination with mutate(), which in my real-life applied case will be insufficient.
Is there a way to use pmap() to apply my custom function and just have the output print rather than be stored in a new column?
library(dplyr)
library(purrr)
library(tibble)
Create demo data & custom function
set.seed(57)
ds_mt <-
mtcars %>%
rownames_to_column("model") %>%
mutate(
am = factor(am, labels = c("auto", "manual")),
vs = factor(vs, labels = c("V", "S"))
) %>%
select(model, mpg, wt, cyl, am, vs) %>%
sample_n(3)
foo <- function(model, am, mpg){
print(
paste("The", model, "has a", am, "transmission and gets", mpg, "mpgs.")
)
}
Successful example of rowwise for-loop:
for (row in 1:nrow(ds_mt)) {
foo(
model = ds_mt[row, "model"],
am = ds_mt[row, "am"],
mpg = ds_mt[row, "mpg"]
)
}
Successful example using apply():
row.names(ds_mt) <- NULL # to avoid named vector as output
apply(
ds_mt,
MARGIN = 1,
FUN = function(ds)
foo(
model = ds["model"],
am = ds["am"],
mpg = ds["mpg"]
)
)
Example using pmap() within mutate() that is almost what I need.
ds_mt %>%
mutate(new_var =
pmap(
.l =
list(
model = model,
am = am,
mpg = mpg
),
.f = foo
))
FAILING CODE: Why doesn't this work?
ds_mt %>%
pmap(
.l =
list(
model = model,
am = am,
mpg = mpg
),
.f = foo
)
r purrr pmap
r purrr pmap
asked Nov 20 at 23:27
Joe
683514
asked Nov 20 at 23:27
Joe
683514
asked Nov 20 at 23:27
Joe
683514
asked Nov 20 at 23:27
Joe
683514
asked Nov 20 at 23:27
Joe
683514
683514
Please note thatpasteis vectorized, so no need for various row-wise operations.with(mtcars[1:3, ], paste("The", vs, "has a", am, "transmission and gets", mpg, "mpgs.")). Perhaps this was a toy example and you have a 'real' function which isn't vectorized?
– Henrik
Nov 20 at 23:35
1
You are passingds_mtto any of the arguments inpmap()in your current code. You could select the columns you want and then pass that object to.l. Likeds_mt %>% select(model, am, mpg) %>% pmap(foo)(although as others have pointed out you don't need this for this particular task.)
– aosmith
Nov 20 at 23:54
add a comment |
Please note thatpasteis vectorized, so no need for various row-wise operations.with(mtcars[1:3, ], paste("The", vs, "has a", am, "transmission and gets", mpg, "mpgs.")). Perhaps this was a toy example and you have a 'real' function which isn't vectorized?
– Henrik
Nov 20 at 23:35
1
You are passingds_mtto any of the arguments inpmap()in your current code. You could select the columns you want and then pass that object to.l. Likeds_mt %>% select(model, am, mpg) %>% pmap(foo)(although as others have pointed out you don't need this for this particular task.)
– aosmith
Nov 20 at 23:54
Please note that
paste is vectorized, so no need for various row-wise operations. with(mtcars[1:3, ], paste("The", vs, "has a", am, "transmission and gets", mpg, "mpgs.")). Perhaps this was a toy example and you have a 'real' function which isn't vectorized?– Henrik
Nov 20 at 23:35
Please note that
paste is vectorized, so no need for various row-wise operations. with(mtcars[1:3, ], paste("The", vs, "has a", am, "transmission and gets", mpg, "mpgs.")). Perhaps this was a toy example and you have a 'real' function which isn't vectorized?– Henrik
Nov 20 at 23:35
1
1
You are passing
ds_mt to any of the arguments in pmap() in your current code. You could select the columns you want and then pass that object to .l. Like ds_mt %>% select(model, am, mpg) %>% pmap(foo) (although as others have pointed out you don't need this for this particular task.)– aosmith
Nov 20 at 23:54
You are passing
ds_mt to any of the arguments in pmap() in your current code. You could select the columns you want and then pass that object to .l. Like ds_mt %>% select(model, am, mpg) %>% pmap(foo) (although as others have pointed out you don't need this for this particular task.)– aosmith
Nov 20 at 23:54
add a comment |
1 Answer
1
active
oldest
votes
So after some more reading it seems this is a case for pwalk() rather than pmap(), because I am trying to get output to print (i.e., a side effect) rather than to be stored in a dataframe.
library(dplyr)
library(purrr)
library(tibble)
set.seed(57)
ds_mt <-
mtcars %>%
rownames_to_column("model") %>%
mutate(
am = factor(am, labels = c("auto", "manual")),
vs = factor(vs, labels = c("V", "S"))
) %>%
select(model, mpg, wt, cyl, am, vs) %>%
sample_n(3)
foo <- function(model, am, mpg){
print(
paste("The", model, "has a", am, "transmission and gets", mpg, "mpgs.")
)
}
ds_mt %>%
select(model, am, mpg) %>%
pwalk(
.l = .,
.f = foo
)
answered Nov 27 at 0:22
Joe
683514
add a comment |
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1 Answer
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active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
So after some more reading it seems this is a case for pwalk() rather than pmap(), because I am trying to get output to print (i.e., a side effect) rather than to be stored in a dataframe.
library(dplyr)
library(purrr)
library(tibble)
set.seed(57)
ds_mt <-
mtcars %>%
rownames_to_column("model") %>%
mutate(
am = factor(am, labels = c("auto", "manual")),
vs = factor(vs, labels = c("V", "S"))
) %>%
select(model, mpg, wt, cyl, am, vs) %>%
sample_n(3)
foo <- function(model, am, mpg){
print(
paste("The", model, "has a", am, "transmission and gets", mpg, "mpgs.")
)
}
ds_mt %>%
select(model, am, mpg) %>%
pwalk(
.l = .,
.f = foo
)
answered Nov 27 at 0:22
Joe
683514
add a comment |
So after some more reading it seems this is a case for pwalk() rather than pmap(), because I am trying to get output to print (i.e., a side effect) rather than to be stored in a dataframe.
library(dplyr)
library(purrr)
library(tibble)
set.seed(57)
ds_mt <-
mtcars %>%
rownames_to_column("model") %>%
mutate(
am = factor(am, labels = c("auto", "manual")),
vs = factor(vs, labels = c("V", "S"))
) %>%
select(model, mpg, wt, cyl, am, vs) %>%
sample_n(3)
foo <- function(model, am, mpg){
print(
paste("The", model, "has a", am, "transmission and gets", mpg, "mpgs.")
)
}
ds_mt %>%
select(model, am, mpg) %>%
pwalk(
.l = .,
.f = foo
)
answered Nov 27 at 0:22
Joe
683514
add a comment |
So after some more reading it seems this is a case for pwalk() rather than pmap(), because I am trying to get output to print (i.e., a side effect) rather than to be stored in a dataframe.
library(dplyr)
library(purrr)
library(tibble)
set.seed(57)
ds_mt <-
mtcars %>%
rownames_to_column("model") %>%
mutate(
am = factor(am, labels = c("auto", "manual")),
vs = factor(vs, labels = c("V", "S"))
) %>%
select(model, mpg, wt, cyl, am, vs) %>%
sample_n(3)
foo <- function(model, am, mpg){
print(
paste("The", model, "has a", am, "transmission and gets", mpg, "mpgs.")
)
}
ds_mt %>%
select(model, am, mpg) %>%
pwalk(
.l = .,
.f = foo
)
answered Nov 27 at 0:22
Joe
683514
So after some more reading it seems this is a case for pwalk() rather than pmap(), because I am trying to get output to print (i.e., a side effect) rather than to be stored in a dataframe.
library(dplyr)
library(purrr)
library(tibble)
set.seed(57)
ds_mt <-
mtcars %>%
rownames_to_column("model") %>%
mutate(
am = factor(am, labels = c("auto", "manual")),
vs = factor(vs, labels = c("V", "S"))
) %>%
select(model, mpg, wt, cyl, am, vs) %>%
sample_n(3)
foo <- function(model, am, mpg){
print(
paste("The", model, "has a", am, "transmission and gets", mpg, "mpgs.")
)
}
ds_mt %>%
select(model, am, mpg) %>%
pwalk(
.l = .,
.f = foo
)
answered Nov 27 at 0:22
Joe
683514
answered Nov 27 at 0:22
Joe
683514
answered Nov 27 at 0:22
Joe
683514
answered Nov 27 at 0:22
Joe
683514
683514
add a comment |
add a comment |
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Please note that
pasteis vectorized, so no need for various row-wise operations.with(mtcars[1:3, ], paste("The", vs, "has a", am, "transmission and gets", mpg, "mpgs.")). Perhaps this was a toy example and you have a 'real' function which isn't vectorized?– Henrik
Nov 20 at 23:35
1
You are passing
ds_mtto any of the arguments inpmap()in your current code. You could select the columns you want and then pass that object to.l. Likeds_mt %>% select(model, am, mpg) %>% pmap(foo)(although as others have pointed out you don't need this for this particular task.)– aosmith
Nov 20 at 23:54