Plot multiple histograms with purrr::map and ggplot2
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0
down vote
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How do I plot the histograms for these four random variables . This works, but it seems unneccessarily long.
#libraries
library(tidyverse)
library(purrr)
# Standard deviation question
std_devs %>%
map(rnorm, n=1000, mean=75) %>%
do.call('rbind', .) %>%
t() %>%
as.data.frame() %>%
gather() %>%
ggplot(., aes(x=value))+geom_histogram()+facet_wrap(~key)
r ggplot2 tidyverse purrr
add a comment |
up vote
0
down vote
favorite
How do I plot the histograms for these four random variables . This works, but it seems unneccessarily long.
#libraries
library(tidyverse)
library(purrr)
# Standard deviation question
std_devs %>%
map(rnorm, n=1000, mean=75) %>%
do.call('rbind', .) %>%
t() %>%
as.data.frame() %>%
gather() %>%
ggplot(., aes(x=value))+geom_histogram()+facet_wrap(~key)
r ggplot2 tidyverse purrr
what itstd_devs
?
– Richard Telford
Nov 10 at 12:09
Apologies, I missed that. The answer below figured out what I meant.
– spindoctor
yesterday
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
How do I plot the histograms for these four random variables . This works, but it seems unneccessarily long.
#libraries
library(tidyverse)
library(purrr)
# Standard deviation question
std_devs %>%
map(rnorm, n=1000, mean=75) %>%
do.call('rbind', .) %>%
t() %>%
as.data.frame() %>%
gather() %>%
ggplot(., aes(x=value))+geom_histogram()+facet_wrap(~key)
r ggplot2 tidyverse purrr
How do I plot the histograms for these four random variables . This works, but it seems unneccessarily long.
#libraries
library(tidyverse)
library(purrr)
# Standard deviation question
std_devs %>%
map(rnorm, n=1000, mean=75) %>%
do.call('rbind', .) %>%
t() %>%
as.data.frame() %>%
gather() %>%
ggplot(., aes(x=value))+geom_histogram()+facet_wrap(~key)
r ggplot2 tidyverse purrr
r ggplot2 tidyverse purrr
edited Nov 10 at 14:57
Richard Telford
5,72742335
5,72742335
asked Nov 10 at 12:00
spindoctor
366218
366218
what itstd_devs
?
– Richard Telford
Nov 10 at 12:09
Apologies, I missed that. The answer below figured out what I meant.
– spindoctor
yesterday
add a comment |
what itstd_devs
?
– Richard Telford
Nov 10 at 12:09
Apologies, I missed that. The answer below figured out what I meant.
– spindoctor
yesterday
what it
std_devs
?– Richard Telford
Nov 10 at 12:09
what it
std_devs
?– Richard Telford
Nov 10 at 12:09
Apologies, I missed that. The answer below figured out what I meant.
– spindoctor
yesterday
Apologies, I missed that. The answer below figured out what I meant.
– spindoctor
yesterday
add a comment |
1 Answer
1
active
oldest
votes
up vote
0
down vote
accepted
purrr
is loaded by tidyverse
so you can skip that line. map_df
makes the rest much more condensed.
library(tidyverse)
# Standard deviation question
set.seed(10)
std_devs <- 1:4
std_devs %>%
map_df(~data_frame(key = ., value = rnorm(n=1000, mean=75, sd = .))) %>%
ggplot(aes(x=value))+geom_histogram()+facet_wrap(~key)
add a comment |
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
0
down vote
accepted
purrr
is loaded by tidyverse
so you can skip that line. map_df
makes the rest much more condensed.
library(tidyverse)
# Standard deviation question
set.seed(10)
std_devs <- 1:4
std_devs %>%
map_df(~data_frame(key = ., value = rnorm(n=1000, mean=75, sd = .))) %>%
ggplot(aes(x=value))+geom_histogram()+facet_wrap(~key)
add a comment |
up vote
0
down vote
accepted
purrr
is loaded by tidyverse
so you can skip that line. map_df
makes the rest much more condensed.
library(tidyverse)
# Standard deviation question
set.seed(10)
std_devs <- 1:4
std_devs %>%
map_df(~data_frame(key = ., value = rnorm(n=1000, mean=75, sd = .))) %>%
ggplot(aes(x=value))+geom_histogram()+facet_wrap(~key)
add a comment |
up vote
0
down vote
accepted
up vote
0
down vote
accepted
purrr
is loaded by tidyverse
so you can skip that line. map_df
makes the rest much more condensed.
library(tidyverse)
# Standard deviation question
set.seed(10)
std_devs <- 1:4
std_devs %>%
map_df(~data_frame(key = ., value = rnorm(n=1000, mean=75, sd = .))) %>%
ggplot(aes(x=value))+geom_histogram()+facet_wrap(~key)
purrr
is loaded by tidyverse
so you can skip that line. map_df
makes the rest much more condensed.
library(tidyverse)
# Standard deviation question
set.seed(10)
std_devs <- 1:4
std_devs %>%
map_df(~data_frame(key = ., value = rnorm(n=1000, mean=75, sd = .))) %>%
ggplot(aes(x=value))+geom_histogram()+facet_wrap(~key)
edited Nov 10 at 14:57
answered Nov 10 at 12:15
Richard Telford
5,72742335
5,72742335
add a comment |
add a comment |
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what it
std_devs
?– Richard Telford
Nov 10 at 12:09
Apologies, I missed that. The answer below figured out what I meant.
– spindoctor
yesterday