Plot multiple histograms with purrr::map and ggplot2











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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)









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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

















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)









share|improve this question
























  • 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















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)









share|improve this question















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






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edited Nov 10 at 14:57









Richard Telford

5,72742335




5,72742335










asked Nov 10 at 12:00









spindoctor

366218




366218












  • 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




















  • 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


















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














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)





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    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)





    share|improve this answer



























      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)





      share|improve this answer

























        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)





        share|improve this answer














        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)






        share|improve this answer














        share|improve this answer



        share|improve this answer








        edited Nov 10 at 14:57

























        answered Nov 10 at 12:15









        Richard Telford

        5,72742335




        5,72742335






























             

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