Dumbbell plot: Order and value label

Question

I am working on a dumbbell plot in R inspired by this post, and have two problems:

Ordering the dumbbell plot (I've tried a strategy provided in this post)
Present value labels in the plot in an aesthetically pleasing way.

My data set is formatted as a wide data set with 18 units with the following structure:

> head(ADHD_med_2010_2018_wide, 18)
# A tibble: 18 x 9
         age           gender                county adhd_pr_1000_2010 adhd_pr_1000_2018 county_label     adhd_2010 adhd_2018   diff
   <dbl+lbl>        <dbl+lbl>             <dbl+lbl>             <dbl>             <dbl> <fct>                <dbl>     <dbl>  <dbl>
 1 2 [10-14] 1 [Both genders]  1 [Østfold]                       32.1              24.3 Østfold               32.1      24.3  -7.80
 2 2 [10-14] 1 [Both genders]  2 [Akershus]                      20.6              23.0 Akershus              20.6      23     2.40
 3 2 [10-14] 1 [Both genders]  3 [Oslo]                          17.2              33.9 Oslo                  17.2      33.9  16.7 
 4 2 [10-14] 1 [Both genders]  4 [Hedmark]                       41.7              30.9 Hedmark               41.7      30.9 -10.8 
 5 2 [10-14] 1 [Both genders]  5 [Oppland]                       24.9              39.0 Oppland               24.9      39    14.1 
 6 2 [10-14] 1 [Both genders]  6 [Buskerud]                      26.7              36.8 Buskerud              26.7      36.8  10.1 
 7 2 [10-14] 1 [Both genders]  7 [Vestfold]                      28.1              27.1 Vestfold              28.1      27    -1.10
 8 2 [10-14] 1 [Both genders]  8 [Telemark]                      29.2              24.7 Telemark              29.2      24.7  -4.5 
 9 2 [10-14] 1 [Both genders]  9 [Aust-Agder]                    34.9              39.2 Aust-Agder            34.9      39.2   4.30
10 2 [10-14] 1 [Both genders] 10 [Vest-Agder]                    17.4              23.8 Vest-Agder            17.4      23.8   6.40
11 2 [10-14] 1 [Both genders] 11 [Rogaland]                      29.5              13.8 Rogaland              29.5      13.8 -15.7 
12 2 [10-14] 1 [Both genders] 12 [Hordaland]                     21.3              14.4 Hordaland             21.3      14.4  -6.90
13 2 [10-14] 1 [Both genders] 14 [Sogn og Fjordane]              21.3              39.7 Sogn og Fjordane      21.3      39.7  18.4 
14 2 [10-14] 1 [Both genders] 15 [Møre og Romsdal]               27.0              18.6 Møre og Romsdal       27        18.6  -8.40
15 2 [10-14] 1 [Both genders] 18 [Nordland]                      40.1              30.0 Nordland              40.1      30   -10.1 
16 2 [10-14] 1 [Both genders] 19 [Troms]                         25.8              33.2 Troms                 25.8      33.2   7.40
17 2 [10-14] 1 [Both genders] 20 [Finnmark]                      19.1              21.3 Finnmark              19.1      21.3   2.20
18 2 [10-14] 1 [Both genders] 50 [Trøndelag]                     25.0              36.9 Trøndelag             25        37    12

I've tried two strategies for problem 1:

library("tidyverse")
library("ggalt")
fig2 <- ggplot(ADHD_med_2010_2018_wide, aes(x=adhd_2010, xend=adhd_2018, y=county_label, group=county_label)) + 
      #create a thick line between x and xend instead of using defaut 
      #provided by geom_dubbell
      geom_segment(aes(x=adhd_2010, 
                       xend=adhd_2018, 
                       y=county_label, 
                       yend=county_label), 
                   color="#b2b2b2", size=1.5)+
      geom_dumbbell(color="light blue", 
                    size_x=3.5, 
                    size_xend = 3.5,
                    #Note: there is no US:'color' for UK:'colour' 
                    # in geom_dumbbel unlike standard geoms in ggplot()
                    colour_x="forestgreen", # green = 2010
                    colour_xend = "red")+ # red = 2018
      labs(x=NULL, y=NULL, 
           title="Dumbbell Chart", 
           subtitle="Change in prescription rate: 2010 vs 2018")+
      geom_text(color="black", size=2, hjust=-0.5,
                aes(x=adhd_2010, label=adhd_2010))+
      geom_text(aes(x=adhd_2018, label=adhd_2018), 
                color="black", size=2, hjust=1.5)
    fig2

Which gives a plot without ordering or values presented in a good way:

To correct ordering, I tried following the strategy provided in the post linked above:

library(dplyr)

ADHD_med_2010_2018_wide%>%
  mutate(difference = abs(adhd_2018-adhd_2010)) %>% #creates the variable of differences
  top_n(18, wt = difference) %>% # Choose the rows with top 20 difference
  ggplot() +
  aes(x=adhd_2010, xend=adhd_2018, y=reorder(county_label, difference), 
      group=county_label) + #reorder the labels by descending difference value
  geom_dumbbell(color="light blue", 
                size_x=3.5, 
                size_xend = 3.5,
                #Note: there is no US:'color' for UK:'colour' 
                # in geom_dumbbel unlike standard geoms in ggplot()
                colour_x="forestgreen", # green = 2010
                colour_xend = "red")+ # red = 2018
  labs(x=NULL, y=NULL, 
       title="Dumbbell Chart", 
       subtitle="Change in prescription rate: 2010 vs 2018")+
  geom_text(color="black", size=2, hjust=-0.5,
            aes(x=adhd_2010, label=adhd_2010))+
  geom_text(aes(x=adhd_2018, label=adhd_2018), 
            color="black", size=2, hjust=1.5)

This still does not give a plot with a nice ordering, although it seem to order the difference (and there's still the issue with value labels):

Hopefully some of you may have input on these issues.

Data to copy:

> dput(head(ADHD_med_2010_2018_wide, 18))
structure(list(age = structure(c(2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2), label = "Age groups", labels = c(`5-9` = 1, 
`10-14` = 2, `15-19` = 3, `20-24` = 4, `25-29` = 5, `30-34` = 6, 
`All ages` = 7), class = "haven_labelled"), gender = structure(c(1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), label = "Gender", labels = c(`Both genders` = 1, 
Female = 2, Male = 3), class = "haven_labelled"), county = structure(c(1, 
2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 18, 19, 20, 50), labels = c(Østfold = 1, 
Akershus = 2, Oslo = 3, Hedmark = 4, Oppland = 5, Buskerud = 6, 
Vestfold = 7, Telemark = 8, `Aust-Agder` = 9, `Vest-Agder` = 10, 
Rogaland = 11, Hordaland = 12, `Sogn og Fjordane` = 14, `Møre og Romsdal` = 15, 
Nordland = 18, Troms = 19, Finnmark = 20, Trøndelag = 50, `Hele landet` = 99
), class = "haven_labelled"), adhd_pr_1000_2010 = c(32.1488990783691, 
20.5894756317139, 17.2119483947754, 41.6982574462891, 24.8543014526367, 
26.7194156646729, 28.1328239440918, 29.2480430603027, 34.8775291442871, 
17.3759765625, 29.4698066711426, 21.340311050415, 21.3308296203613, 
27.0334072113037, 40.1140670776367, 25.7862873077393, 19.1311283111572, 
25.0325565338135), adhd_pr_1000_2018 = c(24.2834396362305, 23.0037822723389, 
33.9068183898926, 30.8641967773438, 39.0195579528809, 36.7909698486328, 
27.0642204284668, 24.6901988983154, 39.1978950500488, 23.8095245361328, 
13.8218154907227, 14.4400091171265, 39.7175636291504, 18.5994052886963, 
29.9642810821533, 33.1638412475586, 21.2596340179443, 36.9249382019043
), county_label = structure(18:1, .Label = c("Trøndelag", "Finnmark", 
"Troms", "Nordland", "Møre og Romsdal", "Sogn og Fjordane", "Hordaland", 
"Rogaland", "Vest-Agder", "Aust-Agder", "Telemark", "Vestfold", 
"Buskerud", "Oppland", "Hedmark", "Oslo", "Akershus", "Østfold"
), class = "factor"), adhd_2010 = c(32.0999984741211, 20.6000003814697, 
17.2000007629395, 41.7000007629395, 24.8999996185303, 26.7000007629395, 
28.1000003814697, 29.2000007629395, 34.9000015258789, 17.3999996185303, 
29.5, 21.2999992370605, 21.2999992370605, 27, 40.0999984741211, 
25.7999992370605, 19.1000003814697, 25), adhd_2018 = c(24.2999992370605, 
23, 33.9000015258789, 30.8999996185303, 39, 36.7999992370605, 
27, 24.7000007629395, 39.2000007629395, 23.7999992370605, 13.8000001907349, 
14.3999996185303, 39.7000007629395, 18.6000003814697, 30, 33.2000007629395, 
21.2999992370605, 37), diff = c(-7.79999923706055, 2.39999961853027, 
16.7000007629395, -10.8000011444092, 14.1000003814697, 10.0999984741211, 
-1.10000038146973, -4.5, 4.29999923706055, 6.39999961853027, 
-15.6999998092651, -6.89999961853027, 18.4000015258789, -8.39999961853027, 
-10.0999984741211, 7.40000152587891, 2.19999885559082, 12)), row.names = c(NA, 
-18L), class = c("tbl_df", "tbl", "data.frame"))

Can you share a reproducible example of your dataframe ? (see here: https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example) — dc37, Mar 03 '20 at 23:20
Sure! I've updated head() so you can see observations for the 18 units. — Wissenschaft, Mar 03 '20 at 23:31
Thank you but it is not easy to copy/paste for running into our r sessions. Instead, can you provide the output of `dput(head(ADHD_med_2010_2018_wide, 18))` ? — dc37, Mar 03 '20 at 23:33
Thanks! Still relatively new to R and didn't know about this command. Added it to end of my post. — Wissenschaft, Mar 03 '20 at 23:36

score 3 · Accepted Answer · answered Mar 03 '20 at 23:47

Here an easy way to order your plot is to use arrange function from dplyr to sort your dataframe according column(s) of your choice and then format the grouping value (county_label) as factor with the ranked elements:

library(dplyr)
library(ggplot2)
DF %>% arrange(adhd_2010) %>% mutate(county_label = factor(county_label, unique(county_label))) %>%
  ggplot(aes(x=adhd_2010, xend=adhd_2018, y=county_label, group=county_label)) + 
  #create a thick line between x and xend instead of using defaut 
  #provided by geom_dubbell
  geom_segment(aes(x=adhd_2010, 
                   xend=adhd_2018, 
                   y=county_label, 
                   yend=county_label), 
               color="#b2b2b2", size=1.5)+
  geom_dumbbell(color="light blue", 
                size_x=3.5, 
                size_xend = 3.5,
                #Note: there is no US:'color' for UK:'colour' 
                # in geom_dumbbel unlike standard geoms in ggplot()
                colour_x="forestgreen", # green = 2010
                colour_xend = "red")+ # red = 2018
  labs(x=NULL, y=NULL, 
       title="Dumbbell Chart", 
       subtitle="Change in prescription rate: 2010 vs 2018")+
  geom_text(color="black", size=2, hjust=-0.5,
            aes(x=adhd_2010, label=adhd_2010))+
  geom_text(aes(x=adhd_2018, label=adhd_2018), 
            color="black", size=2, hjust=1.5)

It is not perfect but at least your values are quite ordered. After you can change the column by which you wish to order your plot (here I order based on adhd_2010)

Thank you! This looks way better, and I'll look more into different specifications of arrange. — Wissenschaft, Mar 04 '20 at 09:27

Foo Cheung · Answer 2 · 2021-02-26T05:46:03.717

# Reformat data
DF2<-DF%>%  arrange(desc(adhd_2010))
DF3<-DF%>% mutate("key" = "Change in Prescription Rate")
DF3$county_label<-factor(DF3$county_label,DF2$county_label)
DF3$adhd_2018<-signif(DF3$adhd_2018, digits = 3)
DF3$adhd_2010<-signif(DF3$adhd_2010, digits = 3)

# Plot
dumbbell::dumbbell(DF3, id="county_label", key="key", column1="adhd_2010", column2="adhd_2018", lab1="2010", lab2="2018", delt=1, textsize = 2, pt_val =1, ,pointsize = 2) + xlim(13,43) + 
labs(x=NULL, y=NULL, title="Dumbbell Chart",subtitle="Change in prescription rate: 2010 vs 2018")

I added in a few bells and whistles, just toggle the options to remove I hope someone finds it useful

Enjoy!

Dumbbell plot: Order and value label

2 Answers2