Help with bar charts

[lolafh]

Hi everyone,

Fairly new R user biting off more than I can chew ...

I'm trying to compare multiple variables in a bar chart and need some help.
I'm comparing side effects of medication vs placebo for multiple trials.

The x axis would have multiple side effects of interest (e.g fever, pain, headache) with placebo and drug "dodged" next to each other. Y would be the % of participants in that trial reporting those side effects. A good example of what I'm trying to do can be seen in figure 2 here: https://www.nejm.org/doi/full/10.1056/nejmoa2107456

Alternatively, I could compare different clinical trials but limited to 1 side effect of interest.

rough idea of the data looks like (minimal provided) and I'm happy formatting and uploading as a CSV.

Study1A<-c('Walter et al', 34, 31, 74, 31)
names(Study1A) <-c('Study', 'Fatigue Vaccine', 'Fatigue Placebo', 'Inj site pain vaccine', 'Inj site pain Plac')

Study2a<-c('Frenck et al',60,41,86,23)
names(Study2a)<-c('Study','Fatigue Vaccine', 'Fatigue Placebo', 'Inj site pain vaccine', 'Inj site pain Placbeo')

Study3a<-c('Ali et al',47.9,36.6,93.1,34.8)
names(Study3a)<-c('Study', 'Fatigue Vaccine', 'Fatigue Placebo', 'Inj site pain vaccine', 'Inj site pain Placbeo')

Thanks!

[nirgrahamuk]

Here is a very good tutorial on graphing in R generally.
3 Data visualisation | R for Data Science (had.co.nz)

[FJCC]

I agree with @nirgrahamuk about the tutorial. I will add some general advice about data layout.

1. You must not mix characters and numeric values in a vector. That will force everything in the vector to be characters.
2. Do not have column names with spaces. It can be done but it introduces needless complexity.
3. Have each column of your data represent one thing. Instead of having a column that shows both the symptom (Fatigue or Pain) and whether the subject was in the vaccine or placebo cohort, have one column for the symptom and one for the cohort.
4. Do not put data in the column headers. Instead of having a column for each study, make a column that stores the study name.

In the code below, I rearrange your data to satisfy those rules and then make a plot. The data wrangling will probably be rather confusing to a beginner. Focus on the difference between your original data and what I end up with.

Walter_et_al <-  c(34, 31, 74, 31)
#names(Study1A) <-c('Study', 'Fatigue Vaccine', 'Fatigue Placebo', 'Inj site pain vaccine', 'Inj site pain Placebo')

Frenck_et_al <- c(60,41,86,23)
#names(Study2a)<-c('Study','Fatigue Vaccine', 'Fatigue Placebo', 'Inj site pain vaccine', 'Inj site pain Placbeo')

Ali_et_al <- c(47.9,36.6,93.1,34.8)
#names(Study3a)<-c('Study', 'Fatigue Vaccine', 'Fatigue Placebo', 'Inj site pain vaccine', 'Inj site pain Placbeo')

Category <- c('Fatigue Vaccine', 'Fatigue Placebo', 'Inj site pain Vaccine', 'Inj site pain Placebo')

DF <- data.frame(Category, Walter_et_al, Frenck_et_al, Ali_et_al)
DF
#>                Category Walter_et_al Frenck_et_al Ali_et_al
#> 1       Fatigue Vaccine           34           60      47.9
#> 2       Fatigue Placebo           31           41      36.6
#> 3 Inj site pain Vaccine           74           86      93.1
#> 4 Inj site pain Placebo           31           23      34.8
library(tidyverse)
#> Warning: package 'tibble' was built under R version 4.1.2
DF <- DF |> mutate(Cohort = str_extract(Category, "[:alpha:]+$"),
                   Category = str_trim(str_remove(Category, "[:alpha:]+$")))
DF
#>        Category Walter_et_al Frenck_et_al Ali_et_al  Cohort
#> 1       Fatigue           34           60      47.9 Vaccine
#> 2       Fatigue           31           41      36.6 Placebo
#> 3 Inj site pain           74           86      93.1 Vaccine
#> 4 Inj site pain           31           23      34.8 Placebo
DFlong <- DF |> pivot_longer(Walter_et_al:Ali_et_al, names_to = "Study")
DFlong
#> # A tibble: 12 x 4
#>    Category      Cohort  Study        value
#>    <chr>         <chr>   <chr>        <dbl>
#>  1 Fatigue       Vaccine Walter_et_al  34  
#>  2 Fatigue       Vaccine Frenck_et_al  60  
#>  3 Fatigue       Vaccine Ali_et_al     47.9
#>  4 Fatigue       Placebo Walter_et_al  31  
#>  5 Fatigue       Placebo Frenck_et_al  41  
#>  6 Fatigue       Placebo Ali_et_al     36.6
#>  7 Inj site pain Vaccine Walter_et_al  74  
#>  8 Inj site pain Vaccine Frenck_et_al  86  
#>  9 Inj site pain Vaccine Ali_et_al     93.1
#> 10 Inj site pain Placebo Walter_et_al  31  
#> 11 Inj site pain Placebo Frenck_et_al  23  
#> 12 Inj site pain Placebo Ali_et_al     34.8
ggplot(DFlong, aes(x = Category, y = value, fill = Cohort)) +
  geom_col(position = "dodge") + facet_wrap(~ Study, nrow = 1)

^{Created on 2022-05-10 by the reprex package (v2.0.1)}