In this vignette we will demo how to visualize data which is only available in summary format as it is coming from a published paper table or figure for example Figure 3 from this paper:
“Remdesivir for the Treatment of Covid-19 — Final Report”
JH Beigel et al. N Engl J Med 2020. DOI: 10.1056/NEJMoa2007764
The data has been made available in a csv data file named remdesivirfig3.csv
library(ggquickeda) #load ggquickeda
remdesivirdata <- read.csv("./remdesivirfig3.csv") # in vignette folder
knitr::kable(remdesivirdata)
Subgroup | Subgroupvalue | Subgroupvalueorder | N.of.patients | Recovery.Rate.Ratio | RRLCI | RRUCI |
---|---|---|---|---|---|---|
All Patients | All Patients | 1 | 1062 | 1.29 | 1.12 | 1.49 |
Geographic Region | North America | 2 | 847 | 1.30 | 1.10 | 1.53 |
Geographic Region | Europe | 3 | 163 | 1.30 | 0.91 | 1.87 |
Geographic Region | Asia | 4 | 52 | 1.36 | 0.74 | 2.47 |
Race | White | 5 | 566 | 1.29 | 1.06 | 1.57 |
Race | Black | 6 | 226 | 1.25 | 0.91 | 1.72 |
Race | Asian | 7 | 135 | 1.07 | 0.73 | 1.58 |
Race | Other | 8 | 125 | 1.68 | 1.10 | 2.58 |
Ethnin group | Hispanic or Latino | 9 | 250 | 1.28 | 0.94 | 1.73 |
Ethnin group | Not Hispanic or Latino | 10 | 755 | 1.31 | 1.10 | 1.55 |
Age | 18 to < 40 yr | 11 | 119 | 1.95 | 1.28 | 2.97 |
Age | 40 to < 65 yr | 12 | 559 | 1.19 | 0.98 | 1.44 |
Age | >= 65 yr | 13 | 384 | 1.29 | 1.00 | 1.67 |
Sex | Male | 14 | 684 | 1.30 | 1.09 | 1.56 |
Sex | Female | 15 | 278 | 1.31 | 1.03 | 1.66 |
Sympoms duration | <= 10 days | 16 | 676 | 1.37 | 1.14 | 1.64 |
Sympoms duration | > 10 days | 17 | 383 | 1.20 | 0.94 | 1.52 |
Baseline Ordinal Score | 4 (not receiving oxygen) | 18 | 138 | 1.29 | 0.91 | 1.83 |
Baseline Ordinal Score | 5 (receiving oxygen) | 19 | 435 | 1.45 | 1.18 | 1.79 |
Baseline Ordinal Score | 6 (receiving high-flow oxygen) | 20 | 193 | 1.09 | 0.76 | 1.57 |
Baseline Ordinal Score | 7 (receicing mv or ECMO) | 21 | 285 | 0.98 | 0.70 | 1.36 |
Summary Data Mapping
Graph Splitting
We still have to set text formatting options using the group of subtabs in the lower part of the page:
At this point you should have this graph:
Facet Options
reordering of subgroup
While you can add another variable and manually drag and drop we will demo next another possibility to reorder yvalues using a statistic of another variable e.g. median:
reordering of Subgroupvalue
### Setting Titles, Captions and Logging the X axis
And now you should get the below plot !:
ggquickeda
As an example of even more advanced features consider the screenshot below where the N of patients as well as the Intervals Values are shown.
more options