Visualizing Summary Data"

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

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{width=100%}

Published Data

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)

Load the Data into the app

# from R launch the app with the data 
#run_ggquickeda(remdesivirdata) 
# if you have access the the app on a server browse to the file and load it

X/Y Mappings and Splitting Options

Summary Data Mapping{width=70%}

Graph Splitting{width=70%}

Facets Options

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{width=100%}

Ordering of Variables and Values

reordering of subgroup{width=50%}

While you can add another variable and manually drag and drop we will demo next another possibility to reorder yvalues using a statistic (e.g. median) of another variable (Subroupvalueorder):

reordering of Subgroupvalue{width=50%}

Remove Default Points and add a Point Interval

Median/PI options{width=75%}

Setting Titles, Captions and Logging the X axis

And now you should get the below plot !: xy label options{width=100%}

Example of what is Possible with ggquickeda

As an example of even more advanced features consider the screenshot below where the Intervals Values are shown while the point Size is proportional to the N of patients. Some theme adjustments to customize the plot and legend were also done.

more options{width=100%}



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ggquickeda documentation built on June 22, 2021, 5:08 p.m.