From 4b1cec93329a13f2dbb22c61052b2ec2e19225da Mon Sep 17 00:00:00 2001 From: Andree Valle Campos Date: Mon, 24 Jun 2024 18:12:53 +0100 Subject: [PATCH] add text edits from review --- episodes/describe-cases.Rmd | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/episodes/describe-cases.Rmd b/episodes/describe-cases.Rmd index bac21804..ee8a0a29 100644 --- a/episodes/describe-cases.Rmd +++ b/episodes/describe-cases.Rmd @@ -257,7 +257,7 @@ confidence interval and using 100 bootstrap samples. `{incidence2}` produces basic plots for epicurves, but additional work is required to create well-annotated graphs. However, using the `{ggplot2}` package, you can generate more sophisticated and better-annotated epicurves. -`{ggplot2}` is a comprehensive package with many functionalities, but we will focus on three key elements essential for producing epicurves: histogram plots, scaling date axes and their labels, and general plot theme annotation. +`{ggplot2}` is a comprehensive package with many functionalities. However, we will focus on three key elements for producing epicurves: histogram plots, scaling date axes and their labels, and general plot theme annotation. The example below demonstrates how to configure these three elements for a simple `{incidence2}` object. ```{r, message=FALSE, warning=FALSE} @@ -301,7 +301,8 @@ ggplot2::ggplot(data = dialy_incidence_data) + ) ``` -To visualize an epicurve with different groups, use the group option in the mapping function. If there is more than one grouping factor, use the facet_wrap option, as demonstrated in the example below +Use the `group` option in the mapping function to visualize an epicurve with different groups. If there is more than one grouping factor, use the `facet_wrap()` option, as demonstrated in the example below: + ```{r, message=FALSE, warning=FALSE} ggplot2::ggplot(data = dialy_incidence_data_2) + geom_histogram(