Merge pull request #54 from moj-analytical-services/purl-options

Update purl options

R_code_participant.R

@@ -1,37 +1,21 @@
-## ----include=FALSE---------------------------------------------------------------------------------------------------
-knitr::opts_chunk$set(message = FALSE, warning = FALSE, cache = FALSE)
-
-
-
-## ----fig.height=4, fig.width=5---------------------------------------------------------------------------------------
 # Random number seed
 set.seed(5)
 
 # Scatter plot
 plot(rnorm(20), rnorm(20))
 
-
-## ----highlight=TRUE--------------------------------------------------------------------------------------------------
 import::from("ggplot2", "aes", "vars", "mpg")
 
-
-## --------------------------------------------------------------------------------------------------------------------
 # Examine the mpg dataset
 dplyr::glimpse(mpg)
 
-
-## ----fig.height=3, fig.width=4---------------------------------------------------------------------------------------
 ggplot2::ggplot(data = mpg, aes(x = displ, y = hwy)) +
   ggplot2::geom_point()
 
-
-## ----fig.height=3, fig.width=4---------------------------------------------------------------------------------------
 ggplot2::ggplot(data = mpg, aes(x = displ, y = hwy)) +
   ggplot2::geom_point() +
   ggplot2::geom_point(aes(x = displ, y = cty), colour = "blue")
 
-
-## ----eval = FALSE----------------------------------------------------------------------------------------------------
 ## # chart template
 ## ggplot(data = <DATA>, aes(<MAPPINGS>) )  +
 ##   <GEOM_FUNCTION> +
@@ -40,166 +24,116 @@ ggplot2::ggplot(data = mpg, aes(x = displ, y = hwy)) +
 ##   <SCALE_FUNCTION> +
 ##   <THEME FUNCTION>
 
-
-## ----fig.height=3, fig.width=6---------------------------------------------------------------------------------------
 # Aesthetics
 ggplot2::ggplot(data = mpg, aes(x = displ, y = hwy, colour = class)) +
   ggplot2::geom_point()
 
-
-## ----fig.height=4, fig.width=8---------------------------------------------------------------------------------------
 # ggplot2 looks at the data type to set a default colour scale
 ggplot2::ggplot(data = mpg, aes(x = displ, y = hwy, colour = year)) +
   ggplot2::geom_point()
 
-
-## ----fig.height=4, fig.width=8---------------------------------------------------------------------------------------
 # You can also use shapes to distinguish between categories
 ggplot2::ggplot(data = mpg, aes(x = displ, y = hwy, shape = class, colour = class)) +
   ggplot2::geom_point()
 
-
-## ----fig.height=4, fig.width=8---------------------------------------------------------------------------------------
 # Some aesthetics are only suitable in certain situations
 ggplot2::ggplot(data = mpg, aes(x = displ, y = hwy, shape = class, colour = class)) +
   ggplot2::geom_point()
 
-
-## ----fig.height=3.5, fig.retina=2------------------------------------------------------------------------------------
 # Use scale_ functions to set properties of the aesthetics
 dplyr::filter(mpg, manufacturer %in% c('audi', 'volkswagen')) |> 
   ggplot2::ggplot(aes(x = displ, y = hwy, colour = manufacturer)) +
   ggplot2::geom_point(size = 3) +
   ggplot2::scale_colour_manual(values = c("audi" = "#12436D", "volkswagen" = "#28A197")) +
   ggplot2::scale_x_continuous(limits = c(1, 5))
 
-
-## ----fig.height=4, fig.width=8---------------------------------------------------------------------------------------
 # Set an aesthetic to a fixed value
 ggplot2::ggplot(data = mpg, aes(x = displ, y = hwy)) +
   ggplot2::geom_point(colour = "orange")
 
-
-## ----fig.height=3, fig.width=5---------------------------------------------------------------------------------------
 # What's wrong with this code? Why aren't the points blue?
 ggplot2::ggplot(data = mpg, aes(x = displ, y = hwy, colour = "blue")) +
   ggplot2::geom_point()
 
-
-## ----fig.height=3----------------------------------------------------------------------------------------------------
 ggplot2::ggplot(data = mpg, aes(x = displ, y = hwy)) +
   ggplot2::geom_point() +
   ggplot2::facet_wrap(vars(class))
 
-
-## --------------------------------------------------------------------------------------------------------------------
 ggplot2::ggplot(data = mpg, aes(x = displ, y = hwy)) +
   ggplot2::geom_point() +
   ggplot2::facet_grid(rows = vars(drv), cols = vars(class))
 
-
-## ----fig.height=3----------------------------------------------------------------------------------------------------
 # What is wrong with this plot?
 ggplot2::ggplot(data = mpg, aes(x = cty, y = hwy)) +
   ggplot2::geom_point()
 
-
-## ----fig.height=3----------------------------------------------------------------------------------------------------
 # Because there are multiple observations, some are **overplotted**. To correct this, you can add 
 # some random noise to the data with `position="jitter"` or `geom_jitter`.
 ggplot2::ggplot(data = mpg, aes(x = cty, y = hwy)) +
   ggplot2::geom_jitter(colour = 'red') +
   ggplot2::geom_point()
 
-
-## ----fig.height=3----------------------------------------------------------------------------------------------------
 ggplot2::ggplot(data = mpg, aes(x = displ, y = hwy)) +
   ggplot2::geom_smooth()
 
-
-## ----fig.height=3----------------------------------------------------------------------------------------------------
 # We can add the points as well, using the + operator
 ggplot2::ggplot(data = mpg, aes(x = displ, y = hwy)) +
   ggplot2::geom_smooth() +
   ggplot2::geom_point() +
   ggplot2::geom_line(aes(x = 4.5))
 
-
-## ----fig.height=3, fig.width=9---------------------------------------------------------------------------------------
 # Bar charts counting rows in the data
 ggplot2::ggplot(data = mpg, aes(x = class)) +
   ggplot2::geom_bar()
 
-
-## ----fig.height=3, fig.width=9---------------------------------------------------------------------------------------
 # Bar charts from tabulated data
 mpg |>
   dplyr::group_by(class) |> 
   dplyr::summarise(count = dplyr::n()) |> 
   ggplot2::ggplot(aes(x = class, y = count)) +
   ggplot2::geom_col() 
 
-
-## ----fig.height=3, fig.width=9---------------------------------------------------------------------------------------
 # Bar chart positioning
 ggplot2::ggplot(data = mpg, aes(x = manufacturer, fill = class)) +
   ggplot2::geom_bar(colour = 'black') +
   ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 90, vjust = 0, hjust = 1))
 
-
-## ----fig.height=3----------------------------------------------------------------------------------------------------
 # By default bars are "stacked" on top of each other. This makes comparing proportions rather difficult. 
 # You can control this with the position argument.
 ggplot2::ggplot(data = mpg, aes(x = manufacturer, fill = class)) +
   ggplot2::geom_bar(colour = 'black', position = 'dodge') +
   ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 90, vjust = 0, hjust = 1))
 
-
-## ----fig.height=3----------------------------------------------------------------------------------------------------
 # Histogram
 ggplot2::ggplot(data = mpg, aes(x = hwy)) +
   ggplot2::geom_histogram(bins = 30) 
 
-
-## ----fig.height=3----------------------------------------------------------------------------------------------------
 # Density plot
 ggplot2::ggplot(data = mpg, aes(x = hwy)) +
   ggplot2::geom_density() 
 
-
-## ----fig.height=3----------------------------------------------------------------------------------------------------
 # Overlapping density plots
 ggplot2::ggplot(data = mpg, aes(x = hwy, fill = drv)) +
   ggplot2::geom_density(alpha = 0.5) 
 
-
-## ----fig.height=3----------------------------------------------------------------------------------------------------
 # Box plots
 ggplot2::ggplot(data = mpg, aes(x = drv, y = hwy)) +
   ggplot2::geom_boxplot(fill = "red")
 
-
-## ----fig.height=3----------------------------------------------------------------------------------------------------
 # Violin plots
 ggplot2::ggplot(data = mpg, aes(x = drv, y = hwy)) +
   ggplot2::geom_violin(aes(fill = drv))
 
-
-## ----fig.height=3----------------------------------------------------------------------------------------------------
 # Line charts
 ggplot2::economics |> 
   ggplot2::ggplot(aes(x = date, y = unemploy)) +
   ggplot2::geom_line()
 
-
-## ----fig.height=3----------------------------------------------------------------------------------------------------
 # Themes, titles, and multiple plots
 ggplot2::ggplot(data = mpg, aes(x = class, y = ggplot2::after_stat(prop), group = 1)) +
   ggplot2::geom_bar() +
   ggplot2::labs(title = "Proportion of sample by class", x = "Class", y = "Proportion")
 
-
-## --------------------------------------------------------------------------------------------------------------------
 # Multiple plots
 plot1 <-
   ggplot2::ggplot(data = mpg, aes(x = cyl, y = ggplot2::after_stat(prop), group = 1)) +
@@ -217,21 +151,15 @@ plot2 <-
                 y = "Highway fuel efficiency")
 
 
-
-## --------------------------------------------------------------------------------------------------------------------
 # gridExtra
 gridExtra::grid.arrange(plot1, plot2, nrow = 1)
 
 
-
-## ----fig.height=5, fig.width=8---------------------------------------------------------------------------------------
 # Themes
 gridExtra::grid.arrange(
   plot2 + ggplot2::theme_bw(), plot2 + ggplot2::theme_classic(), 
   plot2 + ggplot2::theme_dark(), plot2 + ggplot2::theme_light())
 
-
-## ----fig.height=3----------------------------------------------------------------------------------------------------
 # You can also make your own custom themes
 ugly_theme <-
   ggplot2::theme(
@@ -242,28 +170,19 @@ ugly_theme <-
   )
 
 
-
-## ----fig.height=3----------------------------------------------------------------------------------------------------
 plot2 + ugly_theme
 
-
-## ----fig.height=3----------------------------------------------------------------------------------------------------
 # MoJ colour scheme
 ggplot2::ggplot(data = mpg, aes(x = class, fill = drv)) +
   ggplot2::geom_bar(position = "dodge") +
   mojchart::scale_fill_moj(n = 3) +
   mojchart::theme_gss(xlabel = TRUE)
 
-
-## ----fig.height=3----------------------------------------------------------------------------------------------------
 # Accessible colour scheme
 ggplot2::ggplot(data = mpg, aes(x = class, fill = drv)) +
   ggplot2::geom_bar(position = "dodge") +
   mojchart::scale_fill_moj(n = 3, scheme = "govanal_bars") +
   mojchart::theme_gss(xlabel = TRUE)
 
-
-## ----eval=FALSE, results=FALSE---------------------------------------------------------------------------------------
 ## ggplot2::ggplot(data = mpg) +
 ##    ggplot2::geom_point(mapping = aes(x = hwy, y = cty, colour = as.factor(cyl)))
-

index.Rmd

@@ -14,7 +14,7 @@ output:
     highlight: tango
 ---
 
-```{r, include=FALSE}
+```{r, include=FALSE, purl=FALSE}
 knitr::opts_chunk$set(message = FALSE, warning = FALSE, cache = FALSE)
 
 ```

render_r_code_from_source.R

@@ -2,6 +2,6 @@
 # Convert the index.Rmd content to an R script for ease of use by the participants. Only
 # code cells will be converted.
 
-knitr::purl("index.Rmd")
+knitr::purl("index.Rmd", documentation = 0)
 
 file.rename("index.R", "R_code_participant.R")