Merge pull request #51 from moj-analytical-services/alter_first_question

Alter first question in exercises

R_code_participant.R

@@ -1,37 +1,37 @@
-## ----include=FALSE---------------------------------------------------------------------------------------------------------------
+## ----include=FALSE---------------------------------------------------------------------------------------------------
 knitr::opts_chunk$set(message = FALSE, warning = FALSE, cache = FALSE)
 
 
 
-## ----fig.height=4, fig.width=5---------------------------------------------------------------------------------------------------
+## ----fig.height=4, fig.width=5---------------------------------------------------------------------------------------
 # Random number seed
 set.seed(5)
 
 # Scatter plot
 plot(rnorm(20), rnorm(20))
 
 
-## ----highlight=TRUE--------------------------------------------------------------------------------------------------------------
+## ----highlight=TRUE--------------------------------------------------------------------------------------------------
 import::from("ggplot2", "aes", "vars", "mpg")
 
 
-## --------------------------------------------------------------------------------------------------------------------------------
+## --------------------------------------------------------------------------------------------------------------------
 # Examine the mpg dataset
 dplyr::glimpse(mpg)
 
 
-## ----fig.height=3, fig.width=4---------------------------------------------------------------------------------------------------
+## ----fig.height=3, fig.width=4---------------------------------------------------------------------------------------
 ggplot2::ggplot(data = mpg, aes(x = displ, y = hwy)) +
   ggplot2::geom_point()
 
 
-## ----fig.height=3, fig.width=4---------------------------------------------------------------------------------------------------
+## ----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----------------------------------------------------------------------------------------------------------------
+## ----eval = FALSE----------------------------------------------------------------------------------------------------
 ## # chart template
 ## ggplot(data = <DATA>, aes(<MAPPINGS>) )  +
 ##   <GEOM_FUNCTION> +
@@ -41,31 +41,31 @@ ggplot2::ggplot(data = mpg, aes(x = displ, y = hwy)) +
 ##   <THEME FUNCTION>
 
 
-## ----fig.height=3, fig.width=6---------------------------------------------------------------------------------------------------
+## ----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---------------------------------------------------------------------------------------------------
+## ----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---------------------------------------------------------------------------------------------------
+## ----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---------------------------------------------------------------------------------------------------
+## ----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------------------------------------------------------------------------------------------------
+## ----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)) +
@@ -74,64 +74,64 @@ dplyr::filter(mpg, manufacturer %in% c('audi', 'volkswagen')) |>
   ggplot2::scale_x_continuous(limits = c(1, 5))
 
 
-## ----fig.height=4, fig.width=8---------------------------------------------------------------------------------------------------
+## ----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---------------------------------------------------------------------------------------------------
+## ----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----------------------------------------------------------------------------------------------------------------
+## ----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----------------------------------------------------------------------------------------------------------------
+## ----fig.height=3----------------------------------------------------------------------------------------------------
 # What is wrong with this plot?
 ggplot2::ggplot(data = mpg, aes(x = cty, y = hwy)) +
   ggplot2::geom_point()
 
 
-## ----fig.height=3----------------------------------------------------------------------------------------------------------------
+## ----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----------------------------------------------------------------------------------------------------------------
+## ----fig.height=3----------------------------------------------------------------------------------------------------
 ggplot2::ggplot(data = mpg, aes(x = displ, y = hwy)) +
   ggplot2::geom_smooth()
 
 
-## ----fig.height=3----------------------------------------------------------------------------------------------------------------
+## ----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---------------------------------------------------------------------------------------------------
+## ----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---------------------------------------------------------------------------------------------------
+## ----fig.height=3, fig.width=9---------------------------------------------------------------------------------------
 # Bar charts from tabulated data
 mpg |>
   dplyr::group_by(class) |> 
@@ -140,66 +140,66 @@ mpg |>
   ggplot2::geom_col() 
 
 
-## ----fig.height=3, fig.width=9---------------------------------------------------------------------------------------------------
+## ----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----------------------------------------------------------------------------------------------------------------
+## ----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----------------------------------------------------------------------------------------------------------------
+## ----fig.height=3----------------------------------------------------------------------------------------------------
 # Histogram
 ggplot2::ggplot(data = mpg, aes(x = hwy)) +
   ggplot2::geom_histogram(bins = 30) 
 
 
-## ----fig.height=3----------------------------------------------------------------------------------------------------------------
+## ----fig.height=3----------------------------------------------------------------------------------------------------
 # Density plot
 ggplot2::ggplot(data = mpg, aes(x = hwy)) +
   ggplot2::geom_density() 
 
 
-## ----fig.height=3----------------------------------------------------------------------------------------------------------------
+## ----fig.height=3----------------------------------------------------------------------------------------------------
 # Overlapping density plots
 ggplot2::ggplot(data = mpg, aes(x = hwy, fill = drv)) +
   ggplot2::geom_density(alpha = 0.5) 
 
 
-## ----fig.height=3----------------------------------------------------------------------------------------------------------------
+## ----fig.height=3----------------------------------------------------------------------------------------------------
 # Box plots
 ggplot2::ggplot(data = mpg, aes(x = drv, y = hwy)) +
   ggplot2::geom_boxplot(fill = "red")
 
 
-## ----fig.height=3----------------------------------------------------------------------------------------------------------------
+## ----fig.height=3----------------------------------------------------------------------------------------------------
 # Violin plots
 ggplot2::ggplot(data = mpg, aes(x = drv, y = hwy)) +
   ggplot2::geom_violin(aes(fill = drv))
 
 
-## ----fig.height=3----------------------------------------------------------------------------------------------------------------
+## ----fig.height=3----------------------------------------------------------------------------------------------------
 # Line charts
 ggplot2::economics |> 
   ggplot2::ggplot(aes(x = date, y = unemploy)) +
   ggplot2::geom_line()
 
 
-## ----fig.height=3----------------------------------------------------------------------------------------------------------------
+## ----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)) +
@@ -218,20 +218,20 @@ plot2 <-
 
 
 
-## --------------------------------------------------------------------------------------------------------------------------------
+## --------------------------------------------------------------------------------------------------------------------
 # gridExtra
 gridExtra::grid.arrange(plot1, plot2, nrow = 1)
 
 
 
-## ----fig.height=5, fig.width=8---------------------------------------------------------------------------------------------------
+## ----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----------------------------------------------------------------------------------------------------------------
+## ----fig.height=3----------------------------------------------------------------------------------------------------
 # You can also make your own custom themes
 ugly_theme <-
   ggplot2::theme(
@@ -243,27 +243,27 @@ ugly_theme <-
 
 
 
-## ----fig.height=3----------------------------------------------------------------------------------------------------------------
+## ----fig.height=3----------------------------------------------------------------------------------------------------
 plot2 + ugly_theme
 
 
-## ----fig.height=3----------------------------------------------------------------------------------------------------------------
+## ----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----------------------------------------------------------------------------------------------------------------
+## ----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---------------------------------------------------------------------------------------------------
+## ----eval=FALSE, results=FALSE---------------------------------------------------------------------------------------
 ## ggplot2::ggplot(data = mpg) +
 ##    ggplot2::geom_point(mapping = aes(x = hwy, y = cty, colour = as.factor(cyl)))
 

index.Rmd

@@ -146,7 +146,7 @@ The other functions are optional, with default values used if they are not speci
 
 ## Exercises: Section 1
 
-1. Run `ggplot2::ggplot(data = mpg)` what do you see?
+1. Run `ggplot2::ggplot(mpg, aes(x = displ, y = cty))`. Why is the data not plotted?
 2. What does the `drv` variable describe? Read the help for mpg data set to find out by running `?mpg`
 3. Make a scatter plot of `hwy` vs. `cty`
 4. Make a scatter plot of urban fuel consumption vs engine size (displacement). 

index.html

@@ -3343,7 +3343,7 @@ <h3>Objectives:</h3>
 </article></slide><slide class=""><hgroup><h2>Exercises: Section 1</h2></hgroup><article  id="exercises-section-1" class="smaller ">
 
 <ol>
-<li>Run <code>ggplot2::ggplot(data = mpg)</code> what do you see?</li>
+<li>Run <code>ggplot2::ggplot(mpg, aes(x = displ, y = cty))</code>. Why is the data not plotted?</li>
 <li>What does the <code>drv</code> variable describe? Read the help for mpg data set to find out by running <code>?mpg</code></li>
 <li>Make a scatter plot of <code>hwy</code> vs. <code>cty</code></li>
 <li>Make a scatter plot of urban fuel consumption vs engine size (displacement).</li>

solutions.Rmd

@@ -23,7 +23,7 @@ import::from("ggplot2", "aes", "mpg")
 ### 1.1
 
 ```{r}
-ggplot2::ggplot(data = mpg)
+ggplot2::ggplot(mpg, aes(x = displ, y = cty))
 ```
 
 ### 1.2