new worksheet

docs/materials/positconf2024-legends.qmd

@@ -0,0 +1,179 @@
+---
+title: "Effective Data Visualization with ggplot2"
+subtitle: "Sprucing up your legends"
+format: html
+editor: visual
+---
+
+## Required packages
+
+Install the required packages:
+
+```{r}
+#| eval = FALSE
+
+# Run this command to install the required packages.
+# You need to do this only once.
+install.packages(
+  c(
+    "tidyverse", "colorspace", "cowplot"
+  )
+)
+```
+
+## 1. Legend order
+
+By default, ggplot places legend entries in alphabetical order, and that is rarely what we want. See this example:
+
+```{r}
+#| message = FALSE,
+#| warning = FALSE
+
+library(tidyverse)
+library(colorspace)
+library(cowplot)     # for theme functions
+
+tech_stocks <- read_csv("https://wilkelab.org/dataviz_shortcourse/datasets/tech_stocks.csv") |>
+  mutate(date = ymd(date)) |>
+  select(company, date, price_indexed)
+
+ggplot(tech_stocks) +
+  aes(x = date, y = price_indexed) +
+  geom_line(aes(color = company), na.rm = TRUE) +
+  scale_x_date(
+    limits = c(
+      ymd("2012-06-01"),
+      ymd("2017-05-31")
+    ),
+    expand = c(0, 0)
+  ) + 
+  scale_y_continuous(
+    limits = c(0, 560),
+    expand = c(0, 0)
+  )
+```
+
+The visual order of the lines is Facebook, Alphabet, Microsoft, Apple, and we should match it by reodering the categorical variable.
+
+```{r}
+tech_stocks |>
+  mutate(
+    company = fct_relevel(
+      company,
+      "Facebook",  "Alphabet", "Microsoft", "Apple"
+    )
+  ) |>
+  ggplot() +
+  aes(x = date, y = price_indexed) +
+  geom_line(aes(color = company), na.rm = TRUE) +
+  scale_x_date(
+    limits = c(
+      ymd("2012-06-01"),
+      ymd("2017-05-31")
+    ),
+    expand = c(0, 0)
+  ) + 
+  scale_y_continuous(
+    limits = c(0, 560),
+    expand = c(0, 0)
+  )
+```
+
+This is improved, but we can do better. We can get rid of the legend entirely, by adding a secondary axis.
+
+```{r}
+tech_stocks_last <- tech_stocks |>
+  filter(date == max(date))
+
+ggplot(tech_stocks) +
+  aes(x = date, y = price_indexed) +
+  geom_line(aes(color = company), na.rm = TRUE) +
+  scale_x_date(
+    limits = c(
+      ymd("2012-06-01"),
+      ymd("2017-05-31")
+    ),
+    expand = c(0, 0)
+  ) + 
+  scale_y_continuous(
+    limits = c(0, 560),
+    expand = c(0, 0),
+    sec.axis = dup_axis(
+      breaks = tech_stocks_last$price_indexed,
+      labels = tech_stocks_last$company,
+      name = NULL
+    )
+  ) +
+  guides(color = "none")
+```
+
+## Exercises
+
+```{r}
+#| message = FALSE
+
+preprints <- read_csv("https://wilkelab.org/dataviz_shortcourse/datasets/preprints.csv") |>
+  filter(archive %in% c("bioRxiv", "arXiv q-bio")) %>%
+  filter(count > 0)
+```
+
+```{r}
+preprints_final <- filter(preprints, date == max(date))
+
+ggplot(preprints) +
+  aes(date, count, color = archive) + 
+  geom_line(linewidth = 0.75) +
+  scale_y_log10(
+    limits = c(29, 1600),
+    breaks = c(30, 100, 300, 1000),
+    expand = c(0, 0),
+    name = "preprints / month",
+    sec.axis = dup_axis(
+      breaks = preprints_final$count,
+      labels = preprints_final$archive,
+      name = NULL
+    )
+  ) + 
+  scale_x_date(name = "year", expand = c(0, 0)) +
+  scale_color_manual(values = c("#D55E00", "#0072B2"), guide = "none") +
+  theme_minimal_grid() +
+  theme(
+    axis.ticks.y.right = element_blank(),
+    axis.text.y.right = element_text(
+      size = 14,
+      margin = margin(0, 0, 0, 0)
+    )
+  )
+```
+
+## 2. Legend placement
+
+```{r}
+ggplot(mtcars) +
+  aes(disp, mpg, fill = hp, shape = factor(cyl), size = wt) + 
+  geom_point(color = "white") +
+  scale_shape_manual(values = c(23, 24, 21), name = "cylinders") +
+  scale_fill_continuous_sequential(
+    palette = "Emrld", name = "power (hp)",
+    breaks = c(100, 200, 300),
+    rev = FALSE
+  ) +
+  xlab("displacement (cu. in.)") +
+  ylab("fuel efficiency (mpg)") +
+  guides(
+    shape = guide_legend(override.aes = list(size = 4, fill = "#329D84")),
+    size = guide_legend(override.aes = list(shape = 21, fill = "#329D84"),
+    title = "weight (1000 lbs)")
+  ) +
+  theme_half_open() + 
+  background_grid() +
+  theme(
+    #legend.title = element_text(size = 12),
+    legend.box.background = element_rect(fill = "white", color = "white"),
+    legend.position = "inside",
+    legend.direction = "vertical",
+    legend.box = "horizontal",
+    legend.justification = "center",
+    legend.box.margin = margin(7, 7, 7, 7)
+  )
+```

docs/materials/positconf2024-pattern-fill.qmd

@@ -458,10 +458,11 @@ pet_ownership |>
   theme_minimal_vgrid(rel_small = 1)
 ```
 
-Unfortunately this is not quite what we wanted. The images are centered within the bar rather than aligned to one side. There doesn't currently seem to be a way to fix this, so we may have to go back to ggpattern.
+Unfortunately this is not quite what we wanted. The images are centered within the bar rather than aligned to one side. There doesn't currently seem to be a way to fix this, so we may have to go back to ggpattern (see exercises).
 
 ## Exercises
 
 1.  Create a version of the pet ownership isotype plot where bars run vertical instead of horizontal.
+2.  Recreate the pet ownership isotype plot with ggpattern.
 
 ##