Bring it All Together (Advanced Data Visualization)

---
title: R Community Survey
format: html
execute: 
  echo: false
  warning: false
  message: false
---


```{r}
library(tidyverse)
library(scales)
```


```{r}
coding_languages <-
  read_rds("data/coding_languages.rds")

demographics <-
  read_rds("data/demographics.rds")
```

Here is a chart showing the most common languages other than R in the survey data.

```{r}
#| fig-height: 3
coding_languages |>
  count(qcoding_languages) |>
  slice_max(
    order_by = n,
    n = 10
  ) |>
  mutate(
    top_language = case_when(
      n == max(n) ~ "Y",
      .default = "N"
    )
  ) |>
  mutate(qcoding_languages = fct_reorder(qcoding_languages, n)) |>
  mutate(n_formatted = comma(n)) |>
  ggplot(
    aes(
      x = n,
      y = qcoding_languages,
      fill = top_language,
      color = top_language
    )
  ) +
  geom_col(
    width = 0.25
  ) +
  geom_text(
    aes(
      label = n_formatted
    ),
    hjust = -0.1
  ) +
  geom_text(
    aes(
      x = 0,
      label = qcoding_languages
    ),
    hjust = 0,
    vjust = -0.5
  ) +
  scale_fill_manual(
    values = c(
      "Y" = "#6cabdd",
      "N" = "gray80"
    )
  ) +
  scale_color_manual(
    values = c(
      "Y" = "#6cabdd",
      "N" = "gray80"
    )
  ) +
  scale_x_continuous(
    expand = expansion(mult = c(0, 0.2))
  ) +
  theme_void(
    base_family = "Geist",
    base_size = 12
  ) +
  theme(
    legend.position = "none"
  )
```

Here is a chart showing the most common languages other than R in the survey data.

```{r}
coding_languages |>
  left_join(demographics, join_by(id)) |>
  group_by(qdegree) |>
  count(qcoding_languages) |>
  slice_max(
    order_by = n,
    n = 3
  ) |>
  ungroup() |>
  filter(
    qdegree %in%
      c(
        "Bachelor’s degree (e.g. BA, BS)",
        "Master’s degree (e.g. MA, MS, MEd)",
        "Doctorate (e.g. PhD, EdD)"
      )
  ) |>
  ggplot(
    aes(
      x = n,
      y = qcoding_languages
    )
  ) +
  geom_col() +
  facet_wrap(vars(qdegree), ncol = 1)
```