Exercises

Data

Load the gapminder data:

library(gapminder)

Exercises

Exercise 1: Parameterized plots with ggplot2

1. Create a variable to define a year in the gapminder data that you want to plot.

Solution

choose_year <- 1952

2. Edit the code below to use this new year variable.

library(dplyr)
library(ggplot2)
# Median life expectancy per continent
gapminder_1952 <- gapminder |>
  filter(year == 1952) |>
  group_by(continent) |>
  summarise(
    median_lifeExp = median(lifeExp)
  )
# Bar chart
ggplot(data = gapminder_1952) +
  geom_col(
    mapping = aes(
      x = median_lifeExp,
      y = reorder(continent, median_lifeExp)
    )
  ) +
  labs(
    x = "Median Life Expectancy (years)", y = NULL,
    title = "Life Expectancy in 1952"
  )

Solution

library(dplyr)
library(ggplot2)
library(glue)

# Median life expectancy per continent
gapminder_year <- gapminder |>
  filter(year == choose_year) |>
  group_by(continent) |>
  summarise(
    median_lifeExp = median(lifeExp)
  )

# Bar chart
ggplot(data = gapminder_year) +
  geom_col(
    mapping = aes(
      x = median_lifeExp,
      y = reorder(continent, median_lifeExp)
    )
  ) +
  labs(
    x = "Median Life Expectancy (years)", y = NULL,
    title = glue("Life Expectancy in {choose_year}")
  )

3. Turn your code into a function that takes the data and year variable as arguments.

Solution

barchart_year <- function(choose_year, data = gapminder) {
  # Median life expectancy per continent
  gapminder_year <- gapminder |>
    filter(year == choose_year) |>
    group_by(continent) |>
    summarise(
      median_lifeExp = median(lifeExp)
    )
  # Bar chart
  g <- ggplot(data = gapminder_year) +
    geom_col(
      mapping = aes(
        x = median_lifeExp,
        y = reorder(continent, median_lifeExp)
      )
    ) +
    labs(
      x = "Median Life Expectancy (years)", y = NULL,
      title = glue("Life Expectancy in {choose_year}")
    )
  return(g)
}

Check it works:

barchart_year(2002)

4. Bonus: Add another argument to your function that allows a user to define the bar colour.

Solution

barchart_year <- function(
    choose_year, fill = "blue", data = gapminder) {
  # Median life expectancy per continent
  gapminder_year <- gapminder |>
    filter(year == choose_year) |>
    group_by(continent) |>
    summarise(
      median_lifeExp = median(lifeExp)
    )
  # Bar chart
  g <- ggplot(data = gapminder_year) +
    geom_col(
      mapping = aes(
        x = median_lifeExp,
        y = reorder(continent, median_lifeExp)
      ),
      fill = fill
    ) +
    labs(
      x = "Median Life Expectancy (years)", y = NULL,
      title = glue("Life Expectancy in {choose_year}")
    )
  return(g)
}

Check it works:

barchart_year(2002, fill = "purple")

5. Bonus: How could you improve your function?

Solution

• Not all year values are included in the data. Add a check that the value is a number that is included in the gapminder data. if it isn’t, add a more useful message.
• Write some documentation!

Exercise 2: Parameterized reports with Quarto

1. Edit the report.qmd file to add a parameter for year.

Warningreport.qmd

---
title: "Gapminder Report: 1952"
execute: 
  echo: false
---

```{r}
#| label: load-pkgs
#| warning: false
library(gapminder)
library(dplyr)
library(ggplot2)
library(glue)
```

This is a report using the [Gapminder](https://www.gapminder.org/data/) data. @fig-life-exp shows a plot of the median life expectancy in the year 1952 for each continent.

```{r}
#| label: fig-life-exp
#| fig-cap: "Life expectancy in 1952"
# Edit the code below with your plot function!
plot(1:10, 1:10)
```

Solution

---
title: "Gapminder Report: 1952"
execute: 
  echo: false
params:
  choose_year: 1952
---

```{r}
#| label: load-pkgs
#| warning: false
library(gapminder)
library(dplyr)
library(ggplot2)
library(glue)
```

This is a report using the [Gapminder](https://www.gapminder.org/data/) data. @fig-life-exp shows a plot of the median life expectancy in the year 1952 for each continent.

```{r}
#| label: fig-life-exp
#| fig-cap: "Life expectancy in 1952"
# Edit the code below with your plot function!
plot(1:10, 1:10)
```

2. Add your plotting function to the quarto document, and pass the parameter into the plotting function. Check it renders.

Solution

---
title: "Gapminder Report: 1952"
execute: 
  echo: false
params:
  choose_year: 1952
---

```{r}
#| label: load-pkgs
#| warning: false
library(gapminder)
library(dplyr)
library(ggplot2)
library(glue)
```

This is a report using the [Gapminder](https://www.gapminder.org/data/) data. @fig-life-exp shows a plot of the median life expectancy in the year 1952 for each continent.

```{r}
#| label: fig-life-exp
#| fig-cap: "Life expectancy in 1952"
barchart_year <- function(
    choose_year, fill = "blue", data = gapminder) {
  # Median life expectancy per continent
  gapminder_year <- gapminder |>
    filter(year == choose_year) |>
    group_by(continent) |>
    summarise(
      median_lifeExp = median(lifeExp)
    )
  # Bar chart
  g <- ggplot(data = gapminder_year) +
    geom_col(
      mapping = aes(
        x = median_lifeExp,
        y = reorder(continent, median_lifeExp)
      ),
      fill = fill
    ) +
    labs(
      x = "Median Life Expectancy (years)", y = NULL,
      title = glue("Life Expectancy in {choose_year}")
    )
  return(g)
}
barchart_year(params$choose_year)
```

3. Change the value of the parameter, and re-render.

Exercise 3: Parameterized text with Quarto

1. Edit the sentence ...a plot of the median life expectancy in the year 1952 for each continent... to use inline code to add the document parameter for the year.

Solution

---
title: "Gapminder Report: 1952"
execute: 
  echo: false
params:
  choose_year: 1952
---

```{r}
#| label: load-pkgs
#| warning: false
library(gapminder)
library(dplyr)
library(ggplot2)
library(glue)
```

This is a report using the [Gapminder](https://www.gapminder.org/data/) data. @fig-life-exp shows a plot of the median life expectancy in the year `r params$choose_year` for each continent.

```{r}
#| label: fig-life-exp
#| fig-cap: "Life expectancy in 1952"
barchart_year <- function(
    choose_year, fill = "blue", data = gapminder) {
  # Median life expectancy per continent
  gapminder_year <- gapminder |>
    filter(year == choose_year) |>
    group_by(continent) |>
    summarise(
      median_lifeExp = median(lifeExp)
    )
  # Bar chart
  g <- ggplot(data = gapminder_year) +
    geom_col(
      mapping = aes(
        x = median_lifeExp,
        y = reorder(continent, median_lifeExp)
      ),
      fill = fill
    ) +
    labs(
      x = "Median Life Expectancy (years)", y = NULL,
      title = glue("Life Expectancy in {choose_year}")
    )
  return(g)
}
barchart_year(params$choose_year)
```

2. Use inline code for the title as well.

Solution

---
title: "Gapminder Report: `r params$choose_year`"
execute: 
  echo: false
params:
  choose_year: 1952
---

```{r}
#| label: load-pkgs
#| warning: false
library(gapminder)
library(dplyr)
library(ggplot2)
library(glue)
```

This is a report using the [Gapminder](https://www.gapminder.org/data/) data. @fig-life-exp shows a plot of the median life expectancy in the year `r params$choose_year` for each continent.

```{r}
#| label: fig-life-exp
#| fig-cap: "Life expectancy in 1952"
barchart_year <- function(
    choose_year, fill = "blue", data = gapminder) {
  # Median life expectancy per continent
  gapminder_year <- gapminder |>
    filter(year == choose_year) |>
    group_by(continent) |>
    summarise(
      median_lifeExp = median(lifeExp)
    )
  # Bar chart
  g <- ggplot(data = gapminder_year) +
    geom_col(
      mapping = aes(
        x = median_lifeExp,
        y = reorder(continent, median_lifeExp)
      ),
      fill = fill
    ) +
    labs(
      x = "Median Life Expectancy (years)", y = NULL,
      title = glue("Life Expectancy in {choose_year}")
    )
  return(g)
}
barchart_year(params$choose_year)
```

3. Edit the figure caption to use inline code to add the document parameter for the year.

Solution

---
title: "Gapminder Report: `r params$choose_year`"
execute: 
  echo: false
params:
  choose_year: 1952
---

```{r}
#| label: load-pkgs
#| warning: false
library(gapminder)
library(dplyr)
library(ggplot2)
library(glue)
```

This is a report using the [Gapminder](https://www.gapminder.org/data/) data. @fig-life-exp shows a plot of the median life expectancy in the year `r params$choose_year` for each continent.

```{r}
#| label: fig-life-exp
#| fig-cap: !expr 'paste("Life expectancy in ", params$choose_year)'
barchart_year <- function(
    choose_year, fill = "blue", data = gapminder) {
  # Median life expectancy per continent
  gapminder_year <- gapminder |>
    filter(year == choose_year) |>
    group_by(continent) |>
    summarise(
      median_lifeExp = median(lifeExp)
    )
  # Bar chart
  g <- ggplot(data = gapminder_year) +
    geom_col(
      mapping = aes(
        x = median_lifeExp,
        y = reorder(continent, median_lifeExp)
      ),
      fill = fill
    ) +
    labs(
      x = "Median Life Expectancy (years)", y = NULL,
      title = glue("Life Expectancy in {choose_year}")
    )
  return(g)
}
barchart_year(params$choose_year)
```

Exercise 4: Rendering multiple reports

1. Render a version of your report for the year 1972 using the quarto_render() function.

Solution

quarto_render(
  input = "report.qmd",
  execute_params = list(choose_year = 1972)
)

2. Render a version of your report for all years in the data.

Solution

walk(
  .x = unique(gapminder$year),
  .f = ~quarto_render(
    input = "report.qmd",
    output_file = glue("report_{.x}.html"),
    execute_params = list(
      choose_year = .x
    )
  )
)

Exercise 5: Conditional content

1. Edit the .qmd file from Exercise 3. When the format is HTML show an interactive chart using plotly, otherwise show a static chart.

Solution

---
title: "Gapminder Report: `r params$choose_year`"
execute: 
  echo: false
params:
  choose_year: 1952
---

```{r}
#| label: load-pkgs
#| warning: false
library(gapminder)
library(dplyr)
library(ggplot2)
library(glue)
library(plotly)
```

This is a report using the [Gapminder](https://www.gapminder.org/data/) data. @fig-life-exp shows a plot of the median life expectancy in the year `r params$choose_year` for each continent.

```{r}
barchart_year <- function(
    choose_year, fill = "blue", data = gapminder) {
  # Median life expectancy per continent
  gapminder_year <- gapminder |>
    filter(year == choose_year) |>
    group_by(continent) |>
    summarise(
      median_lifeExp = median(lifeExp)
    )
  # Bar chart
  g <- ggplot(data = gapminder_year) +
    geom_col(
      mapping = aes(
        x = median_lifeExp,
        y = reorder(continent, median_lifeExp)
      ),
      fill = fill
    ) +
    labs(
      x = "Median Life Expectancy (years)", y = NULL,
      title = glue("Life Expectancy in {choose_year}")
    )
  return(g)
}
plot_output <- barchart_year(params$choose_year)
```

::: {#fig-life-exp fig-cap="Life expectancy in `r params$choose_year`"}

::: {.content-visible when-format="html"}

```{r}
ggplotly(plot_output)
```

:::

::: {.content-visible unless-format="html"}

```{r}
plot_output
```

:::

:::

2. When the year parameter is 2007, add a sentence to state that it is the most recent data available.

Solution

---
title: "Gapminder Report: `r params$choose_year`"
execute: 
  echo: false
params:
  choose_year: 1952
---

```{r}
#| label: load-pkgs
#| warning: false
library(gapminder)
library(dplyr)
library(ggplot2)
library(glue)
library(plotly)
```

This is a report using the [Gapminder](https://www.gapminder.org/data/) data. @fig-life-exp shows a plot of the median life expectancy in the year `r params$choose_year` for each continent.

```{r}
barchart_year <- function(
    choose_year, fill = "blue", data = gapminder) {
  # Median life expectancy per continent
  gapminder_year <- gapminder |>
    filter(year == choose_year) |>
    group_by(continent) |>
    summarise(
      median_lifeExp = median(lifeExp)
    )
  # Bar chart
  g <- ggplot(data = gapminder_year) +
    geom_col(
      mapping = aes(
        x = median_lifeExp,
        y = reorder(continent, median_lifeExp)
      ),
      fill = fill
    ) +
    labs(
      x = "Median Life Expectancy (years)", y = NULL,
      title = glue("Life Expectancy in {choose_year}")
    )
  return(g)
}
plot_output <- barchart_year(params$choose_year)
```

::: {#fig-life-exp fig-cap="Life expectancy in `r params$choose_year`"}

::: {.content-visible when-format="html"}

```{r}
ggplotly(plot_output)
```

:::

::: {.content-visible unless-format="html"}

```{r}
plot_output
```

:::

:::

```{r}
latest_begin <- if (params$choose_year != 2007) "::: {.content-hidden}"
latest_end <- if (params$choose_year != 2007) ":::"
```

`r latest_begin`

This is the most recent data available.

`r latest_end`

3. Bonus: Can you edit the logic you applied in question 2, to check programmatically if it’s the last year in the data?

Solution

last_year <- max(gapminder$year)
latest_begin <- if (params$choose_year != last_year) "::: {.content-hidden}"
latest_end <- if (params$choose_year != last_year) ":::"

Exercise 6: Parameterized report sections

1. Separate out the barchart_year() function into a separate R script.

2. Load it in using file: instead.

Solution

Create a .R file and put the function in it. You don’t need to make any changes.

setup.R

barchart_year <- function(
    choose_year, fill = "blue", data = gapminder) {
  # Median life expectancy per continent
  gapminder_year <- gapminder |>
    filter(year == choose_year) |>
    group_by(continent) |>
    summarise(
      median_lifeExp = median(lifeExp)
    )
  # Bar chart
  g <- ggplot(data = gapminder_year) +
    geom_col(
      mapping = aes(
        x = median_lifeExp,
        y = reorder(continent, median_lifeExp)
      ),
      fill = fill
    ) +
    labs(
      x = "Median Life Expectancy (years)", y = NULL,
      title = glue("Life Expectancy in {choose_year}")
    )
  return(g)
}

The use file: to load it in.

---
title: "Gapminder Report: `r params$choose_year`"
execute: 
  echo: false
params:
  choose_year: 1952
---

```{r}
#| label: load-pkgs
#| warning: false
library(gapminder)
library(dplyr)
library(ggplot2)
library(glue)
```

```{r}
#| file: setup.R
```

This is a report using the [Gapminder](https://www.gapminder.org/data/) data. @fig-life-exp shows a plot of the median life expectancy in the year `r params$choose_year` for each continent.


::: {.cell}

```{.r .cell-code}
barchart_year(params$choose_year)
```

::: {.cell-output-display}
![Life expectancy in  ](exercises_files/figure-html/fig-life-exp-1.png){#fig-life-exp width=672}
:::
:::

3. Create a child file containing the year as a section heading, followed by the chart.

Solution

Note_child.qmd

## `r params$choose_year`

```{r}
barchart_year(params$choose_year)
```

4. Render document with a section for each year in the data.

Solution

---
title: "Gapminder Report
execute: 
  echo: false
---

```{r}
#| label: load-pkgs
#| warning: false
library(gapminder)
library(dplyr)
library(ggplot2)
library(glue)
```

```{r}
#| file: setup.R
```

```{r}
#| output: asis
all_years <- as.character(unique(gapminder$year))
for (i in seq_len(length(all_years))) {
  params <- list(choose_year = all_years[i])
  a <- knitr::knit_child('_child.qmd', quiet = TRUE)
  cat(a, sep='\n')
}
```