nav.hidden, nav ul [x-cloak], nav ul li ul { display: block !important; } This website requires Javascript for some parts to function properly. Your experience may vary.

Making Beautiful Tables with R

15 lessons

Making Beautiful Tables with R

Adding Charts with Flextable

This lesson is locked

Get access to all lessons in this course.

This lesson is called Adding Charts with Flextable, part of the Making Beautiful Tables with R course. This lesson is called Adding Charts with Flextable, part of the Making Beautiful Tables with R course.

If the video is not playing correctly, you can watch it in a new window

Transcript

Click on the transcript to go to that point in the video. Please note that transcripts are auto generated and may contain minor inaccuracies.

Sparklines are small lines that help you to find trends in the data really fast. By now, they’re one of the standard tricks in the table trade. Here's how to add one in a flextable.

counts_over_time <- penguin_counts |> 
  group_by(species, island, sex) |> 
  summarise(collected_data = list(n)) |> 
  ungroup()


counts_over_time |> 
  flextable() |> 
  compose(j = 'collected_data', value = as_paragraph(
    plot_chunk(value = collected_data, type = 'line', col = 'dodgerblue4')
  ))

And here's how to add a boxplot to a table.

penguin_mass <- penguins |> 
  group_by(species) |> 
  summarise(body_masses = list(body_mass_g)) |> 
  ungroup()

penguin_mass |> 
  flextable() |> 
  compose(
    j = 'body_masses',
    value = as_paragraph(
      plot_chunk(
        value = body_masses,
        type = 'dens',
        col = 'dodgerblue4',
        width = 3,
        height = 1
      )
    )
  )

Your Turn

Solution

life_exp_over_time <- gapminder_data |> 
  filter(country %in% selected_countries$country, str_ends(year, '7')) |> 
  group_by(country) |> 
  summarise(life_exps = list(life_exp))

# Code from before is reprinted because colwidths and labels needs to be adjusted due to new column
prev_table <- selected_countries |> 
  bind_rows(average_life_exps, max_life_exps) |> 
  full_join(life_exp_over_time) |> 
  arrange(continent, country %in% c('Average', 'Maximum')) |> 
  as_grouped_data(
    groups = 'continent'
  ) |> 
  as_flextable(hide_grouplabel = TRUE) |> 
  set_header_labels(values = new_names) |> 
  set_header_labels(life_exps = '') |> 
  add_header_row(
    values = c('', '50s-70s', '80s-20s', ''),
    colwidths = c(1, 3, 3, 1)
  ) |> 
  add_header_lines(
    values = c('Life expectancties over time', 'Data is courtesy of the {gapminder} R package')
  ) |> 
  align(i = 3, align = 'center', part = 'header') |> 
  colformat_double(digits = 2) |> 
  hline(
    i = ~ (
      !is.na(continent) | 
        country == 'Maximum' | 
        lead(country == 'Maximum', 2, default = FALSE)
    )
  ) |> 
  bg(i = ~ is.na(country), bg = 'dodgerblue4') |> 
  bg(i = ~ (country %in% c('Average', 'Maximum')), bg = 'grey95') |> 
  style(pr_t = fp_text(font.family = 'Source Sans Pro'), part = 'all') |> 
  bold(part = 'header', i = 3) |> 
  style( ### group rows
    i = ~ (is.na(country)),
    pr_t = fp_text(
      color = 'white',
      bold = TRUE,
      font.size = 12,
    )
  ) |> 
  style( ### title
    part = 'header',
    i = 1,
    pr_t = fp_text(
      color = 'dodgerblue4',
      font.size = 18,
      font.family = 'Source Sans Pro',
      bold = TRUE
    ),
    pr_c = fp_cell(
      border.top = fp_border(width = 1.5, color = 'grey40'),
      border.bottom = fp_border(width = 0, color = 'grey40')
    )
  ) |> 
  style( #### subtitle
    part = 'header',
    i = 2,
    pr_t = fp_text(font.size = 11),
    pr_c = fp_cell(border = fp_border(width = 0, color = 'grey40'))
  ) |> 
  line_spacing(part= 'all', space = 0.75) |> 
  hline(part = 'header', i = 2, border = fp_border(width = 0)) |> 
  hline(part = 'header', i = 3, border = fp_border(width = 0)) |> 
  border(i = 3, j = 2:7, border.bottom = fp_border(width = 1, color = 'grey40'), part = 'header')


prev_table |> 
  compose(
    i = ~ !(country %in% c('Average', 'Maximum') | is.na(country)), 
    j = 'life_exps', 
    value = as_paragraph(
      plot_chunk(value = life_exps, type = 'line', col = 'dodgerblue4')
    )
  ) |> 
  compose(
    i = ~ (country %in% c('Average', 'Maximum') | is.na(country)), 
    j = 'life_exps', 
    value = as_paragraph('')
  ) |> 
  autofit() |> 
  width(j = 'life_exps', width = 0.75)

Instead of turning columns into a heat map, add another column to your table that contains a sparkline depicting the life expectancy over time for each country. If you don’t want to create sparklines for the average and maximum rows, then use value = as_paragraph('') in a second call to the compose() function.

Hint: If you want, you can manually change the width of the sparkline column with width() after autofit() was called.

Your table should look like this:

Have any questions? Put them below and we will help you out!

You need to be signed-in to comment on this post. Login.