Rank changes, movement status, and legends

ggrank has two primary visual questions:

ggrank() asks How did the ranking evolve?
ggrank_change() asks Who moved the most?

Both use the same ranks. The change chart is not a second ranking algorithm.

How rank change is calculated

For each adjacent comparison:

rank_change = rank_from - rank_to

Rank 7 to rank 3 is +4: the category rose four positions. Rank 2 to rank 5 is -3: it fell three positions. Rank 3 to rank 3 is zero. Competition ties remain statistical ties; display_position only prevents tied categories from overlapping in ggrank().

library(ggrank)

changes <- ggrank_table(
  ggrank_products, product, year, sales,
  top_n = 5,
  show_transitions = "all"
)

changes[c("category", "from", "to", "rank_from", "rank_to",
          "rank_change", "status")]
#>     category from   to rank_from rank_to rank_change  status
#> 1  Product B 2022 2023         2       1           1   riser
#> 2  Product A 2022 2023         1       2          -1  faller
#> 3  Product D 2022 2023         4       3           1   riser
#> 4  Product F 2022 2023         6       4           2 entrant
#> 5  Product C 2022 2023         3       5          -2  faller
#> 6  Product H 2022 2023         8       6           2   riser
#> 7  Product E 2022 2023         5       7          -2    exit
#> 8  Product G 2022 2023         7       8          -1  faller
#> 9  Product B 2023 2024         1       1           0  stable
#> 10 Product D 2023 2024         3       2           1   riser
#> 11 Product E 2023 2024         7       3           4 entrant
#> 12 Product A 2023 2024         2       4          -2  faller
#> 13 Product H 2023 2024         6       5           1 entrant
#> 14 Product C 2023 2024         5       6          -1    exit
#> 15 Product F 2023 2024         4       7          -3    exit
#> 16 Product G 2023 2024         8       8           0  stable

What each status means

ggrank_table() preserves boundary and data-availability information:

Status	Meaning
`riser`	Rank improved and the category did not cross into the selected top N.
`faller`	Rank worsened and the category did not cross out of the selected top N.
`stable`	Statistical rank did not change.
`entrant`	Moved from outside the top-N boundary to inside it.
`exit`	Moved from inside the top-N boundary to outside it.
`new`	No earlier-period rank is available.
`absent`	No later-period rank is available.
`missing`	A non-finite value was supplied for either side.

The ggrank_change() colour is intentionally simpler. It uses the sign of rank_change: an entrant moving 6 to 4 is shown as a riser; an exit moving 3 to 7 is shown as a faller. The original status remains in the plot data.

Latest, all, and explicit comparisons

The default focuses on the latest consecutive comparison and removes stable categories:

ggrank_change(changes, top = 5)

top = 5 means the five largest absolute rank changes in the selected comparison—not five risers plus five fallers.

ggrank_change(changes, top = 5, comparison = "all")

Select a comparison already represented in the table with from and to:

ggrank_change(changes, from = 2022, to = 2023, top = 5)

Stable categories are optional:

ggrank_change(changes, top = 8, show_stable = TRUE)
#> Warning: Removed 2 rows containing missing values or values outside the scale range
#> (`geom_point()`).

Detailed labels and long names

ggrank_change(
  changes,
  top = 5,
  change_label = "ranks",
  label_wrap = 24
)

Use change_label = "change" for +4 and -3, "ranks" for 7 → 3 (+4), or "none" for no bar-end annotation.

Customise movement colours and legend text

movement_colours <- c(
  riser = "#0072B2",
  faller = "#D55E00",
  stable = "#667085"
)

movement_labels <- c(
  riser = "Moved towards rank 1",
  faller = "Moved away from rank 1",
  stable = "No rank change"
)

ggrank_change(
  changes,
  top = 5,
  palette = movement_colours,
  legend_title = "Movement",
  legend_labels = movement_labels
)

Set show_legend = FALSE when direction, labels, and explanatory text make the legend unnecessary. Because the result is a ggplot, standard scale and theme functions remain available for further refinement.

Customise group legends in `ggrank()`

When group is supplied, colour_by = "auto" uses its values. Palette and legend-label names must match those values exactly.

cause_colours <- c(
  "Communicable" = "#009E73",
  "Injuries" = "#0072B2",
  "Non-communicable" = "#D55E00"
)

cause_labels <- c(
  "Communicable" = "Communicable diseases",
  "Injuries" = "Injuries",
  "Non-communicable" = "Non-communicable diseases"
)

ggrank(
  ggrank_causes, cause, year, rate,
  rank = rank, label = display_value, group = cause_group,
  periods = c(1990, 2021), top_n = 10,
  palette = cause_colours,
  legend_title = "Cause group",
  legend_labels = cause_labels
)

To use movement rather than group colours, choose colour_by = "movement". To hide the legend, use show_legend = FALSE.