ggmemo: Add Arrows, Labels, and Change Annotations to 'ggplot2' Charts

Add arrows, labels, and change annotations to ggplot2 charts in one line of code. Two functions:

annotate_callout(): Point at a data row with an arrow and label.
annotate_change(): Show the delta between two rows as percent change, absolute change, or percentage points.

Both return standard ggplot2 layers — add them with +.

Install from GitHub (not on CRAN):

pak::pak("lindsay-lintelman/ggmemo")

Why ggmemo instead of manual ggplot2 annotation?

Manual annotation requires hardcoding coordinates, computing deltas, formatting labels, and picking colors (~10 lines). ggmemo replaces that with a single function call:


# Without ggmemo:
annotate("segment", x = "Q1", xend = "Q4", y = 120, yend = 158,
         arrow = arrow(length = unit(0.15, "inches")),
         colour = "#2E7D32", linewidth = 0.6) +
annotate("label", x = 2.5, y = 139, label = "+31.7
         colour = "#2E7D32", fill = "white", fontface = "bold")

# With ggmemo:
annotate_change(data, from = quarter == "Q1",
                to = quarter == "Q4", value = revenue)

Quick reference


# Label a data point
annotate_callout(data, where, label, position, nudge, ...)

# Show change between two points
annotate_change(data, from, to, value, format, colors, ...)

format options: "percent" (default), "absolute", "points", "both"

Common tasks

Label a peak or milestone	`annotate_callout(df, where = date == "2024-06-01", label = "Peak")`
Show percent change	`annotate_change(df, from = ..., to = ..., value = sales)`
Show absolute difference	`annotate_change(..., format = "absolute")`
Show percentage point change	`annotate_change(..., format = "points")`
Use custom colors	`annotate_change(..., colors = c(up = "#1B9E77", down = "#D95F02", flat = "#999"))`
Override label styling	`annotate_callout(..., size = 4, fill = "lightyellow")`

When to use ggmemo

Use ggmemo when you want to annotate a ggplot2 chart with arrows, callout labels, or change annotations without manually computing coordinates, formatting deltas, or positioning text. Common scenarios: quarterly reports, executive dashboards, time-series narration, before/after comparisons.

When NOT to use ggmemo

Repelling overlapping labels: use the ggrepel package.
NPC (normalized parent coordinates) positioning: use the ggpp package.
Interactive annotations: use plotly or ggiraph.
Theming or styling: use ggthemes, hrbrthemes, or bbplot.

Author

Maintainer: Lindsay Lintelman lindsay.lintelman@posit.co

Authors:

Lindsay Lintelman lindsay.lintelman@posit.co

Examples

library(ggplot2)
library(ggmemo)

# -- Complete template: narrated business chart --
# Data
revenue <- data.frame(
  quarter = factor(c("Q1", "Q2", "Q3", "Q4"),
                   levels = c("Q1", "Q2", "Q3", "Q4")),
  revenue = c(120, 145, 132, 158)
)

# Annotated chart
ggplot(revenue, aes(x = quarter, y = revenue)) +
  geom_col(fill = "steelblue", width = 0.6) +
  annotate_callout(
    revenue,
    where = quarter == "Q4",
    label = "Record quarter",
    position = "top-left"
  ) +
  annotate_change(
    revenue,
    from = quarter == "Q1",
    to = quarter == "Q4",
    value = revenue
  ) +
  labs(title = "2024 Quarterly Revenue ($K)", x = NULL, y = NULL) +
  theme_minimal()