ggplot2 geom_line() in R: Line Charts With Examples

The geom_line() function in ggplot2 connects points in order of x to draw a line. Use it for time series, trends, and any continuous relationship where reading x as a sequence makes sense.

ggplot(df, aes(x, y)) + geom_line()                          # basic line
ggplot(df, aes(x, y, color = group)) + geom_line()           # one line per group
ggplot(df, aes(x, y, group = group)) + geom_line()           # multi-line, no color
ggplot(df, aes(x, y, linetype = group)) + geom_line()        # different linetypes
ggplot(df, aes(x, y)) + geom_line(linewidth = 1.2)           # thicker line
ggplot(df, aes(x, y)) + geom_line() + geom_point()           # line + markers
ggplot(df, aes(x, y)) + geom_line() + scale_x_date()         # time series

What geom_line() does in one sentence

geom_line() draws a line connecting points in ascending order of x. Each row contributes one point; ggplot connects them with straight segments. Use the group aesthetic to draw multiple lines, one per group, in the same plot.

Unlike geom_path() (which connects points in row order regardless of x), geom_line() always sorts by x first. This makes it the right choice for time series and any plot where x represents a continuous independent variable.

Syntax

geom_line() is a layer added to a ggplot() call. Minimum is aes(x, y). For multi-line plots, also map group, color, or linetype.

The full signature:

geom_line(mapping = NULL, data = NULL, stat = "identity", position = "identity",
          ..., na.rm = FALSE, orientation = NA, show.legend = NA, inherit.aes = TRUE)

Six common patterns

1. Basic time series line

The simplest case: x is a date, y is a numeric, line connects them in chronological order.

2. Multi-line with color

color = sex automatically groups the data; ggplot draws one line per unique sex value.

3. Different linetypes per group

linetype maps to one of "solid", "dashed", "dotted", "dotdash", etc. Useful when colors are not appropriate (e.g., grayscale printing).

4. Line + points

A common combo: the line shows the trend, points emphasize each measurement. Useful when data is sparse and individual values matter.

5. Group without color

Use group = sex (in aes) when you need separate lines but do NOT want the legend / color to encode it. Useful when one variable is the focus and other groupings are reference.

6. Stepped line for discrete jumps

geom_step() connects with right-angle steps, not slanted lines. Right for state changes (e.g., Markov chains, on/off signals) where interpolation between values does not make sense.

geom_line() vs base R plot(type = "l")

Base R uses plot(type = "l") or lines(). ggplot2 makes line plots composable and grouping explicit.

When to use which:

• Use ggplot2 for multi-group, faceted, or publication line plots.
• Use base plot(type = "l") for one-line interactive exploration.

Common pitfalls

Pitfall 1: missing group aesthetic for multi-line. Without group, color, or linetype mapped to a categorical variable, ggplot tries to connect ALL points in x order, producing a single zigzag line across all groups. Symptom: looks like a sawtooth wave.

Pitfall 2: confusing geom_line() with geom_path(). geom_line sorts by x first; geom_path connects in ROW order. For time series, geom_line; for paths through space (e.g., GPS tracks), geom_path.

Pitfall 3: factor x axis with continuous group. aes(x = factor(year), y = val, group = 1) is needed when x is a factor but you still want a continuous line. Without group = 1, ggplot draws no line.

Try it yourself

Related ggplot2 functions

After mastering geom_line(), look at:

• geom_path(): connect in row order (not x order)
• geom_step(): right-angle steps for discrete state changes
• geom_area(): filled area under a line
• geom_ribbon(): band between two y values (e.g., confidence intervals)
• geom_smooth(): fit a smooth trend line through points
• scale_x_date(), scale_x_datetime(): date and datetime axis formatting

For animated transitions over time, gganimate::transition_reveal() builds an animated geom_line.

FAQ

How do I add multiple lines to a ggplot?

Map a categorical variable to color, linetype, or group: aes(x, y, color = group). ggplot draws one line per unique group value. If you do not want color in the legend, use group = group instead.

What is the difference between geom_line and geom_path in ggplot2?

geom_line() connects points in ASCENDING x ORDER. geom_path() connects in ROW ORDER (no sorting). For time series, use geom_line. For trajectories or paths through space, use geom_path.

How do I change the line color in geom_line?

For ALL lines: geom_line(color = "blue") (outside aes). To map color to a variable: aes(color = group) (inside aes). Don't mix them up; the wrong form is the most common ggplot2 error.

How do I make a thicker line in ggplot2?

Use linewidth: geom_line(linewidth = 1.5). The old size argument is deprecated in ggplot2 3.4+. Default linewidth is 0.5; values 1 to 2 are typical for clearer plots.

How do I plot a time series in ggplot2?

Use geom_line() with x as a Date or POSIXct column: ggplot(df, aes(x = date, y = value)) + geom_line(). Use scale_x_date() for date-formatted axis labels: + scale_x_date(date_breaks = "1 year", date_labels = "%Y").