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Plot data as a scatterplot

Source: R/plot_point.R
plot_point.Rd

Create a scatterplot for two variables.

Usage

plot_point(
  data,
  x,
  y,
  facet_var = NULL,
  facet_scale = "free",
  facet_nrow = NULL,
  facet_ncol = NULL,
  color = NULL,
  title = NULL,
  subtitle = NULL,
  xlab = NULL,
  ylab = NULL,
  caption = NULL,
  point_size = 1.5,
  point_type = 16,
  point_color = "grey35",
  point_alpha = 1,
  theme_set = theme_tscv(),
  theme_config = list(),
  ...
)

Arguments

data

A data.frame, tibble, or tsibble in long format.

x

Unquoted column in data used on the x-axis.

y

Unquoted column in data containing numeric values shown on the y-axis.

facet_var

Optional unquoted column in data used for faceting.

facet_scale

Character value defining facet axis scaling. Common values are "free", "fixed", "free_x", and "free_y".

facet_nrow

Optional integer. Number of rows in the facet layout.

facet_ncol

Optional integer. Number of columns in the facet layout.

color

Optional unquoted column in data used to map point color.

title

Character value. Plot title.

subtitle

Character value. Plot subtitle.

xlab

Character value. Label for the x-axis.

ylab

Character value. Label for the y-axis.

caption

Character value. Plot caption.

point_size

Numeric value defining the point size.

point_type

Numeric or character value defining the point shape.

point_color

Character value defining the point color. Ignored when color is supplied.

point_alpha

Numeric value between 0 and 1 defining point transparency.

theme_set

A complete ggplot2 theme.

theme_config

A named list with additional arguments passed to ggplot2::theme().

...

Currently not used.

Value

An object of class ggplot.

Details

plot_point() is a convenience wrapper around ggplot2::geom_point(). It is useful for plotting relationships between two variables, for example observed values over time, forecast errors by horizon, or one numeric diagnostic against another.

The arguments x, y, facet_var, and color are passed as unquoted column names.

If color is supplied, point colors are mapped to that variable and point_color is ignored. If color is not supplied, all points are drawn using point_color.

Additional theme settings can be supplied through theme_config. This should be a named list of arguments passed to ggplot2::theme().

See also

Other data visualization: plot_bar(), plot_density(), plot_histogram(), plot_line(), plot_qq(), scale_color_tscv(), scale_fill_tscv(), theme_tscv(), tscv_cols(), tscv_pal()

Examples

library(dplyr)

data <- M4_monthly_data |>
  filter(series == "M23100")

plot_point(
  data = data,
  x = index,
  y = value,
  title = "M4 Monthly Time Series",
  subtitle = "Series M23100",
  xlab = "Time",
  ylab = "Value"
)


acf_data <- estimate_acf(
  .data = M4_monthly_data |>
    filter(series %in% c("M23100", "M14395")),
  context = list(
    series_id = "series",
    value_id = "value",
    index_id = "index"
  ),
  lag_max = 12
)

plot_point(
  data = acf_data,
  x = lag,
  y = value,
  color = series,
  title = "Autocorrelation by Series",
  subtitle = "Sample autocorrelation up to lag 12",
  xlab = "Lag",
  ylab = "ACF",
  point_size = 4
)