Add crossings to a dataframe for area charts

Augments a dataframe with x-values where y = f(x) = 0. This is useful for creating area charts with different fills for values less than versus greater than 0.

Usage

add_crossings(data, x, y, .by = NULL)

Arguments

data

A data frame containing the original x and y values.

x

x-axis values.

y

y-axis values.

.by

Grouping variable(s). Useful for computing crossings for faceted plots.

Value

The input data frame with additional rows representing the crossings (where y = 0), and two new columns:

• pos_neg: Indicates whether the y-value is positive ("pos") or negative ("neg").

• cross_grp: A grouping variable for the segments between crossings.

Details

The returned dataframe will include columns pos_neg and cross_group. Within geom_area(), cross_group should be mapped to group, while pos_neg should be mapped to aesthetics such as fill or color.

Examples

nile_flow <- tibble::tibble(
  Year = time(Nile),
  Flow = as.numeric(Nile),
  FlowDelta = (Flow - Flow[[1]]) / Flow[[1]]
)
nile_flow_x0 <- add_crossings(nile_flow, Year, FlowDelta)
ggplot2::ggplot(nile_flow_x0, ggplot2::aes(Year, FlowDelta)) +
  ggplot2::geom_area(
    ggplot2::aes(group = cross_grp, color = pos_neg, fill = pos_neg),
    alpha = 0.25,
    show.legend = FALSE
  ) +
  ggplot2::geom_hline(yintercept = 0, linewidth = 0.25) +
  ggplot2::scale_color_manual(
    values = c("darkred", "blue"),
    aesthetics = c("color", "fill")
  ) +
  ggplot2::scale_y_continuous(
    "Nile River Annual Flow:\n% Change from 1871",
    labels = scales::percent
  ) +
  ggplot2::theme_minimal()