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Plot the Distribution of Missing Values Over Time

Source: R/plot.check_na_timing.R
plot.anivis_check_na_timing.Rd

Renders a check_na_timing() result (from the anicheck package) as a stacked bar chart of missing (NA) versus present values across successive time intervals — an adaptation of ggplot_na_distribution2() from the imputeTS package (Moritz & Gatscha, GPL-3). Each bar is one interval of the recording; its split shows how much of that stretch was missing, so a run of tall “NA” bars marks a blackout while an even sprinkle marks scattered dropouts. With more than one group, each gets its own stacked panel.

Usage

# S3 method for class 'anivis_check_na_timing'
plot(
  x,
  ...,
  measure = c("percent", "count"),
  n_intervals = NULL,
  mode = c("light", "dark")
)

Arguments

x

A check_na_timing object (from the anicheck package).

...

Additional arguments (currently unused).

measure

Either "percent" (default, share of each interval) or "count" (number of frames).

n_intervals

Number of intervals to bin into. Default (NULL) uses Sturges' rule on the largest group's frame count.

mode

Either "light" (default) or "dark"; passed to theme_imputets().

Value

A ggplot object.

Details

The interval counts are reconstructed from the compact gap table in the check object (no per-frame data needed). Missing uses the imputeTS indianred, present the imputeTS steelblue, with the two named in the coloured subtitle (so no legend is needed). Styling is theme_imputets(). The plot is built from an intermediate frame of class anivis_check_na_timing_data produced by as_plot_data() — the staging step that mirrors data_plot() in see.

See also

as_plot_data()