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time series figure

Source: R/fct_figures.R
fig_timeseries.Rd

Creates a ggplot2 faceted time series line plot. Can be called within plotly_figure() to create an interactive figure.

Usage

fig_timeseries(
  data,
  xval = "day",
  id = "subject_id",
  id_to_highlight,
  color_fill = "significance",
  point_size = "reviewed",
  label = "text_label",
  scale = FALSE,
  use_unscaled_limits = FALSE
)

Arguments

data

A data frame containing the data of interest.

xval

x-value to be used.

id

Character string. Column containing the unique Patient IDs.

id_to_highlight

Character vector. Unique Patient ID. Connects the lines in the time series.

color_fill

Character vector. Column name of the variable to be used for filling color in the figure.

point_size

character vector. Column in the data frame that controls the point size in the figure.

label

Character vector. Label to be used for each data point. Will only be visible if the ggplot object is converted to an interactive plot using plotly::ggplotly(). See plotly_figure()

scale

A logical. Whether to us a scaled value (value_scaled) or the raw variable (item_value).

use_unscaled_limits

If TRUE, limits provided in the data frame will be used. This parameter will be ignored if scaled is set to TRUE.

Value

A faceted ggplot2 time series figure.

See also

plotly_figure()

Examples

set.seed(2023)
mock_data <- lapply(paste0("Subject", 1:10) , \(x){
  data.frame(
   subject_id = x,
    day = sample(1:25, 10),
    item_name = sample(c("item1", "item2"), 10, replace = TRUE),
    item_value = runif(10, 0 , 50),
    significance = sample(names(col_palette), 10, replace = TRUE),
    text_label = "test text",
    reviewed = sample(c("Yes", "No"), replace = TRUE)
  )
}) |>
  dplyr::bind_rows()
fig_timeseries(mock_data, id_to_highlight = "Subject10")