gg_overview: Plot an overview of dataset intervals with implicit missing...

In LightLogR: Process Data from Wearable Light Loggers and Optical Radiation Dosimeters

Plot an overview of dataset intervals with implicit missing data

Description

Plot an overview of dataset intervals with implicit missing data

Usage

gg_overview(
  dataset,
  Datetime.colname = Datetime,
  Id.colname = Id,
  gap.data = NULL,
  ...,
  interactive = FALSE
)

Arguments

dataset	A light logger dataset. Expects a dataframe. If not imported by LightLogR, take care to choose a sensible variable for the x.axis..
Datetime.colname	column name that contains the datetime. Defaults to "Datetime" which is automatically correct for data imported with LightLogR. Expects a symbol. Needs to be part of the dataset.
Id.colname	The column name of the Id column (default is Id), needs to be in the dataset. This is also used as the y-axis variable and is the minimum grouping variable.
gap.data	Optionally provide a tibble with start and end Datetimes of gaps per group. If not provided, the function uses gap_finder() to calculate implicit missing data. This might be computationally intensive for large datasets and many missing data. In these cases it can make sense to calculate those gaps beforehand and provide them to the function. If an empty tibble (tibble::tibble()) is provided, the function will just plot the start and end dates of the dataset, which is computationally very fast at the cost of additional info.
...	Additional arguments given to the main ggplot2::aes() used for styling depending on data within the dataset
interactive	Should the plot be interactive? Expects a logical. Defaults to FALSE.

Value

A ggplot object

Examples

sample.data.environment %>% gg_overview()

LightLogR documentation built on April 3, 2025, 10:10 p.m.