gap_table {LightLogR} | R Documentation |
Tabular summary of data and gaps in all groups
Description
gap_table()
creates a gt::gt()
with one row per group, summarizing key
gap and gap-related information about the dataset. These include the
available data, total duration, number of gaps, missing implicit and explicit
data, and, optionally, irregular data.
Usage
gap_table(
dataset,
Variable.colname = MEDI,
Variable.label = "melanopic EDI",
title = "Summary of available and missing data",
Datetime.colname = Datetime,
epoch = "dominant.epoch",
full.days = TRUE,
include.implicit.gaps = TRUE,
check.irregular = TRUE,
get.df = FALSE
)
Arguments
dataset |
A light logger dataset. Needs to be a dataframe. |
Variable.colname |
Column name of the variable to check for NA values. Expects a symbol. |
Variable.label |
Clear name of the variable. Expects a string |
title |
Title string for the table |
Datetime.colname |
The column that contains the datetime. Needs to be a
|
epoch |
The epoch to use for the gapless sequence. Can be either a
|
full.days |
If |
include.implicit.gaps |
Logical. Whether to expand the datetime sequence
and search for implicit gaps, or not. Default is |
check.irregular |
Logical on whether to include irregular data in the summary, i.e. data points that do not fall on the regular sequence. |
get.df |
Logical whether the dataframe should be returned instead of a
|
Value
A gt table about data and gaps in the dataset
Examples
sample.data.environment |> dplyr::filter(MEDI <= 50000) |> gap_table()