AirVizR: Visualization Tools for Air Quality Data

Description Usage Arguments Value See Also Examples

A series of arguments to detect the minimum time stamp value within a data set, and provide an output of visualization settings to apply to allow for appropriate labeling and scaling.

settings_dt_scale(
  dataset,
  start_date = input_startdate,
  end_date = input_enddate
)

`dataset`	The data set which to evaluate
`start_date`	The start date (to be pasted into captions); will be automatically adjusted based on actual start date of the data set, if possible
`end_date`	The end date (to be pasted into captions); will be automatically adjusted based on actual end date of the data set, if possible

List of values to be applied to various visualization methods:

dataset: Dataset with the minimum time stamp column header renamed 'timestamp'.
lab_title_sub: Character; Working in conjunction with lab_title from settings_units, the unit of temporal measurement of the dataset
x_angle: Numeric; the angle to place x-axis (temporal) text.
x_scale: x-axis scale (from scale_x_datetime) formatting and scale breaks.
date_in_set: Logical; if date value(s) present in data set.
start_date: Date; actual minimum date of data set, regardless of function input.
end_date: Date; actual maximum date of data set, regardless of function input.
lab_caption: Character; label information for details containing date range in the set.

Other visualization settings: add_cap(), drop_incomplete(), settings_shapes(), settings_units()

settings_results_example <- settings_dt_scale(july_api_diurnal, start_date = "2020-07-01", end_date = "2020-07-07")
ggplot(settings_results_example$dataset, aes(timestamp, temperature)) +
  settings_results_example$x_scale +
  labs(subtitle = settings_results_example$lab_caption)
remove(settings_results_example)