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Quickly plot observed (measured) and modelled concentrations over time in short-term data

plot_timeseries.Rd

This is a useful function for examining short-term data after it has been filtered or aggregated, but before it statistics are calculated. Unlike other plotting functions in {mqor}, this function does not take the output of summarise_mqo_stats().

Usage

plot_timeseries(
  data,
  pollutant,
  site,
  color_obs = "#6CC5B0",
  color_mod = "black",
  dict = mqor::mqo_dict(),
  interactive = FALSE
)

Arguments

data

An R data.frame containing at least four columns; a numeric column of observed values, a numeric column of modelled values, a character or factor column of identifiers that identify the site associated with the concentrations, and a character or factor column of identifiers that identify the pollutant being measured/modelled. See demo_shortterm for an example format.

pollutant

The pollutant to plot. Should be a value contained within data[[dict$pollutant]].

site

The station to plot.s Should be a value contained within data[[dict$site]].

color_obs, color_mod

The colours to use for the 'observation' and 'modelled' lines. Can be expressed as hex codes, or any colours listed in colors().

dict

See mqo_dict() for more information. Acts as a data dictionary to specify the columns in the data {mqor} should use.

interactive

If FALSE, the default, a static ggplot2 graphic will be returned which can be saved as a PNG, SVG, or other similar format. If TRUE, a dynamic HTML widget will be returned created by plotly.

See also

Other plotting functions: plot_comparison_bars(), plot_mqi_bars(), plot_mqi_report(), plot_mqi_scatter()

Author

Jack Davison