Time series plot with categories shown as a stacked bar chart

This function shows time series plots as stacked bar charts. The different categories in the bar chart are made up from a character or factor variable in a data frame. The function is primarily developed to support the plotting of cluster analysis output from polarCluster() and trajCluster() that consider local and regional (back trajectory) cluster analysis respectively. However, the function has more general use for understanding time series data.

Usage

timeProp(
  mydata,
  pollutant = "nox",
  proportion = "wd",
  avg.time = "day",
  type = "default",
  cols = "Set1",
  theme = "default",
  normalise = FALSE,
  ref.x = NULL,
  ref.y = NULL,
  key.columns = 1,
  key.position = "right",
  key.title = proportion,
  date.breaks = 7,
  date.format = NULL,
  auto.text = TRUE,
  plot = TRUE,
  key = NULL,
  ...
)

Arguments

mydata

A data frame containing the fields date, pollutant and a splitting variable proportion

pollutant

Name of the pollutant to plot contained in mydata.

proportion

The splitting variable that makes up the bars in the bar chart, defaulting to "wd". Could be "cluster" if the output from polarCluster() or trajCluster() is being analysed. If proportion is a numeric variable it is split into 4 quantiles (by default) by cutData(). If proportion is a factor or character variable then the categories are used directly.

avg.time

This defines the time period to average to. Can be "sec", "min", "hour", "day", "DSTday", "week", "month", "quarter" or "year". For much increased flexibility a number can precede these options followed by a space. For example, an average of 2 months would be avg.time = "2 month". In addition, avg.time can equal "season", in which case 3-month seasonal values are calculated with spring defined as March, April, May and so on.

Note that avg.time when used in timeProp() should be greater than the time gap in the original data. For example, avg.time = "day" for hourly data is OK, but avg.time = "hour" for daily data is not.

type

Character string(s) defining how data should be split/conditioned before plotting. "default" produces a single panel using the entire dataset. Any other options will split the plot into different panels - a roughly square grid of panels if one type is given, or a 2D matrix of panels if two types are given. type is always passed to cutData(), and can therefore be any of:

A built-in type defined in cutData() (e.g., "season", "year", "weekday", etc.). For example, type = "season" will split the plot into four panels, one for each season.
The name of a numeric column in mydata, which will be split into n.levels quantiles (defaulting to 4).
The name of a character or factor column in mydata, which will be used as-is. Commonly this could be a variable like "site" to ensure data from different monitoring sites are handled and presented separately. It could equally be any arbitrary column created by the user (e.g., whether a nearby possible pollutant source is active or not).

Most openair plotting functions can take two type arguments. If two are given, the first is used for the columns and the second for the rows.

cols

Colours to use for plotting. Can be a pre-set palette (e.g., "turbo", "viridis", "tol", "Dark2", etc.) or a user-defined vector of R colours (e.g., c("yellow", "green", "blue", "black") - see colours() for a full list) or hex-codes (e.g., c("#30123B", "#9CF649", "#7A0403")). Alternatively, can be a list of arguments to control the colour palette more closely (e.g., palette, direction, alpha, etc.). See openColours() and colourOpts() for more details.

theme

A string representing an overall plot theme, defaulting to "default". This option makes sweeping changes to non-data plot features such as fonts, colours, line widths, and so on, and may also change default arguments like cols if not set by the user. Can also take a ggplot2::theme() object, which will be used to modify the "default" theme. Pre-set options include:

"default", a lattice-inspired theme resembling the traditional openair look, with structured panels and visible gridlines.
"dark", a dark-background variant of the default theme, designed for presentations and low-light viewing, using high-contrast text and colour palettes optimised for visibility against dark panels.
"modern", a minimalist, contemporary theme inspired by tools such as Plotly and Observable Plot, with reduced visual clutter, horizontal emphasis in gridlines, a clean legend style, and typography suited to dashboards and reports.
"soft", a low-contrast, 'editorial' theme with warm background tones, subtle gridlines, and gently desaturated colours, designed for reports and publication-style figures, particularly where a calmer appearance improves readability.
"print", a strictly greyscale theme optimised for black-and-white reproduction, with stronger structural elements such as clearer gridlines and axis definitions to ensure good contrast and readability in printed or photocopied outputs.

Please note that if a global theme is set with ggplot2::theme_set() to anything other than the default ggplot2::theme_grey(), the selected openair theme will not be fully applied; instead, only minimal adjustments (such as legend positioning) will be made.

normalise

If normalise = TRUE then each time interval is scaled to 100. This is helpful to show the relative (percentage) contribution of the proportions.

ref.x

Either a single value or values representing the x axis intercepts to draw lines, or a list such as that provided by refOpts() to customise the colour/width/type/etc. of each line. See refOpts() for more details.

ref.y

Either a single value or values representing the y axis intercepts to draw lines, or a list such as that provided by refOpts() to customise the colour/width/type/etc. of each line. See refOpts() for more details.

key.columns

Number of columns to be used in a categorical legend. With many categories a single column can make to key too wide. The user can thus choose to use several columns by setting key.columns to be less than the number of categories.

key.position

Location where the legend is to be placed. Allowed arguments include "top", "right", "bottom", "left" and "none", the last of which removes the legend entirely.

key.title

Used to set the title of the legend. The legend title is passed to quickText() if auto.text = TRUE.

date.breaks

Number of major x-axis intervals to use. The function will try and choose a sensible number of dates/times as well as formatting the date/time appropriately to the range being considered. The user can override this behaviour by adjusting the value of date.breaks up or down.

date.format

This option controls the date format on the x-axis. A sensible format is chosen by default, but the user can set date.format to override this. For format types see strptime(). For example, to format the date like "Jan-2012" set date.format = "\%b-\%Y".

auto.text

Either TRUE (default) or FALSE. If TRUE titles and axis labels will automatically try and format pollutant names and units properly, e.g., by subscripting the "2" in "NO2". Passed to quickText().

plot

When openair plots are created they are automatically printed to the active graphics device. plot = FALSE deactivates this behaviour. This may be useful when the plot data is of more interest, or the plot is required to appear later (e.g., later in a Quarto document, or to be saved to a file).

key

Deprecated; please use key.position. If FALSE, sets key.position to "none".

...

Addition options are passed on to cutData() for type handling. Some additional arguments are also available, varying somewhat in different plotting functions:

title, subtitle, caption, tag, xlab and ylab control the plot title, subtitle, caption, tag, x-axis label and y-axis label, passed to ggplot2::labs() via quickText() if auto.text = TRUE.
xlim, ylim and limits control the limits of the x-axis, y-axis and colorbar scales.
ncol and nrow set the number of columns and rows in a faceted plot.
scales can be "fixed", "free_x", "free_y" or "free" to control whether axes are shared across facets when using type. Also supported are the legacy x.relation and y.relation, which can be either "same" or "free" and get remapped to scales automatically.
Similarly, space, axes, axis.labels, switch and strip.position can be used to customise the appearance of faceted plots. See ggplot2::facet_wrap() and ggplot2::facet_grid() for the arguments these take.
fontsize overrides the overall font size of the plot by setting the text argument of ggplot2::theme(). It may also be applied proportionately to any openair annotations (e.g., N/E/S/W labels on polar coordinate plots).
Various graphical parameters are also supported: linewidth, linetype, shape, size, border, and alpha. Not all parameters apply to all plots. These can take a single value, or a vector of multiple values - e.g., shape = c(1, 2) - which will be recycled to the length of values needed.
lineend, linejoin and linemitre tweak the appearance of line plots; see ggplot2::geom_line() for more information.
In polar coordinate plots, annotate = FALSE will remove the N/E/S/W labels and any other annotations.

Value

an openair object

Details

In order to plot time series in this way, some sort of time aggregation is needed, which is controlled by the option avg.time.

The plot shows the value of pollutant on the y-axis (averaged according to avg.time). The time intervals are made up of bars split according to proportion. The bars therefore show how the total value of pollutant is made up for any time interval.

Author

David Carslaw

Jack Davison

Examples

# monthly plot of SO2 showing the contribution by wind sector
timeProp(mydata, pollutant = "so2", avg.time = "month", proportion = "wd")
#> Warning: ! Removing 219 rows due to missing `wd` data.