R: Plot time series values in convential calendar format

calendarPlot {openair} | R Documentation

## Plot time series values in convential calendar format

### Description

This function will plot data by month laid out in a conventional calendar format. The main purpose is to help rapidly visualise potentially complex data in a familiar way. Users can also choose to show daily mean wind vectors if wind speed and direction are available.

### Usage

    calendarPlot(
      mydata,
      pollutant = "nox",
      year = 2003,
      month = 1:12,
      type = "default",
      annotate = "date",
      statistic = "mean",
      cols = "heat",
      limits = c(0, 100),
      lim = NULL,
      col.lim = c("grey30", "black"),
      col.arrow = "black",
      font.lim = c(1, 2),
      cex.lim = c(0.6, 1),
      digits = 0,
      data.thresh = 0,
      labels = NA,
      breaks = NA,
      w.shift = 0,
      remove.empty = TRUE,
      main = NULL,
      key.header = "",
      key.footer = "",
      key.position = "right",
      key = TRUE,
      auto.text = TRUE,
      ...
    )

### Arguments

`mydata` | A data frame minimally containing `date` and at least one other numeric variable. The date should be in either `Date` format or class `POSIXct`.
`pollutant` | Mandatory. A pollutant name corresponding to a variable in a data frame should be supplied e.g. `pollutant = "nox".`
`year` | Year to plot e.g. `year = 2003`. If not supplied all data potentially spanning several years will be plotted.
`month` | If only certain month are required. By default the function will plot an entire year even if months are missing. To only plot certain months use the `month` option where month is a numeric 1:12 e.g. `month = c(1, 12)` to only plot January and December.
`type` | Not yet implemented.
`annotate` | This option controls what appears on each day of the calendar. Can be: “date” — shows day of the month; “wd” — shows vector-averaged wind direction, or “ws” — shows vector-averaged wind direction scaled by wind speed. Finally it can be “value” which shows the daily mean value.
`statistic` | Statistic passed to `timeAverage`.
`cols` | Colours to be used for plotting. Options include “default”, “increment”, “heat”, “jet” and `RColorBrewer` colours — see the `openair` `openColours` function for more details. For user defined the user can supply a list of colour names recognised by R (type `colours()` to see the full list). An example would be `cols = c("yellow", "green", "blue")`
`limits` | Use this option to manually set the colour scale limits. This is useful in the case when there is a need for two or more plots and a consistent scale is needed on each. Set the limits to cover the maximimum range of the data for all plots of interest. For example, if one plot had data covering 0–60 and another 0–100, then set `limits = c(0, 100)`. Note that data will be ignored if outside the limits range.
`lim` | A threshold value to help differentiate values above and below `lim`. It is used when `annotate = "value"`. See next few options for control over the labels used.
`col.lim` | For the annotation of concentration labels on each day. The first sets the colour of the text below `lim` and the second sets the colour of the text above `lim`.
`col.arrow` | The colour of the annotated wind direction / wind speed arrows.
`font.lim` | For the annotation of concentration labels on each day. The first sets the font of the text below `lim` and the second sets the font of the text above `lim`. Note that font = 1 is normal text and font = 2 is bold text.
`cex.lim` | For the annotation of concentration labels on each day. The first sets the size of the text below `lim` and the second sets the size of the text above `lim`.
`digits` | The number of digits used to display concentration values when `annotate = "value"`.
`data.thresh` | Data capture threshold passed to `timeAverage`. For example, `data.thresh = 75` means that at least 75% of the data must be available in a day for the value to be calculate, else the data is removed.
`labels` | If a categorical scale is required then these labels will be used. Note there is one less label than break. For example, `labels = c("good", "bad", "very bad")`. `breaks` must also be supplied if labels are given.
`breaks` | If a categorical scale is required then these breaks will be used. For example, `breaks = c(0, 50, 100, 1000)`. In this case “good” corresponds to values berween 0 and 50 and so on. Users should set the maximum value of `breaks` to exceed the maximum data value to ensure it is within the maximum final range e.g. 100–1000 in this case.
`w.shift` | Controls the order of the days of the week. By default the plot shows Saturday first (`w.shift = 0`). To change this so that it starts on a Monday for example, set `w.shift = 2`, and so on.
`remove.empty` | Should months with no data present be removed? Default is `TRUE`.
`main` | The plot title; default is pollutant and year.
`key.header` | Adds additional text/labels to the scale key. For example, passing `calendarPlot(mydata, key.header = "header", key.footer = "footer")` adds addition text above and below the scale key. These arguments are passed to `drawOpenKey` via `quickText`, applying the `auto.text` argument, to handle formatting.
`key.footer` | see `key.header`.
`key.position` | Location where the scale key is to plotted. Allowed arguments currently include `"top"`, `"right"`, `"bottom"` and `"left"`.
`key` | Fine control of the scale key via `drawOpenKey`. See `drawOpenKey` for further details.
`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.
`...` | Other graphical parameters are passed onto the `lattice` function `lattice:levelplot`, with common axis and title labelling options (such as `xlab`, `ylab`, `main`) being passed to via `quickText` to handle routine formatting.

### Details

`calendarPlot` will plot data in a conventional calendar format i.e. by month and day of the week. Daily statistics are calculated using `timeAverage`, which by default will calculate the daily mean concentration.

If wind direction is available it is then possible to plot the wind direction vector on each day. This is very useful for getting a feel for the meteorological conditions that affect pollutant concentrations. Note that if hourly or higher time resolution are supplied, then `calendarPlot` will calculate daily averages using `timeAverage`, which ensures that wind directions are vector-averaged.

If wind speed is also available, then setting the option `annotate = "ws"` will plot the wind vectors whose length is scaled to the wind speed. Thus information on the daily mean wind speed and direction are available.

It is also possible to plot categorical scales. This is useful where, for example, an air quality index defines concentrations as bands e.g. “good”, “poor”. In these cases users must supply `labels` and corresponding `breaks`.

Note that is is possible to pre-calculate concentrations in some way before passing the data to `calendarPlot`. For example `rollingMean` could be used to calculate rolling 8-hour mean concentrations. The data can then be passed to `calendarPlot` and `statistic = "max"` chosen, which will plot maximum daily 8-hour mean concentrations.

### Value

As well as generating the plot itself, `calendarPlot` also returns an object of class “openair”. The object includes three main components: `call`, the command used to generate the plot; `data`, the data frame of summarised information used to make the plot; and `plot`, the plot itself. If retained, e.g. using `output <- calendarPlot(mydata, "nox")`, this output can be used to recover the data, reproduce or rework the original plot or undertake further analysis.

An openair output can be manipulated using a number of generic operations, including `print`, `plot` and `summary`.

### Author(s)

David Carslaw

### See Also

`timePlot`, `timeVariation`

### Examples

    # load example data from package
    data(mydata)

    # basic plot
    calendarPlot(mydata, pollutant = "o3", year = 2003)

    # show wind vectors
    calendarPlot(mydata, pollutant = "o3", year = 2003, annotate = "wd")
    ## Not run:
    # show wind vectors scaled by wind speed and different colours
    calendarPlot(mydata, pollutant = "o3", year = 2003, annotate = "ws",
    cols = "heat")

    # show only specific months with selectByDate
    calendarPlot(selectByDate(mydata, month = c(3,6,10), year = 2003),
    pollutant = "o3", year = 2003, annotate = "ws", cols = "heat")

    # categorical scale example
    calendarPlot(mydata, pollutant = "no2", breaks = c(0, 50, 100, 150, 1000),
    labels = c("Very low", "Low", "High", "Very High"),
    cols = c("lightblue", "green", "yellow",  "red"), statistic = "max")

    ## End(Not run)

[Package openair version 2.8-5 Index]