openair (version 0.3-13)

summaryPlot: Function to rapidly provide an overview of air quality data

Description

This function provides a quick graphical and numerical summary of data. The location presence/absence of data are shown, with summary statistics and plots of variable distributions. summaryPlot can also provide summaries of a single pollutant across many sites.

Usage

summaryPlot(mydata,
na.len = 24,
clip = TRUE,
percentile = 0.99,
type = "histogram",
pollutant = "nox",
period = "years",
breaks = 20,
col.trend = "darkgoldenrod2",
col.data = "lightblue",
col.mis = rgb(0.65, 0.04, 0.07),
col.hist = "forestgreen",
main = "",
date.breaks = 7,
auto.text = TRUE,
xlab = NULL,
ylab = NULL,
...)

Arguments

mydata

A data frame to be summarised. Must contain a date field and at least one other parameter.

na.len

Missing data are only shown with at least na.len contiguous missing vales. The purpose of setting na.len is for clarity: with long time series it is difficult to see where individual missing hours are. Furthermo

clip

When data contain outliers, the histogram or density plot can fail to show the distribution of the main body of data. Setting clip = TRUE, will remove the top 1 % of data to yield what is often a better display of the overall distrib

percentile

This is used to clip the data. For example, percentile = 0.99 (the default) will remove the top 1 percentile of values i.e. values greater than the 99th percentile will not be used.

type

type is used to determine whether a histogram (the default) or a density plot is used to show the distribution of the data.

pollutant

pollutant is used when there is a field site and there is more than one site in the data frame.

period

period is either year (the default) or month. Statistics are calculated depending on the period chosen.

breaks

Number of histogram bins. Sometime useful but not easy to set a single value for a range of very different variables.

col.trend

Colour to be used to show the monthly trend of the data, shown as a shaded region. Type colors() into R to see the full range of colour names.

col.data

Colour to be used to show the presence of data. Type colors() into R to see the full range of colour names.

col.mis

Colour to be used to show missing data.

col.hist

Colour for the histogram or density plot.

main

The title of the plot, if required.

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. This does not always work as desired automatically.

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.

xlab

x-axis label.

ylab

y-axis label.

...

Other graphical parameters.

Details

summaryPlot produces two panels of plots: one showing the presence/absence of data and the other the distributions. The left panel shows time series and codes the presence or absence of data in different colours. By stacking the plots one on top of another it is easy to compare different pollutants/variables. Overall statistics are given for each variable: mean, maximum, minimum, missing hours (also expressed as a percentage), median and the 95th percentile. For each year the data capture rate (expressed as a percentage of hours in that year) is also given. The right panel shows either a histogram or a density plot depending on the choice of type. Density plots avoid the issue of arbitrary bin sizes that can sometimes provide a misleading view of the data distribution. Density plots are often more appropriate, but their effectiveness will depend on the data in question. summaryPlot will only show data that are numeric or integer type. This is useful for checking that data have been imported properly. For example, if for some reason a column representing wind speed erroneosly had one or more fields with charcters in, the whole column would be either character or factor type. The absence of a wind speed variable in the summaryPlot plot would therefore indicate a problem with the input data. In this particular case, the user should go back to the source data and remove the characters or remove them using R functions. If there is a field site, which would generally mean there is more than one site, summaryPlot will provide information on a single pollutant across all sites, rather than provide details on all pollutants at a single site. In this case the user should also provide a name of a pollutant e.g. pollutant = "nox". If a pollutant is not provided the first numeric field will automatically be chosen. It is strongly recommended that the summaryPlot function is applied to all new imported data sets to ensure the data are imported as expected.

Examples

# load example data from package
data(mydata)

# do not clip density plot data
summaryPlot(mydata, clip = FALSE)

# exclude highest 5 \% of data etc.
summaryPlot(mydata, percentile = 0.95)

# show missing data where there are at least 96 contiguous missing
# values (4 days)
summaryPlot(mydata, na.len = 96)

# show data in green
summaryPlot(mydata, col.data = "green")

# show missing data in yellow
summaryPlot(mydata, col.mis = "yellow")

# show density plot line in black
summaryPlot(mydata, col.dens = "black")