Description Usage Arguments Methods Examples
Plot acs objects, with both estimates and confidence intervals.
1 2 3 4 
x 
the acs object to be plotted 
conf.level 
the desired confidence interval to use for error bars; numeric between 0<1 
err.col 
the color to use for the error bars; analogous to
graphic parameter 
err.lwd 
the line weight to use for the error bars; analogous to
graphic parameter 
err.pch 
the point character to use for the error bars; analogous to
graphic parameter 
err.cex 
the scaling factor to use for the error bars; analogous to
graphic parameter 
err.lty 
the line type to use for the error bars; analogous to
graphic parameter 
x.res 
when plot called with a single acs value (see below), x.res determines the resolution of the resulting density plot; integer (defaults to 300, i.e., the curve is drawn with 300 points) 
labels 
the labels to use for the x axis; defaults to either geography names or acs.colnames based on dimensions of object plotted; vector of proper length required 
by 
in cases where multiple rows and columns are plotted,
whether to provide a different plot for each value of 
true.min 
whether to limit the lower bound of a confidence
interval to some value or now; 
... 
provided to allow for passing of additional arguments to plot functions 
signature(object = "acs")
When passed an acs object (possibly involving subsetting), plot
will call a plot showing both estimates and confidence intervals for
the data contained in the object.
If the object contains only one row or only one column, plot
will use this dimension as the yaxis and will plot each observation
along the xaxis, as three points (an estimate bracketed by upper and
lower confidence bounds). If the object contains multiple rows and
columns, plot
will return a 1byy "plot of plots": by default
there will be one plot per row showing all the data for each
geography, although this can be changed by specifying
by="acs.colnames"
, to plot each variable as its own plot, with
all of the geographies along the xaxis.
In the special case where the dimensions of the object are
exactly c(1,1) (i.e., a single geography and column),
plot
will return a density plot of the estimate. In this
case, conf.level
, err.col
, err.lty
, and
err.lwd
will be used to determine the properties of the
margins of error lines. (For none, use conf.level=FALSE
.
For these density plots, users may also wish to set xlim
and x.res
, which specify the horizontal extent and
resolution of the plot.)
plot
accepts many of the standard graphical arguments to
plot
, such as main
, sub
, xlab
, pch
,
and col
, as well new ones listed above.
In some cases, the lower bound of a confidence interval may
extend below 0; in some cases this is desired, especially when a
variable is actually stating the difference between two
estimates. In other cases, this may seem confusing (for
example, when reporting the estimated count in a particular
category). Setting true.min
to FALSE
(or 0) will
limit the lower boundary of any confidence intervals computed
and plotted.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30  # load ACS data
data(kansas07)
# plot a single value
plot(kansas07[4,4])
# plot by geography
plot(kansas07[,10])
# plot by columns
plot(kansas07[4,3:10])
# a density plot for a single variable
plot(kansas07[7,10])
# same, using some graphical parameters
plot(kansas07[7,10], col="blue", err.col="purple", err.lty=3)
plot(kansas07[7,49], col="lightblue", type="h", x.res=3000,
err.col="purple", err.lty=3, err.lwd=4, conf.level=.99,
main=(paste("Distribution of Females>85 Years in ",
geography(kansas07)[7,1], sep="")),
sub="(99percent margin of error shown in purple)")
# something more complicated...
plot(kansas07[c(1,3,4),3:25], err.col="purple",
pch=16, err.pch="x", err.cex=1, ylim=c(0,5000),
col=rainbow(23), conf.level=.99,
labels=paste("grp. ",1:23))

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