Last chance! 50% off unlimited learning
Sale ends in
Constructs and plots diverging stacked barcharts for Likert, semantic differential, rating scale data, and population pyramids.
likert(x, ...)
likertplot(x, ...)
# S3 method for likert
plot(x, ...)
# S3 method for formula
plot.likert(x, data, ReferenceZero=NULL, value, levelsName="",
scales.in=NULL, ## use scales=
between=list(x=1 + (horizontal), y=.5 + 2*(!horizontal)),
auto.key.in=NULL, ## use auto.key=
panel.in=NULL, ## use panel=
horizontal=TRUE,
par.settings.in=NULL, ## use par.settings=
...,
as.percent = FALSE,
## titles
ylab= if (horizontal) {
if (length(x)==3)
deparse(x[[2]])
else
"Question"
}
else
if (as.percent != FALSE) "Percent" else "Count",
xlab= if (!horizontal) {
if (length(x)==3)
deparse(x[[2]])
else
"Question"
}
else
if (as.percent != FALSE) "Percent" else "Count",
main = x.sys.call,
## right axis
rightAxisLabels = rowSums(data.list$Nums),
rightAxis = !missing(rightAxisLabels),
ylab.right = if (rightAxis) "Row Count Totals" else NULL,
xlab.top = NULL,
right.text.cex =
if (horizontal) { ## lazy evaluation
if (!is.null(scales$y$cex)) scales$y$cex else .8
}
else
{
if (!is.null(scales$x$cex)) scales$x$cex else .8
}, ## scales
xscale.components = xscale.components.top.HH,
yscale.components = yscale.components.right.HH,
xlimEqualLeftRight = FALSE,
xTickLabelsPositive = TRUE,
## row sequencing
as.table=TRUE,
positive.order=FALSE,
data.order=FALSE,
reverse=ifelse(horizontal, as.table, FALSE),
## resizePanels arguments
h.resizePanels=sapply(result$y.used.at, length),
w.resizePanels=sapply(result$x.used.at, length),
## color options
reference.line.col="gray65",
key.border.white=TRUE,
col=likertColor(Nums.attr$nlevels,
ReferenceZero=ReferenceZero,
colorFunction=colorFunction,
colorFunctionOption=colorFunctionOption),
colorFunction="diverge_hcl",
colorFunctionOption="lighter"
)
# S3 method for default
plot.likert(x,
positive.order=FALSE,
ylab=names(dimnames(x)[1]),
xlab=if (as.percent != FALSE) "Percent" else "Count",
main=xName,
reference.line.col="gray65",
col.strip.background="gray97",
col=likertColor(attr(x, "nlevels"),
ReferenceZero=ReferenceZero,
colorFunction=colorFunction,
colorFunctionOption=colorFunctionOption),
colorFunction="diverge_hcl",
colorFunctionOption="lighter",
as.percent=FALSE,
par.settings.in=NULL,
horizontal=TRUE,
ReferenceZero=NULL,
...,
key.border.white=TRUE,
xName=deparse(substitute(x)),
rightAxisLabels=rowSums(abs(x)),
rightAxis=!missing(rightAxisLabels),
ylab.right=if (rightAxis) "Row Count Totals" else NULL,
panel=panel.barchart,
xscale.components=xscale.components.top.HH,
yscale.components=yscale.components.right.HH,
xlimEqualLeftRight=FALSE,
xTickLabelsPositive=TRUE,
reverse=FALSE)
# S3 method for array
plot.likert(x,
condlevelsName=paste("names(dimnames(", xName, "))[-(1:2)]",
sep=""),
xName=deparse(substitute(x)),
main=paste("layers of", xName, "by", condlevelsName),
...)
# S3 method for likert
plot.likert(x, ...) ## See Details
# S3 method for list
plot.likert(x, ## named list of matrices, 2D tables,
## 2D ftables, or 2D structables,
## or all-numeric data.frames
condlevelsName="ListNames",
xName=deparse(substitute(x)),
main=paste("List items of", xName, "by", condlevelsName),
layout=if (length(dim.x) > 1) dim.x else {
if (horizontal) c(1, length(x)) else c(length(x), 1)},
positive.order=FALSE,
strip=!horizontal,
strip.left=horizontal,
strip.left.values=names(x),
strip.values=names(x),
strip.par=list(cex=1, lines=1),
strip.left.par=list(cex=1, lines=1),
horizontal=TRUE,
...,
rightAxisLabels=sapply(x, function(x) rowSums(abs(x)), simplify = FALSE),
rightAxis=!missing(rightAxisLabels),
resize.height.tuning=-.5,
resize.height=if (missing(layout) || length(dim.x) != 2) {
c("nrow","rowSums")
} else {
rep(1, layout[2])
},
resize.width=if (missing(layout)) {1 } else {
rep(1, layout[1])
},
box.ratio=if (
length(resize.height)==1 &&
resize.height == "rowSums") 1000 else 2,
xscale.components=xscale.components.top.HH,
yscale.components=yscale.components.right.HH)
# S3 method for table
plot.likert(x, ..., xName=deparse(substitute(x)))
# S3 method for ftable
plot.likert(x, ..., xName=deparse(substitute(x)))
# S3 method for structable
plot.likert(x, ..., xName=deparse(substitute(x)))
# S3 method for data.frame
plot.likert(x, ..., xName=deparse(substitute(x)))
xscale.components.top.HH(...)
yscale.components.right.HH(...)
For the formula method, a model formula. All terms in the
formula must be the names of columns in the data.frame argument
data or the special abbreviation . only on the right-hand-side. Functions of the
names will not work. The right-hand-side must be either . or
the sum of the names of numeric variables in data.
Non-syntactic names must be in quotes (single ' or double
"),
but not backticks `. The . on the
right-hand-side is expanded to the formula containing the sum of all
remaining (after the response and the conditioning variables)
numeric columns in data. An empty left-hand-side is
interpreted as the rownames(data). See the examples
for all possible forms of formula recognized by the likert function.
Otherwise, any numeric object stored as a vector, matrix, array,
data.frame, table, ftable, structable (as defined in the vcd
package), or as a list of named two-dimensional objects. This is
the only required argument. See the Details section for
restrictions on the form of data.frame, list, ftable, and structable
arguments.
For the formula method, a data.frame.
Do not use variable names ".value" or ".variable".
Numeric scalar or NULL. The position in
the range
seq(0, attr(x, "nlevels")+.5, .5) where the
reference line at 0 will be placed. attr(x, "nlevels") is the
number of columns of the original argument x, before it
has been coerced to a "likert" object. The default
NULL corresponds to the middle level if there are an odd
number of levels, and to half-way between the two middle levels if
there are an even number of levels. This argument is used when the
number of positive levels and the number of negative levels are not
the same. For example, with 4 levels
c("Disagree", "Neutral", "Weak Agree", "Strong Agree"), the
argument would be specified ReferenceZero=2 indicating that
the graphical split would be in the middle of the second group with
label "Neutral".
Name of the numeric variable containing the data when the formula method is used with the long data form. The predictor in the formula will be a factor name. The name of the predictor will be used as the title in the key.
(optional) Name of the implied factor distinguishing the columns of the response variables when the formula method is used with the wide data form. This name will be used as the title in the key.
If FALSE, the default value, the original
order of the rows is retained. This is necessary for arrays,
because each panel has the same rownames. If TRUE, rows are
ordered within each panel with the row whose bar goes farthest to
the right at the top of a panel of horizontal bars or at the left of
a panel of vertical bars.
positive.order is frequently set to TRUE for lists.
formula method only. If
positive.order is TRUE, this data.order
variable is ignored.
If FALSE, the default value, and the rows are specified by a
factor, then they are ordered by their levels. If TRUE, then
the rows are ordered by their order in the input data.frame.
When as.percent==TRUE or
as.percent=="noRightAxis", then the values in each row are rescaled
to row percents.
When as.percent==TRUE the original row totals are used as
rightAxisLabels,
rightAxis is set to TRUE, the ylab.right is by
default set to "Row Count Totals" (the user can change its value in
the calling sequence). When as.percent=="noRightAxis", then
rightAxis will be set to FALSE.
Standard lattice argument. See barchart.
These are placeholders
for lattice arguments that lets the user
specify some lattice par.settings and still retain the
ones that are prespecified in the
plot.likert.default.
Standard lattice graph
labels in barchart.
The right axis, as used here for the
"Row Count Totals", has non-standard controls. It's cex
follows the cex of the left axis, unless this argument is
used to override that value. When codehorizontal=FALSE, then
the top axis defaults to follow the bottom
axis unless overridden by right.text.cex.
Standard lattice argument.
Vector of color names for the levels of the agreement factor.
Although the colors can be specified as an arbitrary vector of color names, for example,
col=c('red','blue','#4AB3F2'), usually specifying one of the diverging
palettes from diverge_hcl or sequential
palettes from sequential_hcl will suffice.
For less intense colors, you can use the middle colors from a larger
set of colors; e.g., col=sequential_hcl(11)[5:2]. See the last
AudiencePercent example below for this usage.
See likertColor.
Color for reference line at zero.
Background color for the strip labels.
Logical. If TRUE, then place a white
border around the rect in the key, else use the col of
the rect itself.
Logical, with default TRUE indicating
horizontal bars, will be passed to the
barchart function by the plot.likert method.
In addition, it interchanges the meaning of resize.height and
resize.width arguments
to the likert functions applied to arrays and lists.
other arguments. These will be passed to the barchart
function by the plot.likert method. The most useful of these
is the border argument which defaults to make the borders of
the bars the same color as the bars themselves. A scalar
alternative (border="white" being our first choice) puts a border
around each bar in the stacked barchart. This works very well when
the ReferenceZero line is between two levels. It gives a
misleading division of the central bar when the ReferenceZero
is in the middle of a level. See the example in the examples
section.
Arguments to the lattice auto.key=list() argument
(described in barchart) will be used in the
legend. See the examples.
Logical. The default strip.left=TRUE
places the strip
labels on the left of each panel as in the
first professional challenges example.
The alternative
strip.left=FALSE puts
the strip labels on the top of each panel, the traditional
lattice strip label position.
Arguments which will be passed to
ResizeEtc.
Name of the argument in its original environment.
logical. Should right axis values be displayed?
Defaults to FALSE unless
rightAxisLabels are specified.
Values to be displayed on the right axis. The
default values are the row totals. These are sensible for
tables of counts. When the data is rescaled to percents by the
as.percent=TRUE argument, then the rightAxisLabels
are still defaulted to the row totals for the counts.
We illustrate this usage in the ProfChal example.
Tuning parameter used to adjust the space
between bars as specified by the resize.height argument to
the ResizeEtc function.
Either character scalar or numeric vector.
If "nrow", then the panels heights are proportional to the number of
bars in each panel. If "rowSums" and there is exactly one bar
per panel,
then the panels heights are proportional to the total count in each
bar, and see the discussion of the box.ratio argument.
If a numeric vector, the panel heights are proportional to the numbers
in the argument.
Numeric vector. The panel widths are proportional to the numbers in the argument.
If there are more than one bar in any panel, then
this defaults to the trellis standard value of 2.
If there is exactly one bar in a panel, then the value is 1000, with
the intent to minimize the white space in the panel. In this way,
when as.percent==TRUE, the
bar total area is the count and the bar widths are all equal at
100%. See the example below.
panel function eventually to be used by barchart.
See
yscale.components.default.
xscale.components.top.HH constructs the top x-axis
labels, when needed, as the names of the bottom x-axis labels.
yscale.components.right.HH constructs the right y-axis
labels, when needed, as the names of the left y-axis labels. The
names are placed automatically by the plot.likert methods based on
the value of the arguments as.percent, rightAxis,
and rightAxisLabels. By default, when rightAxis != FALSE the layout.widths
are set to list(ylab.right=5, right.padding=0). Otherwise,
those arguments are left at their default values. They may be
adjusted with an argument of the form par.settings.in=
list(layout.widths=list(ylab.right=5, right.padding=0)).
Similarly, spacing for the top labels can be adjusted with an
argument of the form
par.settings.in=list(layout.heights=list(key.axis.padding=6)).
Logical. The default is FALSE. If
TRUE and at and labels are not explicitly specified,
then the left and right x limits are set to negative
and positive of the larger of the absolute value of the original x limits.
When !horizontal, this argument applies to the y coordinate.
Logical. The default is TRUE.
If TRUE and at and labels are not explicitly specified,
then the tick labels on the negative side are
displayed as positive values. When !horizontal, this argument
applies to the y coordinate.
Logical. The default is FALSE.
If TRUE, the rows of the input matrix are reversed.
The default is to plot the rows from top-to-bottom
for horizontal bars
and from left-to-write for vertical bars.
reverse, positive.order, and horizontal are
independent.
All eight combinations are possible. See the
Eight sequences and orientations section
in the example for all eight.
A "trellis" object containing the plot. The plot will be
automatically displayed unless the result is assigned to an object.
The counts (or percentages) of respondents on each row who agree with
the statement are shown to the right of the zero line; the counts (or
percentages) who disagree are shown to the left. The counts (or
percentages) for respondents who neither agree nor disagree are split
down the middle and are shown in a neutral color. The neutral category
is omitted when the scale has an even number of choices.
It is difficult to compare
lengths without a common baseline. In this situation, we are primarily
interested in the total count (or percent) to the right or left of the
zero line; the breakdown into strongly or not is of lesser interest so
that the primary comparisons do have a common baseline of zero. The
rows within each panel are displayed in their original order by
default. If the argument positive.order=TRUE is specified, the rows
are ordered by the counts (or percentages) who agree.
Diverging stacked barcharts are also called "two-directional stacked barcharts". Some authors use the term "floating barcharts" for vertical diverging stacked barcharts and the term "sliding barcharts" for horizontal diverging stacked barcharts.
All items in a list of named two-dimensional objects must have the
same number of columns. If the items have different column names, the
column names of the last item in the list will be used in the key. If
the dimnames of the matrices are named, the names will be used in the
plot. It is possible to produce a likert plot with a list of objects
with different numbers of columns, but not with the
plot.likert.list method. These must be done manually by using
the ResizeEtc function on each of the individual likert
plots. The difficulty is that the legend is based on the last item in
the list and will have the wrong number of values for some of the
panels.
A single data.frame x will be plotted as data.matrix(x[sapply(x, is.numeric)]).
The subscripting on the class of the columns is there to remove
columns of characters (which would otherwise be coerced to NA) and
factor columns (which would otherwise be coerced to integers).
A data.frame with only numeric columns will work in a named list.
A list of data.frame with factors or characters will be plotted by
automatically removing columns that are not numeric.
ftable and structable arguments x will be plotted as
as.table(x). This changes the display sequence.
Therefore the user will probably want to use aperm on the
ftable or structable before using plot.likert.
The likert method is designed for use with "likert"
objects created with the independent likert package. It is not
recommended that the HH package and the likert package
both be loaded at the same time, as they have incompatible usage of
the exported function names likert and plot.likert. If
the likert package is installed, it can be run without loading
by using the function calls likert::likert() and
likert:::plot.likert().
Richard M. Heiberger, Naomi B. Robbins (2014)., "Design of Diverging Stacked Bar Charts for Likert Scales and Other Applications", Journal of Statistical Software, 57(5), 1--32, http://www.jstatsoft.org/v57/i05/.
Richard Heiberger and Naomi Robbins (2011), "Alternative to Charles Blow's Figure in \"Newt's War on Poor Children\"", Forbes OnLine, December 20, 2011. http://www.forbes.com/sites/naomirobbins/2011/12/20/alternative-to-charles-blows-figure-in-newts-war-on-poor-children-2/
Naomi Robbins (2011), "Visualizing Data: Challenges to
Presentation of Quality Graphics---and Solutions", Amstat News,
September 2011, 28--30.
http://magazine.amstat.org/blog/2011/09/01/visualizingdata/
Luo, Amy and Tim Keyes (2005). "Second Set of Results in from the Career Track Member Survey," Amstat News. Arlington, VA: American Statistical Association.
barchart, ResizeEtc,
as.likert,
as.matrix.listOfNamedMatrices,
pyramidLikert
# NOT RUN {
## See file HH/demo/likert-paper.r for a complete set of examples using
## the formula method into the underlying lattice:::barchart plotting
## technology. See file HH/demo/likert-paper-noFormula.r for the same
## set of examples using the matrix and list of matrices methods. See
## file HH/demo/likertMosaic-paper.r for the same set of examples using
## the still experimental functions built on the vcd:::mosaic as the
## underlying plotting technology
data(ProfChal) ## ProfChal is a data.frame.
## See below for discussion of the dataset.
## Count plot
likert(Question ~ . , ProfChal[ProfChal$Subtable=="Employment sector",],
main='Is your job professionally challenging?',
ylab=NULL,
sub="This plot looks better in a 9in x 4in window.")
## Percent plot calculated automatically from Count data
likert(Question ~ . , ProfChal[ProfChal$Subtable=="Employment sector",],
as.percent=TRUE,
main='Is your job professionally challenging?',
ylab=NULL,
sub="This plot looks better in a 9in x 4in window.")
## formula method
data(NZScienceTeaching)
likert(Question ~ . | Subtable, data=NZScienceTeaching,
ylab=NULL,
scales=list(y=list(relation="free")), layout=c(1,2))
# }
# NOT RUN {
## formula notation with expanded right-hand-side
likert(Question ~
"Strongly disagree" + Disagree + Neutral + Agree + "Strongly agree" |
Subtable, data=NZScienceTeaching,
ylab=NULL,
scales=list(y=list(relation="free")), layout=c(1,2))
# }
# NOT RUN {
# }
# NOT RUN {
## formula notation with long data arrangement
NZScienceTeachingLong <- reshape2::melt(NZScienceTeaching,
id.vars=c("Question", "Subtable"))
names(NZScienceTeachingLong)[3] <- "Agreement"
head(NZScienceTeachingLong)
likert(Question ~ Agreement | Subtable, value="value", data=NZScienceTeachingLong,
ylab=NULL,
scales=list(y=list(relation="free")), layout=c(1,2))
# }
# NOT RUN {
## Examples with higher-dimensional arrays.
tmp3 <- array(1:24, dim=c(2,3,4),
dimnames=list(A=letters[1:2], B=LETTERS[3:5], C=letters[6:9]))
## positive.order=FALSE is the default. With arrays
## the rownames within each item of an array are identical.
## likert(tmp3)
likert(tmp3, layout=c(1,4))
likert(tmp3, layout=c(2,2), resize.height=c(2,1), resize.width=c(3,4))
## plot.likert interprets vectors as single-row matrices.
## http://survey.cvent.com/blog/customer-insights-2/box-scores-are-not-just-for-baseball
Responses <- c(15, 13, 12, 25, 35)
names(Responses) <- c("Strongly Disagree", "Disagree", "No Opinion",
"Agree", "Strongly Agree")
# }
# NOT RUN {
likert(Responses, main="Retail-R-Us offers the best everyday prices.",
sub="This plot looks better in a 9in x 2.6in window.")
# }
# NOT RUN {
## reverse=TRUE is needed for a single-column key with
## horizontal=FALSE and with space="right"
likert(Responses, horizontal=FALSE,
aspect=1.5,
main="Retail-R-Us offers the best everyday prices.",
auto.key=list(space="right", columns=1,
reverse=TRUE, padding.text=2),
sub="This plot looks better in a 4in x 3in window.")
# }
# NOT RUN {
## Since age is always positive and increases in a single direction,
## this example uses colors from a sequential palette for the age
## groups. In this example we do not use a diverging palette that is
## appropriate when groups are defined by a characteristic, such as
## strength of agreement or disagreement, that can increase in two directions.
## Initially we use the default Blue palette in the sequential_hcl function.
data(AudiencePercent)
likert(AudiencePercent,
auto.key=list(between=1, between.columns=2),
xlab=paste("Percentage of audience younger than 35 (left of zero)",
"and older than 35 (right of zero)"),
main="Target Audience",
col=rev(colorspace::sequential_hcl(4)),
sub="This plot looks better in a 7in x 3.5in window.")
## The really light colors in the previous example are too light.
## Therefore we use the col argument directly. We chose to use an
## intermediate set of Blue colors selected from a longer Blue palette.
likert(AudiencePercent,
positive.order=TRUE,
auto.key=list(between=1, between.columns=2),
xlab=paste("Percentage of audience younger than 35",
"(left of zero) and older than 35 (right of zero)"),
main="Brand A has the most even distribution of ages",
col=colorspace::sequential_hcl(11)[5:2],
scales=list(x=list(at=seq(-90,60,10),
labels=as.vector(rbind("",seq(-80,60,20))))),
sub="This plot looks better in a 7in x 3.5in window.")
# }
# NOT RUN {
# }
# NOT RUN {
## See the ?as.pyramidLikert help page for these examples
## Population Pyramid
data(USAge.table)
USA79 <- USAge.table[75:1, 2:1, "1979"]/1000000
PL <- likert(USA79,
main="Population of United States 1979 (ages 0-74)",
xlab="Count in Millions",
ylab="Age",
scales=list(
y=list(
limits=c(0,77),
at=seq(1,76,5),
labels=seq(0,75,5),
tck=.5))
)
PL
as.pyramidLikert(PL)
likert(USAge.table[75:1, 2:1, c("1939","1959","1979")]/1000000,
main="Population of United States 1939,1959,1979 (ages 0-74)",
sub="Look for the Baby Boom",
xlab="Count in Millions",
ylab="Age",
scales=list(
y=list(
limits=c(0,77),
at=seq(1,76,5),
labels=seq(0,75,5),
tck=.5)),
strip.left=FALSE, strip=TRUE,
layout=c(3,1), between=list(x=.5))
# }
# NOT RUN {
Pop <- rbind(a=c(3,2,4,9), b=c(6,10,12,10))
dimnames(Pop)[[2]] <- c("Very Low", "Low", "High", "Very High")
likert(as.listOfNamedMatrices(Pop),
as.percent=TRUE,
resize.height="rowSums",
strip=FALSE,
strip.left=FALSE,
main=paste("Area and Height are proportional to 'Row Count Totals'.",
"Width is exactly 100%.", sep="\n"))
## Professional Challenges example.
##
## The data for this example is a list of related likert scales, with
## each item in the list consisting of differently named rows. The data
## is from a questionnaire analyzed in a recent Amstat News article.
## The study population was partitioned in several ways. Data from one
## of the partitions (Employment sector) was used in the first example
## in this help file. The examples here show various options for
## displaying all partitions on the same plot.
##
data(ProfChal)
levels(ProfChal$Subtable)[6] <- "Prof Recog" ## reduce length of label
## 1. Plot counts with rows in each panel sorted by positive counts.
##
# }
# NOT RUN {
likert(Question ~ . | Subtable, ProfChal,
positive.order=TRUE,
main="This works, but needs more specified arguments to look good")
likert(Question ~ . | Subtable, ProfChal,
scales=list(y=list(relation="free")), layout=c(1,6),
positive.order=TRUE,
between=list(y=0),
strip=FALSE, strip.left=strip.custom(bg="gray97"),
par.strip.text=list(cex=.6, lines=5),
main="Is your job professionally challenging?",
ylab=NULL,
sub="This looks better in a 10inx7in window")
# }
# NOT RUN {
ProfChalCountsPlot <-
likert(Question ~ . | Subtable, ProfChal,
scales=list(y=list(relation="free")), layout=c(1,6),
positive.order=TRUE,
box.width=unit(.4,"cm"),
between=list(y=0),
strip=FALSE, strip.left=strip.custom(bg="gray97"),
par.strip.text=list(cex=.6, lines=5),
main="Is your job professionally challenging?",
rightAxis=TRUE, ## display Row Count Totals
ylab=NULL,
sub="This looks better in a 10inx7in window")
ProfChalCountsPlot
# }
# NOT RUN {
## 2. Plot percents with rows in each panel sorted by positive percents.
## This is a different sequence than the counts. Row Count Totals are
## displayed on the right axis.
ProfChalPctPlot <-
likert(Question ~ . | Subtable, ProfChal,
as.percent=TRUE, ## implies display Row Count Totals
scales=list(y=list(relation="free")), layout=c(1,6),
positive.order=TRUE,
box.width=unit(.4,"cm"),
between=list(y=0),
strip=FALSE, strip.left=strip.custom(bg="gray97"),
par.strip.text=list(cex=.6, lines=5),
main="Is your job professionally challenging?",
rightAxis=TRUE, ## display Row Count Totals
ylab=NULL,
sub="This looks better in a 10inx7in window")
ProfChalPctPlot
## 3. Putting both percents and counts on the same plot, both in
## the order of the positive percents.
LikertPercentCountColumns(Question ~ . | Subtable, ProfChal,
layout=c(1,6), scales=list(y=list(relation="free")),
ylab=NULL, between=list(y=0),
strip.left=strip.custom(bg="gray97"), strip=FALSE,
par.strip.text=list(cex=.7),
positive.order=TRUE,
main="Is your job professionally challenging?")
## Restore original name
## levels(ProfChal$Subtable)[6] <- "Attitude\ntoward\nProfessional\nRecognition"
# }
# NOT RUN {
# }
# NOT RUN {
## 4. All possible forms of formula for the likert formula method:
data(ProfChal)
row.names(ProfChal) <- abbreviate(ProfChal$Question, 8)
likert( Question ~ . | Subtable,
data=ProfChal, scales=list(y=list(relation="free")), layout=c(1,6))
likert( Question ~
"Strongly Disagree" + Disagree + "No Opinion" + Agree + "Strongly Agree" | Subtable,
data=ProfChal, scales=list(y=list(relation="free")), layout=c(1,6))
likert( Question ~ . ,
data=ProfChal)
likert( Question ~ "Strongly Disagree" + Disagree + "No Opinion" + Agree + "Strongly Agree",
data=ProfChal)
likert( ~ . | Subtable,
data=ProfChal, scales=list(y=list(relation="free")), layout=c(1,6))
likert( ~ "Strongly Disagree" + Disagree + "No Opinion" + Agree + "Strongly Agree" | Subtable,
data=ProfChal, scales=list(y=list(relation="free")), layout=c(1,6))
likert( ~ . ,
data=ProfChal)
likert( ~ "Strongly Disagree" + Disagree + "No Opinion" + Agree + "Strongly Agree",
data=ProfChal)
# }
# NOT RUN {
# }
# NOT RUN {
## 5. putting the x-axis tick labels on top for horizontal plots
## putting the y-axis tick lables on right for vertical plots
##
## This non-standard specification is a consequence of using the right
## axis labels for different values than appear on the left axis labels
## with horizontal plots, and using the top axis labels for different
## values than appear on the bottom axis labels with vertical plots.
## Percent plot calculated automatically from Count data
tmph <-
likert(Question ~ . , ProfChal[ProfChal$Subtable=="Employment sector",],
as.percent=TRUE,
main='Is your job professionally challenging?',
ylab=NULL,
sub="This plot looks better in a 9in x 4in window.")
tmph$x.scales$labels
names(tmph$x.scales$labels) <- tmph$x.scales$labels
update(tmph, scales=list(x=list(alternating=2)), xlab=NULL, xlab.top="Percent")
tmpv <-
likert(Question ~ . , ProfChal[ProfChal$Subtable=="Employment sector",],
as.percent=TRUE,
main='Is your job professionally challenging?',
sub="likert plots with long Question names look better horizontally.
With effort they can be made to look adequate vertically.",
horizontal=FALSE,
scales=list(y=list(alternating=2), x=list(rot=c(90, 0))),
ylab.right="Percent",
ylab=NULL,
xlab.top="Column Count Totals",
par.settings=list(
layout.heights=list(key.axis.padding=5),
layout.widths=list(key.right=1.5, right.padding=0))
)
tmpv$y.scales$labels
names(tmpv$y.scales$labels) <- tmpv$y.scales$labels
tmpv
tmpv$x.limits <- abbreviate(tmpv$x.limits,8)
tmpv$x.scales$rot=c(0, 0)
tmpv
# }
# NOT RUN {
# }
# NOT RUN {
## illustration that a border on the bars is misleading when it splits a bar.
tmp <- data.frame(a=1, b=2, c=3)
likert(~ . , data=tmp, ReferenceZero=2, main="No border. OK.")
likert(~ . , data=tmp, ReferenceZero=2, border="white",
main="Border. Misleading split of central bar.")
likert(~ . , data=tmp, ReferenceZero=2.5, main="No border. OK.")
likert(~ . , data=tmp, ReferenceZero=2.5, border="white", main="Border. OK.")
# }
# NOT RUN {
# }
# NOT RUN {
## run the shiny app
shiny::runApp(system.file("shiny/likert", package="HH"))
# }
# NOT RUN {
## The ProfChal data is done again with explicit use of ResizeEtc
## in ?HH:::ResizeEtc
# }
Run the code above in your browser using DataLab