# one way to extract the breakpoints labs <- levels(cut(aaa, 3 ))Ĭbind(lower = as.numeric ( sub( "\\((.+). #- the same, since no exact INT! # sometimes the default dig.lab is not enough to be avoid confusion: aaa <- c ( 1, 2, 3, 4, 5, 2, 3, 4, 5, 6, 7 )Ĭut(aaa, 3, dig.lab = 4, ordered = TRUE ) # extra digits don't "harm" here table(cut(y, breaks = 1 *(- 3 : 3 ), right = FALSE )) Which( is.na (cx)) x #- the first 9 values 0 which( is.na (cxl)) x #- the last 5 values 8 # Label construction: y <- stats::rnorm( 100 ) On the alignment page, find the box in row A in which the two sets of lines overlap the most, for example, A10. Each box on the page consists of two sets of lines. The printer prints an alignment page with rows of numbered boxes. Table(cxl <- cut(x, breaks = 2 *( 0 : 4 ), right = FALSE )) On the Device Services tab, click Align Cartridges. #- some values OUTSIDE the breaks : table(cx <- cut(x, breaks = 2 *( 0 : 4 ))) Table( cut(x, breaks = 3 *(- 2 : 5 ), right = FALSE )) Sum (table(cut(Z, breaks = - 6 : 6, labels = FALSE ))) Quantile for ways of choosing breaks of roughly equal Split for splitting a variable according to a group factor Other methods are not required to and labels will correspond toĪs from R 3.2.0, getOption("OutDec") is consulted when labelsĪre constructed for labels = NULL. The default method will sort a numeric vector of breaks, but Should be used in formatting the numbers b1, b2, ….Ī larger value (up to 12) will be used if needed to distinguishīetween any pair of endpoints: if this fails labels such as In this case, dig.lab indicates the minimum number of digits Right = TRUE and as "[b1, b2)", … if right = If none is specified, the factor level labels areĬonstructed as "(b1, b2]", "(b2, b3]" etc. If a labels parameter is specified, its values are used to name Is a constant vector, equal-length intervals are created, one of The extreme values both fall within the break intervals. The outer limits are moved away by 0.1% of the range to ensure that When breaks is specified as a single number, the range of theĭata is divided into breaks pieces of equal length, and then Values which fall outside the range of breaks are coded as In the Alignment section of the Format Axis box there's a 'Resize shape to fit. When I resize the box, the chart itself is also resized and the labels are again cut off. The horizontal axis labels have been rotated 90, and are now cut off by the chart box. Results in an integer vector of level codes. I have a routine XY Scatter Chart in Excel 2010. ValueĪ factor is returned, unless labels = FALSE which > table(age.cat(clinical.Further arguments passed to or from other methods. > # now specifying a lower bound AND the "by" argument
> table(age.cat(ial$age, lower = 30, upper = 70)) It uses cut inside of it, but does some preprocessing and uses the labels argument to cut to make the output look nice.Īge.cat # only specifying an upper bound, uses 0 as lower bound, and
It could be any grouping that you want.įinally, I am going to show you an example of a custom R function to categorize ages. There is no reason that the breaks argument has to be equally spaced as I have done above. > # cut the age variable using the seq defined above > # specify break points explicitly using seq function Luckily, we can specify the exact intervals we want for age. Well, the intervals that cut chose by default are not the nicest looking with the age example, although they are fine with the year example, since it was already discrete. > # year.enroll is a factor, so must convert to numeric first! > # basic usage of cut with a numeric variable The default labels use standard mathematical notation for open and closed intervals. This method will cause cut to break up age into 4 intervals. Our first example calls cut with the breaks argument set to a single number. Now, we will use the cut function to make age a factor, which is what R calls a categorical variable.
#CUTTING OFF BOTTON GRAPH R TRIAL#
> # generate data for clinical trial example First, we will simulate some data from a hypothetical clinical trial that includes variables for patient ID, age, and year of enrollment.
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