cut_interval: Discretise numeric data into categorical

Description Usage Arguments Author(s) See Also Examples

View source: R/utilities-break.r

Description

cut_interval makes n groups with equal range, cut_number makes n groups with (approximately) equal numbers of observations; cut_width makes groups of width width.

Usage

1
2
3
4
5
6
cut_interval(x, n = NULL, length = NULL, ...)

cut_number(x, n = NULL, ...)

cut_width(x, width, center = NULL, boundary = NULL, closed = c("right",
  "left"))

Arguments

x

numeric vector

n

number of intervals to create, OR

length

length of each interval

...

other arguments passed on to cut

width

The bin width.

center, boundary

Specify either the position of edge or the center of a bin. Since all bins are aligned, specifying the position of a single bin (which doesn't need to be in the range of the data) affects the location of all bins. If not specified, uses the "tile layers algorithm", and sets the boundary to half of the binwidth.

To center on integers, width = 1 and center = 0. boundary = 0.5.

closed

One of "right" or "left" indicating whether right or left edges of bins are included in the bin.

Author(s)

Randall Prium contributed most of the implementation of cut_width.

See Also

cut_number

Examples

1
2
3
4
5
6
7
8
table(cut_interval(1:100, 10))
table(cut_interval(1:100, 11))

table(cut_number(runif(1000), 10))

table(cut_width(runif(1000), 0.1))
table(cut_width(runif(1000), 0.1, boundary = 0))
table(cut_width(runif(1000), 0.1, center = 0))

Example output

   [1,10.9] (10.9,20.8] (20.8,30.7] (30.7,40.6] (40.6,50.5] (50.5,60.4] 
         10          10          10          10          10          10 
(60.4,70.3] (70.3,80.2] (80.2,90.1]  (90.1,100] 
         10          10          10          10 

  [1,10]  (10,19]  (19,28]  (28,37]  (37,46]  (46,55]  (55,64]  (64,73] 
      10        9        9        9        9        9        9        9 
 (73,82]  (82,91] (91,100] 
       9        9        9 

[0.00196,0.118]   (0.118,0.228]   (0.228,0.311]   (0.311,0.416]   (0.416,0.518] 
            100             100             100             100             100 
  (0.518,0.611]   (0.611,0.697]   (0.697,0.792]     (0.792,0.9]         (0.9,1] 
            100             100             100             100             100 

[-0.05,0.05]  (0.05,0.15]  (0.15,0.25]  (0.25,0.35]  (0.35,0.45]  (0.45,0.55] 
          43          101           87          104          111          100 
 (0.55,0.65]  (0.65,0.75]  (0.75,0.85]  (0.85,0.95]  (0.95,1.05] 
          99           96          101          109           49 

  [0,0.1] (0.1,0.2] (0.2,0.3] (0.3,0.4] (0.4,0.5] (0.5,0.6] (0.6,0.7] (0.7,0.8] 
      108        94       109       114       103       109        85        78 
(0.8,0.9]   (0.9,1] 
       98       102 

[-0.05,0.05]  (0.05,0.15]  (0.15,0.25]  (0.25,0.35]  (0.35,0.45]  (0.45,0.55] 
          57          129          100           95           96          101 
 (0.55,0.65]  (0.65,0.75]  (0.75,0.85]  (0.85,0.95]  (0.95,1.05] 
          86          100           96           98           42 

ggplot2 documentation built on May 30, 2017, 2:36 a.m.