I have a column with distance and I want create a new column distance_class where the distances are grouped under a certain class range. The classes must be steps of 10, so for example: a distance of 8.099716 will be assigned to 10 in the new column. A distance of 12.430613 will be assigned to 20 etc.
Since my data goes up to 498 metres, this require a lot of classes and I know how to do it manually:
df$distance_class <- 10
df[df$distance >= 10.0000001 & df$distance <= 20,]$distance_class <- 20
etc, but this fills a lot of space in my r script. What function could I use to make these classes?
df =
structure(list(HEX_Tag_ID = c("3D6.153413ECBC", "3D6.153413ECE0",
"3D6.153413EF72", "3D6.153413EF72", "3D6.15341B9871", "3D6.15341B9B1D",
"3D6.15341B9B36", "3D6.15341BA2E5", "3D6.15341BA3BA", "3D6.15341BA4AA",
"3D6.15341BAACC", "3D6.15341BAD53", "3D6.15341BADE3", "3D6.15341BAE18",
"3D6.15341BAE4D", "3D6.15341BB40B", "3D6.15341BB46B", "3D6.15341BB664",
"3D6.15341BBB4F", "3D6.15341BBCBC", "3D6.15341BBFB5", "3D6.15341BBFEF",
"3D6.15341BC0A1", "3D6.15341BC0FB", "3D6.15341BC232", "3D6.15341BC301",
"3D6.15341BC475", "3D6.15341BC60F", "3D6.15341BC9D8", "3D6.15341BCB9A",
"3D6.15341BCBFE", "3D6.15341BCF0C", "3D6.15341BCF0C", "3D6.15341BCF8A",
"3D6.15341BD0D4", "3D6.15341BD291", "3D6.15341BD531", "3D6.15341BD71B",
"3D6.15341BDE9F", "3D6.15341BDF75", "3D6.15341BE2C4", "3D6.15341BE5B6",
"3D6.15341BE8C3", "3D6.15341BEBB7", "3D6.15341BF00C", "3D6.15341BF0EF",
"3D6.15341BF1FD", "3D6.15341BF4E3", "3D6.15341BF6C8", "3D6.15341BF8F1",
"3D6.15341BF949", "3D6.15341BFA21", "3D6.15341BFBF2", "3D6.15341BFE8F",
"3D6.15341BFF55", "3D6.15341BFFF8", "3D6.15341C0083", "3D6.15343A5AF3",
"3D6.15343A5B9A", "3D6.15343A5DB5", "3D6.15343A5F31", "3D6.15343A6078",
"3D6.15343A6589", "3D6.15343A658F", "3D6.15343A66A8", "3D6.15343A66CA",
"3D6.15343A677A", "3D6.15343A67C9", "3D6.15343A6824", "3D6.15343A6829",
"3D6.15343A6847", "3D6.15343A6848", "3D6.15343A688B", "3D6.15343A6AFB",
"3D6.15343A6E01", "3D6.15343A6E12", "3D6.15343A6E56", "3D6.15343A6F23",
"3D6.15343A71A8", "3D6.15343A71B0", "3D6.15343A71B6", "3D6.15343A71BF",
"3D6.15343A71C3", "3D6.15343A71D0", "3D6.15343A71E0", "3D6.15343A7548",
"3D6.15343A757C", "3D6.15343A75A6", "3D6.15343A75BB", "3D6.15343A766B",
"3D6.15343A7736", "3D6.15343A773B", "3D6.15343A7CC8", "3D6.15343A7CF5",
"3D6.15343A7DD8", "3D6.15343A8073", "3D6.15343A8317", "3D6.15343A831D",
"3D6.15343A832E", "3D6.15343A980B"), Lengteklasse = structure(c(4L,
5L, 5L, 5L, 5L, 5L, 4L, 2L, 3L, 3L, 4L, 5L, 4L, 6L, 7L, 6L, 5L,
6L, 4L, 6L, 7L, 2L, 5L, 7L, 3L, 5L, 3L, 6L, 5L, 6L, 6L, 5L, 5L,
6L, 6L, 4L, 3L, 5L, 6L, 4L, 5L, 6L, 5L, 4L, 4L, 5L, 5L, 5L, 6L,
5L, 2L, 5L, 4L, 4L, 6L, 3L, 5L, 4L, 4L, 6L, 3L, 4L, 5L, 4L, 4L,
3L, 5L, 5L, 4L, 3L, 4L, 6L, 5L, 5L, 5L, 3L, 1L, 3L, 5L, 4L, 7L,
4L, 6L, 2L, 2L, 5L, 7L, 4L, 5L, 5L, 3L, 3L, 6L, 5L, 5L, 6L, 5L,
2L, 4L, 6L), .Label = c("6", "7", "8", "9", "10", "11", "12",
"13"), class = "factor"), distance = c(8.0997162289136, 12.4306131164191,
61.3106411610124, 58.5153016042213, 32.2744999859089, 89.414358823574,
28.0108486925122, 47.8219099537216, 9.0620201326797, 42.44256852726,
78.890670989817, 14.4029581051937, 30.9625482306174, 16.8654943464726,
46.9868070888032, 50.0744747268464, 28.0727803370875, 90.1657178100163,
105.883889293255, 64.6258993837158, 13.7303841199513, 5.30383607472221,
23.4063386162898, 101.846842420048, 110.743855606155, 93.7033487614962,
54.2208290023929, 284.353952212319, 5.80214621411396, 9.00695055301609,
141.475231499517, 17.0048805782567, 28.0458481248819, 154.038498446018,
37.725475052369, 139.446207060833, 51.1696402910276, 15.5079590734332,
57.4006455173585, 11.100902574906, 241.023087647416, 17.8158585698874,
128.095902669084, 30.3714003058918, 110.477320018898, 31.4974206462646,
9.00695055301609, 82.0444687609409, 19.9640782122363, 98.4831535433995,
10.1485490181753, 10.1198911075185, 60.0673937023095, 61.30855893794,
15.243456492333, 7.19527826709304, 5.89430300905792, 14.6110248650041,
16.0826976446818, 12.4654874602058, 117.743722916799, 1.12489917618149,
39.2696515885893, 10.3075837820188, 12.1762671570106, 11.7501210701527,
4.87143478511475, 40.5667469824971, 202.73045988395, 10.1705562580906,
170.793444639309, 447.235720974034, 8.27263671180456, 10.5997730205872,
13.3275431540535, 39.1729038623626, 6.43559510500503, 61.94224987052,
85.8550416470563, 5.55746379097464, 60.054459598035, 15.9423052029938,
16.0655921713406, 125.621317253718, 30.4341885798698, 19.6787135744613,
21.9526432324342, 32.6115161846427, 23.0584552162136, 15.7035854165388,
32.0891313247117, 356.071825968971, 21.5282811844687, 49.3123085255221,
22.9122313204, 62.5149283380102, 9.05272361429296, 74.9756897608931,
19.1320807799778, 39.1088642338198)), class = c("grouped_df",
"tbl_df", "tbl", "data.frame"), row.names = c(NA, -100L), groups = structure(list(
HEX_Tag_ID = c("3D6.153413ECBC", "3D6.153413ECE0", "3D6.153413EF72",
"3D6.15341B9871", "3D6.15341B9B1D", "3D6.15341B9B36", "3D6.15341BA2E5",
"3D6.15341BA3BA", "3D6.15341BA4AA", "3D6.15341BAACC", "3D6.15341BAD53",
"3D6.15341BADE3", "3D6.15341BAE18", "3D6.15341BAE4D", "3D6.15341BB40B",
"3D6.15341BB46B", "3D6.15341BB664", "3D6.15341BBB4F", "3D6.15341BBCBC",
"3D6.15341BBFB5", "3D6.15341BBFEF", "3D6.15341BC0A1", "3D6.15341BC0FB",
"3D6.15341BC232", "3D6.15341BC301", "3D6.15341BC475", "3D6.15341BC60F",
"3D6.15341BC9D8", "3D6.15341BCB9A", "3D6.15341BCBFE", "3D6.15341BCF0C",
"3D6.15341BCF8A", "3D6.15341BD0D4", "3D6.15341BD291", "3D6.15341BD531",
"3D6.15341BD71B", "3D6.15341BDE9F", "3D6.15341BDF75", "3D6.15341BE2C4",
"3D6.15341BE5B6", "3D6.15341BE8C3", "3D6.15341BEBB7", "3D6.15341BF00C",
"3D6.15341BF0EF", "3D6.15341BF1FD", "3D6.15341BF4E3", "3D6.15341BF6C8",
"3D6.15341BF8F1", "3D6.15341BF949", "3D6.15341BFA21", "3D6.15341BFBF2",
"3D6.15341BFE8F", "3D6.15341BFF55", "3D6.15341BFFF8", "3D6.15341C0083",
"3D6.15343A5AF3", "3D6.15343A5B9A", "3D6.15343A5DB5", "3D6.15343A5F31",
"3D6.15343A6078", "3D6.15343A6589", "3D6.15343A658F", "3D6.15343A66A8",
"3D6.15343A66CA", "3D6.15343A677A", "3D6.15343A67C9", "3D6.15343A6824",
"3D6.15343A6829", "3D6.15343A6847", "3D6.15343A6848", "3D6.15343A688B",
"3D6.15343A6AFB", "3D6.15343A6E01", "3D6.15343A6E12", "3D6.15343A6E56",
"3D6.15343A6F23", "3D6.15343A71A8", "3D6.15343A71B0", "3D6.15343A71B6",
"3D6.15343A71BF", "3D6.15343A71C3", "3D6.15343A71D0", "3D6.15343A71E0",
"3D6.15343A7548", "3D6.15343A757C", "3D6.15343A75A6", "3D6.15343A75BB",
"3D6.15343A766B", "3D6.15343A7736", "3D6.15343A773B", "3D6.15343A7CC8",
"3D6.15343A7CF5", "3D6.15343A7DD8", "3D6.15343A8073", "3D6.15343A8317",
"3D6.15343A831D", "3D6.15343A832E", "3D6.15343A980B"), .rows = structure(list(
1L, 2L, 3:4, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L,
14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L,
25L, 26L, 27L, 28L, 29L, 30L, 31L, 32:33, 34L, 35L, 36L,
37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L,
48L, 49L, 50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L,
59L, 60L, 61L, 62L, 63L, 64L, 65L, 66L, 67L, 68L, 69L,
70L, 71L, 72L, 73L, 74L, 75L, 76L, 77L, 78L, 79L, 80L,
81L, 82L, 83L, 84L, 85L, 86L, 87L, 88L, 89L, 90L, 91L,
92L, 93L, 94L, 95L, 96L, 97L, 98L, 99L, 100L), ptype = integer(0), class = c("vctrs_list_of",
"vctrs_vctr", "list"))), class = c("tbl_df", "tbl", "data.frame"
), row.names = c(NA, -98L), .drop = TRUE))
CodePudding user response：
You can use plyr::round_any function:
library(dplyr)
df |>
mutate(distance_class = plyr::round_any(distance,10, f = ceiling))
Output:
HEX_Tag_ID Lengteklasse distance distance_class
<chr> <fct> <dbl> <dbl>
1 3D6.153413ECBC 9 8.10 10
2 3D6.153413ECE0 10 12.4 20
3 3D6.153413EF72 10 61.3 70
4 3D6.153413EF72 10 58.5 60
5 3D6.15341B9871 10 32.3 40
6 3D6.15341B9B1D 10 89.4 90
7 3D6.15341B9B36 9 28.0 30
8 3D6.15341BA2E5 7 47.8 50
9 3D6.15341BA3BA 8 9.06 10
10 3D6.15341BA4AA 8 42.4 50