在 R 中按行号添加分组列
[英]Add a grouping column by row number in R
问题描述
I have time series data:
我有时间序列数据：
mytime <- seq.Date(as.Date("2015-01-01"), as.Date("2022-01-01"), "day")
value <- rnorm(n = length(mytime))
df <- cbind.data.frame(mytime, value)
I want to create a new column which starts with 1 and increases by 1 for every fixed number of rows.我想创建一个以 1 开头的新列，每固定行数增加 1。 For example, the first 100 rows get a value of 1, the next 100 rows get a value of 2, and so on.例如，前 100 行的值为 1，接下来的 100 行的值为 2，依此类推。
2 个解决方案
解决方案1
3 2022-09-05 09:52:50
This should work:这应该有效：
library(tidyverse)
mytime <- seq.Date(as.Date("2015-01-01"), as.Date("2022-01-01"), "day")
value <- rnorm(n = length(mytime))
df <- cbind.data.frame(mytime, value)
df %>%
mutate(grouping = rep(c(1:100), each = 100)[1:length(value)])
#> mytime value grouping
#> 1 2015-01-01 0.8188726406 1
#> 2 2015-01-02 -0.7051437552 1
#> 3 2015-01-03 -0.4052449198 1
#> 4 2015-01-04 0.1069765445 1
#> 5 2015-01-05 -1.7624077376 1
#> 6 2015-01-06 -1.3541046081 1
#> 7 2015-01-07 -1.5836060959 1
#> 8 2015-01-08 1.6975299938 1
#> 9 2015-01-09 0.1365021842 1
#> 10 2015-01-10 1.3583782190 1
#> 11 2015-01-11 0.4389094423 1
#> 12 2015-01-12 -1.2695437977 1
#> 13 2015-01-13 -0.0185099335 1
#> 14 2015-01-14 -1.2504712388 1
#> 15 2015-01-15 0.4999558250 1
#> 16 2015-01-16 0.7138838410 1
#> 17 2015-01-17 -1.7709035964 1
#> 18 2015-01-18 -0.6555022760 1
#> 19 2015-01-19 0.2771728385 1
#> 20 2015-01-20 -0.2647472076 1
#> 21 2015-01-21 -0.1846148670 1
#> 22 2015-01-22 -1.7964703879 1
#> 23 2015-01-23 1.0119717818 1
#> 24 2015-01-24 -1.4243738227 1
#> 25 2015-01-25 -1.2956929904 1
#> 26 2015-01-26 -0.6236723296 1
#> 27 2015-01-27 -0.4082983500 1
#> 28 2015-01-28 2.3180442246 1
#> 29 2015-01-29 -0.3830073587 1
#> 30 2015-01-30 1.7191377387 1
#> 31 2015-01-31 1.8575794944 1
#> 32 2015-02-01 -2.1582163873 1
#> 33 2015-02-02 1.7012159685 1
#> 34 2015-02-03 -1.1991523660 1
#> 35 2015-02-04 0.9475081079 1
#> 36 2015-02-05 0.1152464165 1
#> 37 2015-02-06 -2.6407434397 1
#> 38 2015-02-07 1.3821892807 1
#> 39 2015-02-08 0.8054893231 1
#> 40 2015-02-09 0.9223800849 1
#> 41 2015-02-10 -0.3546256458 1
#> 42 2015-02-11 0.6478162596 1
#> 43 2015-02-12 -0.7505130565 1
#> 44 2015-02-13 -2.0366870996 1
#> 45 2015-02-14 1.0649788649 1
#> 46 2015-02-15 -0.9217779191 1
#> 47 2015-02-16 -0.3045693249 1
#> 48 2015-02-17 0.0518172566 1
#> 49 2015-02-18 0.0532814044 1
#> 50 2015-02-19 0.1876367083 1
#> 51 2015-02-20 0.3327661457 1
#> 52 2015-02-21 -0.2952679556 1
#> 53 2015-02-22 0.3293960050 1
#> 54 2015-02-23 1.2409077698 1
#> 55 2015-02-24 0.3580355273 1
#> 56 2015-02-25 -1.4924835886 1
#> 57 2015-02-26 0.7058099312 1
#> 58 2015-02-27 0.2104966444 1
#> 59 2015-02-28 -0.3057447517 1
#> 60 2015-03-01 1.5756875721 1
#> 61 2015-03-02 -0.1917941771 1
#> 62 2015-03-03 0.5913340531 1
#> 63 2015-03-04 -0.5700276892 1
#> 64 2015-03-05 1.0740621827 1
#> 65 2015-03-06 -1.2117093430 1
#> 66 2015-03-07 1.1110831399 1
#> 67 2015-03-08 -0.4552585955 1
#> 68 2015-03-09 -0.8588412294 1
#> 69 2015-03-10 1.9932422428 1
#> 70 2015-03-11 -1.7018407616 1
#> 71 2015-03-12 -0.0308941351 1
#> 72 2015-03-13 0.5055698207 1
#> 73 2015-03-14 0.4188607070 1
#> 74 2015-03-15 0.7982967262 1
#> 75 2015-03-16 -2.2995915989 1
#> 76 2015-03-17 -0.5689886197 1
#> 77 2015-03-18 -0.7878760699 1
#> 78 2015-03-19 1.9519211037 1
#> 79 2015-03-20 0.9026785904 1
#> 80 2015-03-21 1.3952120899 1
#> 81 2015-03-22 -0.6474826181 1
#> 82 2015-03-23 0.8958113474 1
#> 83 2015-03-24 -1.2238473311 1
#> 84 2015-03-25 0.4058042441 1
#> 85 2015-03-26 -0.5709496280 1
#> 86 2015-03-27 -0.4189819537 1
#> 87 2015-03-28 -0.3253399775 1
#> 88 2015-03-29 -0.2504487158 1
#> 89 2015-03-30 -0.5048374234 1
#> 90 2015-03-31 0.2755789912 1
#> 91 2015-04-01 0.8922287071 1
#> 92 2015-04-02 1.1172195419 1
#> 93 2015-04-03 -1.6022222969 1
#> 94 2015-04-04 -0.2639181444 1
#> 95 2015-04-05 -1.0666771455 1
#> 96 2015-04-06 0.5772296824 1
#> 97 2015-04-07 0.3058956784 1
#> 98 2015-04-08 0.3958394775 1
#> 99 2015-04-09 0.4086626441 1
#> 100 2015-04-10 0.5702892942 1
#> 101 2015-04-11 -0.3305672962 2
#> 102 2015-04-12 1.1116674141 2
#> 103 2015-04-13 -0.3013942049 2
#> 104 2015-04-14 -0.5810105837 2
#> 105 2015-04-15 0.5907661366 2
#> 106 2015-04-16 -0.0033270315 2
#> 107 2015-04-17 -0.5018928764 2
#> 108 2015-04-18 -0.7306115691 2
#> 109 2015-04-19 0.8195806083 2
#> 110 2015-04-20 0.1874579340 2
#> 111 2015-04-21 0.2209803536 2
#> 112 2015-04-22 -1.3126491196 2
#> 113 2015-04-23 0.3083904082 2
#> 114 2015-04-24 0.7918114136 2
#> 115 2015-04-25 -0.6279447046 2
#> 116 2015-04-26 0.1982677395 2
#> 117 2015-04-27 0.1015474687 2
#> 118 2015-04-28 -0.9389828948 2
#> 119 2015-04-29 -0.3207971613 2
#> 120 2015-04-30 1.0007723074 2
#> 121 2015-05-01 0.3239017453 2
#> 122 2015-05-02 -1.2809204214 2
#> 123 2015-05-03 -0.5277261595 2
#> 124 2015-05-04 0.7688500927 2
#> 125 2015-05-05 1.0318535818 2
#> 126 2015-05-06 1.4980233862 2
#> 127 2015-05-07 -0.7881506596 2
#> 128 2015-05-08 -0.0463271920 2
#> 129 2015-05-09 2.0093012251 2
#> 130 2015-05-10 -0.9134628460 2
#> 131 2015-05-11 -2.3400047323 2
#> 132 2015-05-12 -1.1726139699 2
#> 133 2015-05-13 0.7844263225 2
#> 134 2015-05-14 1.3506619127 2
#> 135 2015-05-15 -2.5540631175 2
#> 136 2015-05-16 0.6912525372 2
#> 137 2015-05-17 0.7538481654 2
....
Created on 2022-09-05 with reprex v2.0.2使用reprex v2.0.2创建于 2022-09-05
解决方案2
2 已采纳 2022-09-05 10:53:54
We could also utilize the row_number() :我们也可以使用row_number() ：
library(dplyr)
df |>
mutate(grouping = ceiling(row_number()/100))
Output: Output：
mytime value grouping
1 2015-01-01 0.143792098 1
2 2015-01-02 -1.401455624 1
3 2015-01-03 -1.858456039 1
4 2015-01-04 1.187416005 1
5 2015-01-05 1.379141495 1
6 2015-01-06 -0.675080153 1
7 2015-01-07 0.320909205 1
8 2015-01-08 1.852616919 1
9 2015-01-09 -0.846052547 1
10 2015-01-10 -0.658311621 1
11 2015-01-11 0.222296116 1
12 2015-01-12 -0.543392482 1
13 2015-01-13 -0.755015488 1
14 2015-01-14 -0.178678382 1
15 2015-01-15 1.110967146 1
16 2015-01-16 -1.275580679 1
17 2015-01-17 -0.010064079 1
18 2015-01-18 -2.170296324 1
19 2015-01-19 1.250837273 1
20 2015-01-20 -1.209153067 1
21 2015-01-21 -0.550676735 1
22 2015-01-22 0.952916907 1
23 2015-01-23 0.277654831 1
24 2015-01-24 0.042829946 1
25 2015-01-25 -0.240098180 1
26 2015-01-26 -0.746263380 1
27 2015-01-27 -0.284752154 1
28 2015-01-28 0.346689091 1
29 2015-01-29 -0.666216586 1
30 2015-01-30 -0.640442501 1
31 2015-01-31 -0.244509760 1
32 2015-02-01 -2.075441987 1
33 2015-02-02 0.147406620 1
34 2015-02-03 0.363748658 1
35 2015-02-04 0.134561515 1
36 2015-02-05 -0.391123031 1
37 2015-02-06 -0.170565332 1
38 2015-02-07 0.183892659 1
39 2015-02-08 -0.854721228 1
40 2015-02-09 1.278300433 1
41 2015-02-10 -1.421003730 1
42 2015-02-11 0.913688901 1
43 2015-02-12 -0.877178883 1
44 2015-02-13 0.467617692 1
45 2015-02-14 -1.903758723 1
46 2015-02-15 -0.525691357 1
47 2015-02-16 -0.324291219 1
48 2015-02-17 -0.001652138 1
49 2015-02-18 -1.451039958 1
50 2015-02-19 -0.143701884 1
51 2015-02-20 0.921537907 1
52 2015-02-21 0.307838066 1
53 2015-02-22 1.251906011 1
54 2015-02-23 -1.824026442 1
55 2015-02-24 -1.883911514 1
56 2015-02-25 0.465843894 1
57 2015-02-26 0.087336821 1
58 2015-02-27 -0.257907284 1
59 2015-02-28 -1.215340438 1
60 2015-03-01 -0.737590344 1
61 2015-03-02 -1.152280630 1
62 2015-03-03 0.445959871 1
63 2015-03-04 0.412874111 1
64 2015-03-05 0.912774140 1
65 2015-03-06 -0.753539221 1
66 2015-03-07 -0.247727125 1
67 2015-03-08 1.248229876 1
68 2015-03-09 -0.857405365 1
69 2015-03-10 -2.062565968 1
70 2015-03-11 0.906372397 1
71 2015-03-12 1.770847797 1
72 2015-03-13 -1.194959910 1
73 2015-03-14 0.705680544 1
74 2015-03-15 0.608626405 1
75 2015-03-16 0.483917761 1
76 2015-03-17 0.486972548 1
77 2015-03-18 0.167493580 1
78 2015-03-19 1.007013432 1
79 2015-03-20 1.540288238 1
80 2015-03-21 -0.082749960 1
81 2015-03-22 0.267562341 1
82 2015-03-23 0.334862334 1
83 2015-03-24 0.678018653 1
84 2015-03-25 0.816515100 1
85 2015-03-26 1.059476108 1
86 2015-03-27 0.622612181 1
87 2015-03-28 0.851457454 1
88 2015-03-29 1.044443068 1
89 2015-03-30 -0.601267237 1
90 2015-03-31 0.569441548 1
91 2015-04-01 1.592983829 1
92 2015-04-02 1.283704270 1
93 2015-04-03 0.200713538 1
94 2015-04-04 0.902635425 1
95 2015-04-05 0.542227464 1
96 2015-04-06 -0.329488879 1
97 2015-04-07 0.040194473 1
98 2015-04-08 -0.863276688 1
99 2015-04-09 -0.830596568 1
100 2015-04-10 -0.666276306 1
101 2015-04-11 0.738113129 2
102 2015-04-12 -1.152088593 2
103 2015-04-13 0.309580066 2
104 2015-04-14 0.639723004 2
105 2015-04-15 0.926298625 2
106 2015-04-16 -1.044929798 2
107 2015-04-17 -1.088962011 2
108 2015-04-18 0.137856131 2
109 2015-04-19 0.846136781 2
110 2015-04-20 0.372345665 2
111 2015-04-21 3.400435187 2
112 2015-04-22 -2.026547096 2
113 2015-04-23 -0.106970853 2
114 2015-04-24 -1.226614624 2
115 2015-04-25 0.918546253 2
116 2015-04-26 0.027024114 2
117 2015-04-27 -2.127191506 2
118 2015-04-28 -1.600815099 2
119 2015-04-29 0.749681304 2
120 2015-04-30 0.721914459 2
121 2015-05-01 -0.338230147 2
122 2015-05-02 0.913592837 2
123 2015-05-03 0.587794938 2
124 2015-05-04 -0.851625256 2
125 2015-05-05 -0.345100249 2
126 2015-05-06 1.195675453 2
127 2015-05-07 -1.163156366 2
128 2015-05-08 0.006734588 2
129 2015-05-09 1.410087674 2
130 2015-05-10 1.322741860 2
131 2015-05-11 -0.297038999 2
132 2015-05-12 -0.197173515 2
133 2015-05-13 0.224360972 2
134 2015-05-14 0.516641666 2
135 2015-05-15 -0.779288529 2
136 2015-05-16 0.579790369 2
137 2015-05-17 -1.455354422 2
138 2015-05-18 0.080913482 2
139 2015-05-19 -0.144821155 2
140 2015-05-20 -0.114079060 2
141 2015-05-21 -0.763828057 2
142 2015-05-22 0.707339053 2
143 2015-05-23 0.647765433 2
144 2015-05-24 -1.490961303 2
145 2015-05-25 0.620563653 2
146 2015-05-26 -0.543335407 2
147 2015-05-27 0.104817520 2
148 2015-05-28 -0.003077069 2
149 2015-05-29 0.703242269 2
150 2015-05-30 -0.432612310 2
151 2015-05-31 0.765172967 2
152 2015-06-01 0.662351120 2
153 2015-06-02 0.320601441 2
154 2015-06-03 -1.542552690 2
155 2015-06-04 -0.841613323 2
156 2015-06-05 0.244023691 2
157 2015-06-06 -0.363205416 2
158 2015-06-07 0.425083853 2
159 2015-06-08 0.480960952 2
160 2015-06-09 1.171789654 2
161 2015-06-10 0.689310253 2
162 2015-06-11 0.069911244 2
163 2015-06-12 1.211315304 2
164 2015-06-13 -2.992856256 2
165 2015-06-14 -1.725439305 2
166 2015-06-15 -0.427232751 2
167 2015-06-16 -0.320677428 2
168 2015-06-17 -0.625616224 2
169 2015-06-18 0.436684268 2
170 2015-06-19 -0.051345979 2
171 2015-06-20 -0.005905043 2
172 2015-06-21 -0.650648380 2
173 2015-06-22 0.104280158 2
174 2015-06-23 0.692602024 2
175 2015-06-24 -0.284524585 2
176 2015-06-25 0.114234704 2
177 2015-06-26 -0.307465039 2
178 2015-06-27 -0.868424089 2
179 2015-06-28 -0.008077344 2
180 2015-06-29 -0.216263894 2
181 2015-06-30 0.716286098 2
182 2015-07-01 -0.246694377 2
183 2015-07-02 -0.514709162 2
184 2015-07-03 0.571000411 2
185 2015-07-04 0.951861313 2
186 2015-07-05 -0.657196354 2
187 2015-07-06 0.702772460 2
188 2015-07-07 -1.889945487 2
189 2015-07-08 -1.556305726 2
190 2015-07-09 -1.333879020 2
191 2015-07-10 -0.148308307 2
192 2015-07-11 0.862758957 2
193 2015-07-12 0.015712677 2
194 2015-07-13 -0.518988630 2
195 2015-07-14 0.381518862 2
196 2015-07-15 -0.920415442 2
197 2015-07-16 -0.291423016 2
198 2015-07-17 0.051580366 2
199 2015-07-18 -0.653667887 2
200 2015-07-19 -1.159563927 2
201 2015-07-20 -0.524343555 3
202 2015-07-21 -0.499934439 3
203 2015-07-22 0.890589850 3
204 2015-07-23 -0.583243838 3
205 2015-07-24 0.464586806 3
206 2015-07-25 -1.072116565 3
207 2015-07-26 -1.995098501 3
208 2015-07-27 -1.398424995 3
209 2015-07-28 -0.047756678 3
210 2015-07-29 0.993838354 3
211 2015-07-30 0.274223295 3
212 2015-07-31 -1.274376302 3
213 2015-08-01 -1.586586701 3
214 2015-08-02 0.230695873 3
215 2015-08-03 0.151248025 3
216 2015-08-04 1.631408895 3
217 2015-08-05 -0.878848837 3
218 2015-08-06 0.451727327 3
219 2015-08-07 0.392156218 3
220 2015-08-08 0.544240403 3
221 2015-08-09 -0.211142978 3
222 2015-08-10 1.364874158 3
223 2015-08-11 -0.541504849 3
224 2015-08-12 -0.089349427 3
225 2015-08-13 -0.815008782 3
226 2015-08-14 -0.121764644 3
227 2015-08-15 -1.741367522 3
228 2015-08-16 2.043085589 3
229 2015-08-17 1.051024717 3
230 2015-08-18 0.071467837 3
231 2015-08-19 0.346026920 3
232 2015-08-20 0.190915132 3
233 2015-08-21 -1.104888803 3
234 2015-08-22 -0.193678833 3
235 2015-08-23 0.453708267 3
236 2015-08-24 -0.114886984 3
237 2015-08-25 0.279705350 3
238 2015-08-26 -0.291677485 3
239 2015-08-27 -1.046920131 3
240 2015-08-28 0.546206788 3
241 2015-08-29 0.417895255 3
242 2015-08-30 0.607427357 3
243 2015-08-31 0.386263173 3
244 2015-09-01 1.693325483 3
245 2015-09-02 -0.269513707 3
246 2015-09-03 0.972799720 3
247 2015-09-04 -0.136891511 3
248 2015-09-05 0.036534446 3
249 2015-09-06 -0.818723816 3
250 2015-09-07 -0.270747970 3
251 2015-09-08 -0.099214990 3
252 2015-09-09 -0.441796094 3
253 2015-09-10 -0.785450099 3
254 2015-09-11 -0.266662717 3
255 2015-09-12 -0.185548366 3
256 2015-09-13 -0.587839058 3
257 2015-09-14 0.570935157 3
258 2015-09-15 0.339546529 3
259 2015-09-16 0.436241922 3
260 2015-09-17 -1.345637228 3
261 2015-09-18 0.265399285 3
262 2015-09-19 -0.490105412 3
263 2015-09-20 0.497014587 3
264 2015-09-21 -0.073881747 3
265 2015-09-22 -1.339337587 3
266 2015-09-23 -1.575732554 3
267 2015-09-24 1.590806011 3
268 2015-09-25 0.283380826 3
269 2015-09-26 -0.437666267 3
270 2015-09-27 0.086035992 3
271 2015-09-28 -0.205143330 3
272 2015-09-29 -0.368002399 3
273 2015-09-30 0.277060950 3
274 2015-10-01 1.184281033 3
275 2015-10-02 -0.042580777 3
276 2015-10-03 -0.034058572 3
277 2015-10-04 1.822264836 3
278 2015-10-05 1.418461585 3
279 2015-10-06 -1.663314285 3
280 2015-10-07 0.306396419 3
281 2015-10-08 -0.133955098 3
282 2015-10-09 1.785256820 3
283 2015-10-10 2.144114886 3
284 2015-10-11 1.946704788 3
285 2015-10-12 1.081968268 3
286 2015-10-13 0.466607356 3
287 2015-10-14 0.708654794 3
288 2015-10-15 0.250716353 3
289 2015-10-16 0.280578762 3
290 2015-10-17 -0.102182693 3
291 2015-10-18 1.519061748 3
292 2015-10-19 -0.240985742 3
293 2015-10-20 -1.392785238 3
294 2015-10-21 -1.213613515 3
295 2015-10-22 0.241381597 3
296 2015-10-23 -0.234988013 3
297 2015-10-24 1.620456160 3
298 2015-10-25 0.548044651 3
299 2015-10-26 1.520948096 3
300 2015-10-27 -1.069683544 3
301 2015-10-28 -2.149756515 4
302 2015-10-29 -0.371598782 4
303 2015-10-30 -0.017200805 4
304 2015-10-31 1.421065588 4
305 2015-11-01 -0.719738038 4
306 2015-11-02 -0.539361753 4
307 2015-11-03 0.127735424 4
308 2015-11-04 0.521494673 4
309 2015-11-05 -1.071468633 4
310 2015-11-06 0.311667225 4
311 2015-11-07 0.593034587 4
312 2015-11-08 -0.281065031 4
313 2015-11-09 -0.454378772 4
314 2015-11-10 -0.612201420 4
315 2015-11-11 1.261906072 4
316 2015-11-12 -0.832989599 4
317 2015-11-13 1.042128138 4
318 2015-11-14 0.101058897 4
319 2015-11-15 1.481095345 4
320 2015-11-16 0.550768802 4
321 2015-11-17 0.709517939 4
322 2015-11-18 1.403988053 4
323 2015-11-19 0.050966805 4
324 2015-11-20 -0.663606215 4
325 2015-11-21 -0.120978945 4
326 2015-11-22 0.830822407 4
327 2015-11-23 -0.846003819 4
328 2015-11-24 1.460456262 4
329 2015-11-25 0.758233907 4
330 2015-11-26 0.241672077 4
331 2015-11-27 0.461815643 4
332 2015-11-28 0.086404903 4
333 2015-11-29 -1.345535596 4
声明:本站的技术帖子网页，遵循CC BY-SA 4.0协议，如果您需要转载，请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.
相关问题
如何在 R 的列中添加第一个数字 - How to add first number in row in a column in R
如何将每行中值> 0的列添加到R中的表中？ - How to add a column giving the number of values >0 in each row to a table in R?
R：添加列与当前行的x出现次数是多少 - R: Add column with what number of appearance of x the current row is
如何根据行号在 R 中添加“组”列 - How to add a “group” column in R based on the row number
将数字索引添加到 R 中另一列中的每个唯一值的行中 - Add number index into a row for each unique value in anoter column in R
根据 R 中的字幕分组添加数据框列 - add a dataframe column based on grouping by subtitles in R
按 r 中的数字序列分组 - grouping by number sequences in r
根据连续的 TRUE/FALSE 列值添加分组号 - add grouping number based on consecutive TRUE/FALSE column values
按R中的一列分组 - grouping by one column in R
在 R 中对数据列进行分组 - Grouping a Data Column in R
相关标签