I need to remove rows in this dataset until there is no TRUE within FALSE or vice-versa or in order words the all subsequent rows are the same (yes, except the boundary). The number of row deletions should be the lowest possible.
For example, by deleting rows which counter == 9 in the dataset below, more consecutive rows with TRUE value will be formed. I want the loop to identify the lowest frequency value in counter and remove these rows progressively, until there is no FALSE within TRUE and vice-versa. We also could remove all rows which counter == 4, 5, and 6 because they also occur only twice. Note that after these rows are removed, larger "blocks" or "chunks" of TRUEs and FALSEs are formed, which should be accounted for future deletions.
Here is the dataset:
inter counter
189 FALSE 1
192 FALSE 1
233 FALSE 1
235 FALSE 1
237 FALSE 1
238 FALSE 1
249 FALSE 1
256 FALSE 1
258 FALSE 1
259 FALSE 1
14 FALSE 1
17 FALSE 1
36 FALSE 1
39 FALSE 1
82 FALSE 1
114 FALSE 1
117 FALSE 1
136 FALSE 1
152 FALSE 1
194 FALSE 1
212 FALSE 1
215 FALSE 1
251 FALSE 1
262 FALSE 1
267 FALSE 1
268 FALSE 1
57 TRUE 2
60 TRUE 2
96 TRUE 2
99 TRUE 2
232 TRUE 2
239 TRUE 2
242 TRUE 2
260 TRUE 2
19 FALSE 3
41 FALSE 3
119 FALSE 3
217 FALSE 3
62 TRUE 4
101 TRUE 4
181 FALSE 5
206 FALSE 5
244 TRUE 6
269 TRUE 6
176 FALSE 7
179 FALSE 7
201 FALSE 7
204 FALSE 7
157 FALSE 7
159 FALSE 7
72 TRUE 8
74 TRUE 8
126 TRUE 8
128 TRUE 8
142 TRUE 8
144 TRUE 8
172 TRUE 8
178 TRUE 8
180 TRUE 8
182 TRUE 8
183 TRUE 8
186 TRUE 8
203 TRUE 8
205 TRUE 8
207 TRUE 8
208 TRUE 8
175 FALSE 9
200 FALSE 9
9 TRUE 10
11 TRUE 10
31 TRUE 10
33 TRUE 10
109 TRUE 10
111 TRUE 10
174 TRUE 10
199 TRUE 10
52 TRUE 10
54 TRUE 10
91 TRUE 10
93 TRUE 10
177 TRUE 10
184 TRUE 10
202 TRUE 10
209 TRUE 10
227 TRUE 10
222 TRUE 10
225 TRUE 10
161 TRUE 10
76 TRUE 10
130 TRUE 10
146 TRUE 10
188 TRUE 10
224 TRUE 10
226 TRUE 10
228 TRUE 10
229 TRUE 10
13 TRUE 10
35 TRUE 10
113 TRUE 10
211 TRUE 10
56 TRUE 10
Here is the code.
structure(list(inter = c(FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, TRUE, TRUE,
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE,
TRUE, TRUE, TRUE, TRUE), counter = c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L,
4L, 4L, 5L, 5L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L,
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 10L, 10L)), class = "data.frame", row.names = c(189L,
192L, 233L, 235L, 237L, 238L, 249L, 256L, 258L, 259L, 14L, 17L,
36L, 39L, 82L, 114L, 117L, 136L, 152L, 194L, 212L, 215L, 251L,
262L, 267L, 268L, 57L, 60L, 96L, 99L, 232L, 239L, 242L, 260L,
19L, 41L, 119L, 217L, 62L, 101L, 181L, 206L, 244L, 269L, 176L,
179L, 201L, 204L, 157L, 159L, 72L, 74L, 126L, 128L, 142L, 144L,
172L, 178L, 180L, 182L, 183L, 186L, 203L, 205L, 207L, 208L, 175L,
200L, 9L, 11L, 31L, 33L, 109L, 111L, 174L, 199L, 52L, 54L, 91L,
93L, 177L, 184L, 202L, 209L, 227L, 222L, 225L, 161L, 76L, 130L,
146L, 188L, 224L, 226L, 228L, 229L, 13L, 35L, 113L, 211L, 56L
))
Here is one possible answer:
library(data.table)
for(i in 1:nrow(dt)) {
if(length(rle(dt$inter)$lengths)>2)
dt$counter<-rleid(dt$inter)
dt<-dt[!dt$counter %in% names(which(table(dt$counter) == min(table(dt$counter)))), ]
dt$counter<-rleid(dt$inter)
if(length(rle(dt$inter)$lengths)==2)
break}