You could use grep, but it's probably easier to use %in% (see also
is.element()), e.g.:
house_info[ house_info[,1] %in% c("Water damage", "water pipes damaged", "leaking
water"), ]
water_evaluation.water_evaluation_selection. house_number
6 water pipes damaged 489
8 water pipes damaged 512
11 water pipes damaged 597
19 Water damage 478
21 water pipes damaged 373
23 Water damage 465
....
house_info[ house_info[,1] %in% c("Water damage", "water pipes damaged", "leaking
water"), 2]
[1] 489 512 597 478 373 465 337 362 234 535 551 351 415 495 220 216 317 443 346
577 585 268 463 441 225 200 304 486 390 476 485 247
[33] 399 504 262 551 575 359 538
sort(unique(house_info[ house_info[,1] %in% c("Water damage", "water pipes damaged",
"leaking water"), 2]))
[1] 200 216 220 225 234 247 262 268 304 317 337 346 351 359 362 373 390 399 415
441 443 463 465 476 478 485 486 489 495 504 512 535
[33] 538 551 575 577 585 597
Also, an easier way to generated random integers is sample(), e.g.
sample(1:3, size=5, rep=T)
[1] 3 1 2 1 1
(This is more straightforward, and more easily avoids possibly unintended
errors such as floor(runif(100, 1,6) never generating a 6, but do be careful of
the gotcha that sample(2:3, ...) will generate a selection of 2's and 3's,
while sample(3,...) will generate samples from 1, 2, and 3.)
-- Tony Plate
Jason Rupert wrote:
Say I have the following data:
house_number<-floor(runif(100, 200, 600))
water_evaluation<-c("No water damage", "Water damage", "Water On", "Water off", "water pipes
damaged", "leaking water")
water_evaluation_selection<-floor(runif(100, 1,6))
house_info<-data.frame(water_evaluation[water_evaluation_selection],
house_number)
And, that I only want to pull out the ones with negative water evaluations, i.e. Water damage, water pipes damaged, and leaking water.
Should/could I use grep in order to pull the house numbers out of house_info with those negative water evaluations?
I guess I want to know the house numbers from house_info where the water evaluation is negative. Is there a way to use grep or another R function in order to acquire that information?
Thank you again in advance for any insights.
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and provide commented, minimal, self-contained, reproducible code.
