基于满足不同标准范围的 2 列保留 dataframe 中的行； dataframe中有27行范围

Question

I have a dataframe dat which I need to extract the entire row based on 2 columns ut and ctz which must satisfy their respective rows of ranges in data.frame range_criteria simultaneously; the ranges are different for ut and ctz and they must satisfy their respective ranges . If either the ut or ctz is out of the range, the entire row will be discarded.

I have been cracking my brain over this for for 12 hours, I must make sure each row of ut and dat is checked by every row of the respective range_criteria . I know I have to loop, but I am not sure how... please help!

dat <- data.frame(name = c('Tom', "Harry", "David", "Daniel", "Harri", "Davidi", "Daniely"),
             ut = c(2.4, 3.2, 3.5,9.5,5.2,6.0,45),
             ctz = c(1, 6.0, 3.5, 5.1, 51.5, 6.6, 7))

range_criteria <- data.frame(ut_min = c(0.0, 0.5, 1.0, 2.0, 7.2, 9.0, 21.0),
    ut_max = c(5, 10, 15, 25, 30, 35, 50),
    ctz_min = c(0, 1, 2, 3.2, 4.3, 6.3, 6.9),
    ctz_max = c(5, 5.5, 6.1, 6.2, 6.4 ,6.5, 7.8)

The expected outcome should be:

interest <- data.frame(name = c('Tom', "David", "Daniely" ),
                 ut = c(2.4, 3.5,45),
                 ctz = c(1, 3.5, 7))

Thank you so much !!

Answer 1

Based on your description it sounds like you want the i th row of dat to satisfy both ranges specified in the i th row of range_criteria , is that correct?

If so, there's no need to loop (explicitly). R's vectorized approach makes this work pretty easily:

dat <- data.frame(name = c('Tom', "Harry", "David", "Daniel", "Harri", "Davidi", "Daniely"),
                  ut = c(2.4, 3.2, 3.5,9.5,5.2,6.0,45),
                  ctz = c(1, 6.0, 3.5, 5.1, 51.5, 6.6, 7))

rc <- data.frame(ut_min = c(0.0, 0.5, 1.0, 2.0, 7.2, 9.0, 21.0),
                             ut_max = c(5, 10, 15, 25, 30, 35, 50),
                             ctz_min = c(0, 1, 2, 3.2, 4.3, 6.3, 6.9),
                             ctz_max = c(5, 5.5, 6.1, 6.2, 6.4 ,6.5, 7.8))

dat[dat$ut >= rc$ut_min & dat$ut <= rc$ut_max & dat$ctz >= rc$ctz_min & dat$ctz <= rc$ctz_max,]

This also returns "Daniel" in addition to the other three names you mentioned, but looking at the data I think that's correct.

Alternately you could use a package designed for data manipulation like dplyr or data.table to do the same thing a bit more smoothly.

library(data.table)

both <- cbind(dat, rc)
setDT(both)
interest <- both[between(ut, ut_min, ut_max) & between(ctz, ctz_min, ctz_max)]

or

library(dplyr)

both <- bind_cols(dat, rc)

interest <- both %>%
  filter(ut >= ut_min & ut <= ut_max & ctz >= ctz_min & ctz <= ctz_max)