R subset

set.seed(500)
dat <- data.frame(c1 = rnorm(10), c2 = sample(1:3, 10, TRUE),
                  c3 = sample(LETTERS[1:5], 10, TRUE))
#             c1 c2 c3
# 1   0.96848929  1  A
# 2   1.96536781  3  A
# 3   0.88632253  1  D
# 4   0.03054026  2  A
# 5   0.94955742  1  B
# 6  -0.57673001  3  E
# 7   0.72152335  3  E
# 8   0.61909890  3  A
# 9   0.02100582  1  E
# 10  0.27485018  1  A

dat[dat$c3 %in% dat[dat$c1 >= 0.9 & dat$c2 == 1, 'c3'], ]
#            c1 c2 c3
# 1  0.96848929  1  A
# 2  1.96536781  3  A
# 4  0.03054026  2  A
# 5  0.94955742  1  B
# 8  0.61909890  3  A
# 10 0.27485018  1  A


library(dplyr)
dat %>% filter(c3 %in% (dat %>% filter(c1 >= 0.9, c2 == 1) %>% .$c3))
#           c1 c2 c3
# 1 0.96848929  1  A
# 2 1.96536781  3  A
# 3 0.03054026  2  A
# 4 0.94955742  1  B
# 5 0.61909890  3  A
# 6 0.27485018  1  A