How to filter a df where every instance of an element has a value > x in another column (same row-CodePudding

I am trying to sort a df where every instance of each value in the subject column has to be above a certain value.

I want a df with only those subjects with values in values > 0.5 in every instance.

Example df:

df1 <- data.frame(subject = c(1, 2, 3, 4, 5, 1, 2, 3, 4, 5),
                   values = c(.4, .6, .6, .6, .6, .6, .6, .6, .6, .4))
> df1
   subject values
1        1    0.4
2        2    0.6
3        3    0.6
4        4    0.6
5        5    0.6
6        1    0.6
7        2    0.6
8        3    0.6
9        4    0.6
10       5    0.4

would produce:

> df1
  subject values
1       2    0.6
2       3    0.6
3       4    0.6
4       2    0.6
5       3    0.6
6       4    0.6

Thanks.

CodePudding user response：

You can use all() inside a grouped filter using dplyr:

library(dplyr)

df1 %>%
  group_by(subject) %>%
  filter(all(values > .5)) %>%
  ungroup()

Output:

# A tibble: 6 x 2
  subject values
    <dbl>  <dbl>
1       2    0.6
2       3    0.6
3       4    0.6
4       2    0.6
5       3    0.6
6       4    0.6

CodePudding user response：

Using min in ave.

df1[with(df1, ave(values, subject, FUN=min)) > .5, ]
#   subject values
# 2       2    0.6
# 3       3    0.6
# 4       4    0.6
# 7       2    0.6
# 8       3    0.6
# 9       4    0.6

CodePudding user response：

a data.table approach

library(data.table_)
setDT(df1)[, .SD[all(values == 0.6) == TRUE], by = .(subject)][]
#    subject values
# 1:       2    0.6
# 2:       2    0.6
# 3:       3    0.6
# 4:       3    0.6
# 5:       4    0.6
# 6:       4    0.6