subset rows with (1) ALL and (2) ANY columns larger than a specific value

Question

I have a data frame with an id column and some (potentially many) columns with values, here 'v1', 'v2':

df <- data.frame(id = c(1:5), v1 = c(0,15,9,12,7), v2 = c(9,32,6,17,11))
#   id v1 v2
# 1  1  0  9
# 2  2 15 32
# 3  3  9  6
# 4  4 12 17
# 5  5  7 11

1. How can I extract rows where ALL values are larger than a certain value, say 10, which should return:

   #   id v1 v2
   # 2  2 15 32
   # 4  4 12 17
   

2. How can I extract rows with ANY (at least one) value is larger than 10:

   #   id v1 v2
   # 2  2 15 32
   # 4  4 12 17
   # 5  5  7 11
   

Answer 1

See functions all() and any() for the first and second parts of your questions respectively. The apply() function can be used to run functions over rows or columns. (MARGIN = 1 is rows, MARGIN = 2 is columns, etc). Note I use apply() on df[, -1] to ignore the id variable when doing the comparisons.

Part 1:

> df <- data.frame(id=c(1:5), v1=c(0,15,9,12,7), v2=c(9,32,6,17,11))
> df[apply(df[, -1], MARGIN = 1, function(x) all(x > 10)), ]
  id v1 v2
2  2 15 32
4  4 12 17

Part 2:

> df[apply(df[, -1], MARGIN = 1, function(x) any(x > 10)), ]
  id v1 v2
2  2 15 32
4  4 12 17
5  5  7 11

To see what is going on, x > 10 returns a logical vector for each row (via apply() indicating whether each element is greater than 10. all() returns TRUE if all element of the input vector are TRUE and FALSE otherwise. any() returns TRUE if any of the elements in the input is TRUE and FALSE if all are FALSE.

I then use the logical vector resulting from the apply() call

> apply(df[, -1], MARGIN = 1, function(x) all(x > 10))
[1] FALSE  TRUE FALSE  TRUE FALSE
> apply(df[, -1], MARGIN = 1, function(x) any(x > 10))
[1] FALSE  TRUE FALSE  TRUE  TRUE

to subset df (as shown above).