counting the amount of True/False values in a pandas row

You can do this:

df[(df > 3).sum(axis=1) >= 3]

where df > 3 returns a Boolean mask over the entire DataFrame according to the condition, and sum(axis=1) returns the number of True in that mask, for each row. Finally the >=3 operation returns another mask that can be used to filter the original DataFrame.

Output:

   A  B  C  D  E
b  3  6  5  8  8
c  6  2  5  5  2