check and count a condition over all rows of a dataframe

I have a dataframe like this

data = { 'number':['one','two','three'],
         'l_min_x':[6,6,6],
         'l_max_x':[12,18,15],
         'r_min_x':[6,6,6],
         'r_max_x':[17,19,15]}
         
datadf= pd.DataFrame(data)
print(datadf)

and I get

  number  l_min_x  l_max_x  r_min_x  r_max_x
0    one        6       12        6       17
1    two        6       18        6       19
2  three        6       15        6       15

and I want to check and count how many of the rows fulfill a condition.
Now I can do this going row by row like this question but I am wondering if there is another way that takes the whole dataframe and do the following:

• Check how many rows have l_min_x less than a value (for example 7) and l_max_x greater than another value (say 17)
  In this case the answer would be 1 (one)

• Check how many rows have r_min_x less than a value (for example 8) and r_max_x greater than another value (say 16)
  In this case the answer would be 2 (two)

Can I do this without iterating over all rows of the dataframe?