Find the product of the minimum height of defenders lower than 180 cm and the maximum height of midfielders higher than 185 cm

Question

positions = ['GK', 'M', 'A', 'D', 'M', 'D', 'M', 'M', 'M', 'A', 'M', 'M', 'A', 'A', 'A', 'M', 'D', 'A', 'D', 'M', 'GK', 'D', 'D', 'M', 'M', 'M', 'M', 'D', 'M', 'GK', 'D', 'GK', 'D', 'D', 'M']
heights = [191, 184, 185, 180, 181, 187, 170, 179, 183, 186, 185, 170, 187, 183, 173, 188, 183, 180, 188, 175, 193, 180, 185, 170, 183, 173, 185, 185, 168, 190, 178, 185, 185, 193, 183]

np_positions = np.array(positions)
np_heights = np.array(heights)

My code is:

print(np.min(positions=='D'[heights<180]) * np.max(positions=='A'[heights > 185]))

I get a TypeError. I made it another way, but I need to do this in 1 string.

Answer 1

What you could do is to create a 2D list with position and height using zip.

In the min and max functions of python you are able to define your own key on what the minimum and maximum value should be searched for. In this case I used a lambda function using an if else statement.

positions = ['GK', 'M', 'A', 'D', 'M', 'D', 'M', 'M', 'M', 'A', 'M', 'M', 'A', 'A', 'A', 'M', 'D', 'A', 'D', 'M', 'GK', 'D', 'D', 'M', 'M', 'M', 'M', 'D', 'M', 'GK', 'D', 'GK', 'D', 'D', 'M'] 
heights = [191, 184, 185, 180, 181, 187, 170, 179, 183, 186, 185, 170, 187, 183, 173, 188, 183, 180, 188, 175, 193, 180, 185, 170, 183, 173, 185, 185, 168, 190, 178, 185, 185, 193, 183]

# create a 2d array:
d = list(zip(positions, heights))
min_height_defender = min(d, key=lambda x: x[1] if x[0] == 'D' and x[1] < 180 else 1e9)
max_height_midfielder = max(d, key=lambda x: x[1] if x[0] == 'A' and x[1] > 185 else -1e9)

print( min_height_defender[1] * max_height_midfielder[1] )
>>> 33286

Or you can use numpy, but I would suggest that you test your minimum and maximum value after filtering, otherwise your code becomes unreadable:

# or with numpy:
positions = np.array(positions)
heights = np.array(heights)

print( heights[np.argwhere(positions == 'D')].min() * heights[np.argwhere(positions == 'A')].max() )
>>> 33286


# or without argwhere:
print( heights[positions == 'D'].min() * heights[positions == 'A'].max() )
>>> 33286

If you want to filter inline you can use it, but as said it is very ugly (in my opinion) and you should avoid to do more than 1 thing per line of code. But if you want of just for the kick of doing things in one line:

print( heights[heights<180][positions[heights<180] == 'D'].min() * heights[heights>185][positions[heights>185] == 'A'].max() )
>>> 33286

Answer 2

IIUC, use your numpy arrays and boolean slicing!

NB. assuming Defender is D and Midfielder is M.

            # position is D/M   condition on height
(np_heights[(np_positions=='D')&(np_heights<180)].min()
*np_heights[(np_positions=='M')&(np_heights>185)].max()
)

output: 33464 (178*188)