04. NumPy Axis

import numpy as np

# Change False to True for this block of code to see what it does

# NumPy axis argument
if False:
    a = np.array([
        [1, 2, 3],
        [4, 5, 6],
        [7, 8, 9]
    ])
    
    print a.sum()
    print a.sum(axis=0)
    print a.sum(axis=1)
    
# Subway ridership for 5 stations on 10 different days
ridership = np.array([
    [   0,    0,    2,    5,    0],
    [1478, 3877, 3674, 2328, 2539],
    [1613, 4088, 3991, 6461, 2691],
    [1560, 3392, 3826, 4787, 2613],
    [1608, 4802, 3932, 4477, 2705],
    [1576, 3933, 3909, 4979, 2685],
    [  95,  229,  255,  496,  201],
    [   2,    0,    1,   27,    0],
    [1438, 3785, 3589, 4174, 2215],
    [1342, 4043, 4009, 4665, 3033]
])

def min_and_max_riders_per_day(ridership):
    '''
    Fill in this function. First, for each subway station, calculate the
    mean ridership per day. Then, out of all the subway stations, return the
    maximum and minimum of these values. That is, find the maximum
    mean-ridership-per-day and the minimum mean-ridership-per-day for any
    subway station.
    '''
    max_daily_ridership = None     # Replace this with your code
    min_daily_ridership = None     # Replace this with your code
    
    return (max_daily_ridership, min_daily_ridership)