Write a function column_means(matrix) that returns a list where each element is the mean of the corresponding column in the matrix. Do not use np.mean().
Example:
Input: matrix = [[1, 2, 3],
[4, 5, 6],
[7, 8, 9]]
Output: [4.0, 5.0, 6.0]
**Explanation:** Col 0: (1+4+7)/3=4.0, Col 1: (2+5+8)/3=5.0, Col 2: (3+6+9)/3=6.0
Constraints:
Test Cases
Test Case 1
Input:
[[1, 2, 3], [4, 5, 6], [7, 8, 9]]Expected:
[4.0, 5.0, 6.0]Test Case 2
Input:
[[10, 20], [30, 40]]Expected:
[20.0, 30.0]Test Case 3
Input:
[[5, 10, 15]]Expected:
[5.0, 10.0, 15.0]+ 2 hidden test cases