How do you extract a column from a multi-dimensional array?

Question

Does anybody know how to extract a column from a multi-dimensional array in Python?

Answer 1

check it out!

a = [[1, 2], [2, 3], [3, 4]]
a2 = zip(*a)
a2[0]

it is the same thing as above except somehow it is neater the zip does the work but requires single arrays as arguments, the *a syntax unpacks the multidimensional array into single array arguments

Answer 2

[matrix[i][column] for i in range(len(matrix))]

Answer 3

array = [[1,2,3,4],[5,6,7,8],[9,10,11,12],[13,14,15,16]]

col1 = [val[1] for val in array]
col2 = [val[2] for val in array]
col3 = [val[3] for val in array]
col4 = [val[4] for val in array]
print(col1)
print(col2)
print(col3)
print(col4)

Output:
[1, 5, 9, 13]
[2, 6, 10, 14]
[3, 7, 11, 15]
[4, 8, 12, 16]

Answer 4

All columns from a matrix into a new list:

N = len(matrix) 
column_list = [ [matrix[row][column] for row in range(N)] for column in range(N) ]

Answer 5

>>> x = arange(20).reshape(4,5)
>>> x array([[ 0,  1,  2,  3,  4],
        [ 5,  6,  7,  8,  9],
        [10, 11, 12, 13, 14],
        [15, 16, 17, 18, 19]])

if you want the second column you can use

>>> x[:, 1]
array([ 1,  6, 11, 16])

Answer 6

Well a 'bit' late ...

In case performance matters and your data is shaped rectangular, you might also store it in one dimension and access the columns by regular slicing e.g. ...

A = [[1,2,3,4],[5,6,7,8]]     #< assume this 4x2-matrix
B = reduce( operator.add, A ) #< get it one-dimensional

def column1d( matrix, dimX, colIdx ):
  return matrix[colIdx::dimX]

def row1d( matrix, dimX, rowIdx ):
  return matrix[rowIdx:rowIdx+dimX] 

>>> column1d( B, 4, 1 )
[2, 6]
>>> row1d( B, 4, 1 )
[2, 3, 4, 5]

The neat thing is this is really fast. However, negative indexes don't work here! So you can't access the last column or row by index -1.

If you need negative indexing you can tune the accessor-functions a bit, e.g.

def column1d( matrix, dimX, colIdx ):
  return matrix[colIdx % dimX::dimX]

def row1d( matrix, dimX, dimY, rowIdx ):
  rowIdx = (rowIdx % dimY) * dimX
  return matrix[rowIdx:rowIdx+dimX]