To create a two-dimensional array (matrix), use `np.array()`

as demonstrated above, but use a sequence
of sequences to provide the values.

>>> d2 = np.array([(0, 1, 2, 3), (4, 5, 6, 7), (8, 9, 10, 11)]) >>> print d2 [[ 0 1 2 3] [ 4 5 6 7] [ 8 9 10 11]]

To retrieve a value from a matrix

, use an expression of the form `M`

where * M*[

`row`

`col`

`row`

is the row position
and `col`

is the column position.
>>> print d2[0,2] 2 >>> print d2[2, 3] 11

You can use slicing to get one row or column. A slice operation has this general form:

[`M`

,`rows`

]`cols`

In this form,

and `rows`

may be
either regular Python slice operations (such as `cols`

`2:5`

to select the third through fifth items), or they
may be just “`:`

” to select all the
elements in that dimension.

In this example, we extract a 2×3 submatrix, containing rows 0 and 1, and columns 0, 1, and 2.

>>> print d2[0:2, 0:3] [[0 1 2] [4 5 6]]

This example extracts all the rows, but only the first three columns.

>>> print d2[:,0:3] [[ 0 1 2] [ 4 5 6] [ 8 9 10]]

In this example we select all the columns, but only the first two rows.

>>> print d2[0:2,:] [[0 1 2 3] [4 5 6 7]]

You can use the `np.zeros()`

function to create
an empty matrix. The argument is a sequence (list or tuple)
of the dimensions; we'll use a tuple this time.

>>> z2 = np.zeros((2,7)) >>> print z2 [[ 0. 0. 0. 0. 0. 0. 0.] [ 0. 0. 0. 0. 0. 0. 0.]]