I\'m currently trying to learn Numpy and Python. Given the following array:
import numpy as np
a = np.array([[1,2],[1,2]])
Is there a funct
It is .shape:
ndarray.shape
Tuple of array dimensions.
Thus:
>>> a.shape
(2, 2)
a.shape
is just a limited version of np.info()
. Check this out:
import numpy as np
a = np.array([[1,2],[1,2]])
np.info(a)
Out
class: ndarray
shape: (2, 2)
strides: (8, 4)
itemsize: 4
aligned: True
contiguous: True
fortran: False
data pointer: 0x27509cf0560
byteorder: little
byteswap: False
type: int32
rows = a.shape[0] # 2
cols = a.shape[1] # 2
a.shape #(2,2)
a.size # rows * cols = 4
You can use .ndim
for dimension and .shape
to know the exact dimension
var = np.array([[1,2,3,4,5,6], [1,2,3,4,5,6]])
var.ndim
# displays 2
var.shape
# display 6, 2
You can change the dimension using .reshape
function
var = np.array([[1,2,3,4,5,6], [1,2,3,4,5,6]]).reshape(3,4)
var.ndim
#display 2
var.shape
#display 3, 4
import numpy as np
>>> np.shape(a)
(2,2)
Also works if the input is not a numpy array but a list of lists
>>> a = [[1,2],[1,2]]
>>> np.shape(a)
(2,2)
Or a tuple of tuples
>>> a = ((1,2),(1,2))
>>> np.shape(a)
(2,2)
You can use .shape
In: a = np.array([[1,2,3],[4,5,6]])
In: a.shape
Out: (2, 3)
In: a.shape[0] # x axis
Out: 2
In: a.shape[1] # y axis
Out: 3