PYTHON

numpy item size

#itemsize shows the length of one array element in bytes

import numpy as np
a = np.array([[1,2,3],[4,5,6]],dtype = np.int64)
a.itemsize
#output will be 8

numpy array length

np_array.size

get array dimension numpy

import numpy as np

arr = np.array([1,2,3])
arr.ndim

numpy get array size

myArray.shape # Returns the number of rows, columns etc. (depends on dimensions how many numbers you get)

print(a_1d.shape)
# (3,)

print(type(a_1d.shape))
# <class 'tuple'>

print(a_2d.shape)
# (3, 4)

print(a_3d.shape)
# (2, 3, 4)

.size() method in Numpy

# Python program explaining
# numpy.size() method
 
# importing numpy
import numpy as np
 
# Making a random array
arr = np.array([[1, 2, 3, 4], [5, 6, 7, 8]])
 
# count the number of elements along the axis.
# Here rows and columns are being treated
# as elements
 
#gives no. of rows along x-axis
print(np.size(arr, 0))
 
#gives no. of columns along y-axis
print(np.size(arr, 1))

np array size

x = np.zeros((3, 5, 2), dtype=np.complex128)
>>> x.size
30
>>> np.prod(x.shape)
30

size of a NumPy array in Python

a = np.arange(3)
b = np.arange(12).reshape((3, 4))
c = np.arange(24).reshape((2, 3, 4))

# it returns the total number of elements
print(a.size) # 3
print(b.size) # 12
print(c.size) # 24

number of dimensions of NumPy array in Python

a = np.arange(3)
b = np.arange(12).reshape((3, 4))
c = np.arange(24).reshape((2, 3, 4))

print(a.ndim) # 1
print(b.ndim) # 2
print(c.ndim) # 3