import numpy as np 
a = np.array([[1,2,3],[4,5,6]]) 
print a.shape

(2, 3)

# this resizes the ndarray 
import numpy as np 

a = np.array([[1,2,3],[4,5,6]]) 
a.shape = (3,2) 
print a

[[1, 2] 
 [3, 4] 
 [5, 6]]

import numpy as np 
a = np.array([[1,2,3],[4,5,6]]) 
b = a.reshape(3,2) 
print b

[[1, 2] 
 [3, 4] 
 [5, 6]]

# an array of evenly spaced numbers 
import numpy as np 
a = np.arange(24) 
print a

[0 1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16 17 18 19 20 21 22 23]

# this is one dimensional array 
import numpy as np 
a = np.arange(24) 
a.ndim  

# now reshape it 
b = a.reshape(2,4,3) 
print b 
# b is having three dimensions

[[[ 0,  1,  2] 
  [ 3,  4,  5] 
  [ 6,  7,  8] 
  [ 9, 10, 11]]  
  [[12, 13, 14] 
   [15, 16, 17]
   [18, 19, 20] 
   [21, 22, 23]]]

# dtype of array is int8 (1 byte) 
import numpy as np 
x = np.array([1,2,3,4,5], dtype = np.int8) 
print x.itemsize

1

# dtype of array is now float32 (4 bytes) 
import numpy as np 
x = np.array([1,2,3,4,5], dtype = np.float32) 
print x.itemsize

4

import numpy as np 
x = np.array([1,2,3,4,5]) 
print x.flags

C_CONTIGUOUS : True 
F_CONTIGUOUS : True 
OWNDATA : True 
WRITEABLE : True 
ALIGNED : True 
UPDATEIFCOPY : False