### Numpy Ndarray

Ndarray is The n-dimensional array object defined in the numpy is ndarray which stores the collection of the similar type of elements.

An item in an ndarray takes the same size of block in the memory. The ndarray object can be accessed by using the 0 based indexing.

Creating a ndarray :

``x = numpy.array``

Before creating the ndarraay make sure that the numpy module is installed and imported into the program. If not install then check this article (Installation-of-numpy).

``````import numpy as np
x =  np.array()
print(x)``````

The above code will create the empty  n-dimensional array. We can also pass the parameters in the array  to create the equivalent n-dimensional array, Use following syntax.

``````numpy.array(object, dtype = None, copy = True, order = None, subok = False, ndmin = 0)
``````

Following are the in-details use of parameters.

 Sr No. Parameter Description 1 object It represents the object. It can be a list, dictionary, set, tuple etc. 2 dtype The dtype parameter is used for changing data type. e.g float, int,     complex etc 3 copy By default it is true and optional. Which means the object is copied. 4 order Order can be C (column), R (row), or A (any)(default) 5 subok It returned base class array by default. We can change it option to true so   it will passes through subclasses. 6 ndmin Ndmin means minimum dimensions of the resulting array.

Following are the some example to creating ndarray.

• creating array using list
``````import numpy as np
x = np.array([11,25,48])
print (x)``````

Output :

``````[11, 25, 48]
``````

For in-depth opertaion of ndarray check this article ( Numpy-Ndarray-Operation)

Happy coding....

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