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Parameters Return value Examples Creating Numpy array using list Creating Numpy array using tuple Creating Numpy array with explicit type Creating 2D Numpy array Creating 2D Numpy array using ndmin

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NumPy | array method

schedule Aug 10, 2023

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Parameters Return value Examples Creating Numpy array using list Creating Numpy array using tuple Creating Numpy array with explicit type Creating 2D Numpy array Creating 2D Numpy array using ndmin

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Numpy's array(~) method constructs a Numpy array out of the provided object, which is typically a list or a tuple.

Parameters

1. object | array-like objects

Data source used to build a Numpy array. Typically, we use a list or a tuple.

2. dtypelink | string or type | optional

Type of data stored in the Numpy array. By default, type will be inferred.

3. ndminlink | int | optional

The minimum number of dimensions the Numpy array will have.

Return value

A Numpy array with the data-type as specified.

Examples

Creating Numpy array using list


        
        
            
                
                
                    np.array([1,2,3])
                
            
            array([1, 2, 3])

The inferred type of the data is int.

Creating Numpy array using tuple


        
        
            
                
                
                    np.array((1,2,3))
                
            
            array([1, 2, 3])

Creating Numpy array with explicit type


        
        
            
                
                
                    np.array((1,2,3), float)
np.array((1,2,3), "float")
                
            
            array([1., 2., 3.])

Notice how we have 1. instead of just 1 - this means that the data in the Numpy array is of type float instead of int. You can also provide the dtype in string form, like "float".

Creating 2D Numpy array


        
        
            
                
                
                    np.array([[1, 2, 3], [4, 5, 6]])
                
            
            array([[1, 2, 3],
       [4, 5, 6]])

Creating 2D Numpy array using ndmin


        
        
            
                
                
                    np.array([1, 2], ndmin=2)
                
            
            array([[1, 2]])

Here, normally we would have a 1D Numpy array, but since we specified ndmin=2, we get a 2D Numpy array instead.

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