Numpy is one of the Powerful Python Data Science Libraries. It comes with a builtin robust Array data structure that can be used for many mathematical operations. The numpy library supports many methods and
numpy.dot()
is one of those. Using the numpy dot() method, we can calculate the dot product of two arrays. The numpy
dot(array1,array2)
method accepts two arrays as a parameter and returns their dot product or matrix multiplication.
Numpy dot() syntax
numpy.dot(array1, array2, out=None)
Parameters
arrray1
and
array2
represent the arraylike structure. The
out
parameter represents the output argument. By default, its value is
None,
and if specified explicitly, it needs to be the exact kind of return output of the dot() method.
Return value
The dot() product returns a
ndarray.
Python numpy dot() method examples
Example1:
Python dot() product if both array1 and array2 are 1D arrays.
>>> import numpy as np
>>> array1 = [1,2,3]
>>> array2 = [4,5,6]
>>> print(np.dot(array1, array2))
32
If both the arrays are 1D, the
dot()
method performs the inner product between the arrays and returns the output as a number.
>>>1*4 + 2*5 + 3*6
>>>4+10+18
32
Example 2: Python dot() product if both array1 and array2 are 2D arrays
>>> import numpy as np
>>> array1 = [[4,0], [1,9]]
>>> array2 = [[8,0],[2,18]]
>>> print(np.dot(array1, array2))
[[ 32 0]
[10 162]]
If both arrays are 2D, the dot will perform the matrix multiplication between them.
>>>[[4*8 + 0*2, 4*0 + 0*18 ]
[1*8 + 9*2, 1*0 + 9*18 ]
>>>[[32, 0]
[10, 162]]
Note:
As a matrix multiplication, the row size of
array1
must be equal to the column size of
array2
else, the dot() method throws a ValueError.
Example3:
Python dot() product if either of array1 or array2 is a 0D(scalar) array
>>> import numpy as np
>>> array1 = 10
>>> array2 = [[8,0],[2,18]]
>>> print(np.dot(array1, array2))
[[ 80 0]
[ 20 180]]
If one array of either is a 0D array, the
dot()
multiply the 0D array with the other array.
Summary
The numpy
dot()
method finds out the product of two arrays based on their shape. Here are some important facts about
dot(array1, array2)
method of how it computes the product for different array shapes.

If
array1,
andarray2
are 1D array, the dot() method performs inner product between both the arrays. 
If
array1
andarray2
are 2D arrays, the numpy dot() method performs matrix multiplication between them. 
If anyone between the
array1
orarray2
is a scalar or 1d array, the numpydot()
method will multiply that 1d or scalar number with another array. 
If
array1
is an ND array andarray2
is a 1D array, then the numpydot()
method will calculate the sumproduct over the last axis ofarray1
andarray2.

If
array1
is an ND array andarray2
is an MD array (M>=2 ), then thedot()
method will calculate the sumproduct over the last axis ofarray1
and second to the last axis ofarray2.
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