Python | Numpy numpy.ndarray.__mul__()
With the help of Numpy numpy.ndarray.__mul__(), we can multiply a particular value that is provided as a parameter in the ndarray.__mul__() method. Value will be multiplied to each and every element in a numpy array.
Syntax: ndarray.__mul__($self, value, /)
Return: self*value
Example #1 :
In this example, we can see that each element in an array is multiplied with the value given as a parameter in method ndarray.__mul__(). This method will work fine for positive, negative and floating point values of an array.
# import the important module in python import numpy as np # make an array with numpy gfg = np.array([1, 2.5, 3, 4.8, 5]) # applying ndarray.__mul__() method print(gfg.__mul__(5)) |
[ 5. 12.5 15. 24. 25. ]
Example #2 :
# import the important module in python import numpy as np # make an array with numpy gfg = np.array([[1, 2, 3, 4.45, 5], [6, 5.5, 4, 3, 2.62]]) # applying ndarray.__mul__() method print(gfg.__mul__(5)) |
[[ 5. 10. 15. 22.25 25. ] [ 30. 27.5 20. 15. 13.1 ]]
Recommended Posts:
- Python | Numpy numpy.ndarray.__isub__()
- Python | Numpy numpy.ndarray.__divmod__()
- Python | Numpy numpy.ndarray.__invert__()
- Python | Numpy numpy.ndarray.__mod__()
- Python | Numpy numpy.ndarray.__floordiv__()
- Python | Numpy numpy.ndarray.__sub__()
- Python | Numpy numpy.ndarray.__truediv__()
- Python | Numpy numpy.ndarray.__pos__()
- Python | Numpy numpy.ndarray.__add__()
- Python | Numpy numpy.ndarray.__pow__()
- Python | Numpy numpy.ndarray.__iadd__()
- Python | Numpy numpy.ndarray.__imul__()
- Python | Numpy numpy.ndarray.__xor__()
- Python | Numpy numpy.ndarray.__and__()
- Python | Numpy numpy.ndarray.__or__()
If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to contribute@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.
Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.



