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Reduce Array's Dimension by One with Different Value in NumPy
To reduce array’s dimension by one, use the np.ufunc.reduce() method in Python Numpy. Here, we have used add.reduce() to reduce it to the addition of all the elements. To initialize the reduction with a different value, use the "initials" parameter.
A universal function (or ufunc for short) is a function that operates on ndarrays in an element-byelement fashion, supporting array broadcasting, type casting, and several other standard features. That is, a ufunc is a "vectorized" wrapper for a function that takes a fixed number of specific inputs and produces a fixed number of specific outputs
Steps
At first, import the required library −
import numpy as np
Create a 1D array −
arr = np.array([7, 14, 21, 28, 35])
Display the array −
print("Array...
", arr)
Get the type of the array −
print("
Our Array type...
", arr.dtype)
Get the dimensions of the Array −
print("
Our Array Dimensions...
",arr.ndim)
To reduce array’s dimension by one, use the np.ufunc.reduce() method in Python Numpy. Here, we have used add.reduce() to reduce it to the addition of all the elements. To initialize the reduction with a different value, use the "initials" parameter −
print("
Result (addition)...
",np.add.reduce(arr, initial = 99))
Example
import numpy as np # The numpy.ufunc has functions that operate element by element on whole arrays. # ufuncs are written in C (for speed) and linked into Python with NumPy’s ufunc facility # Create a 1D array arr = np.array([7, 14, 21, 28, 35]) # Display the array print("Array...
", arr) # Get the type of the array print("
Our Array type...
", arr.dtype) # Get the dimensions of the Array print("
Our Array Dimensions...
",arr.ndim) # To reduce array’s dimension by one, use the np.ufunc.reduce() method in Python Numpy # Here, we have used add.reduce() to reduce it to the addition of all the elements # To initialize the reduction with a different value, use the "initials" parameter print("
Result (addition)...
",np.add.reduce(arr, initial = 99))
Output
Array... [ 7 14 21 28 35] Our Array type... int64 Our Array Dimensions... 1 Result (addition)... 204