With this setup:
>>> A = np.array([0,1,2])
>>> B = np.array([1,0,3])
>>> C = np.array([3,0,4])
You can either do:
>>> np.maximum.reduce([A,B,C])
array([3, 1, 4])
Or:
>>> np.vstack([A,B,C]).max(axis=0)
array([3, 1, 4])
I would go with the first option.
Answer from Daniel on Stack OverflowNumPy
numpy.org › doc › 2.4 › reference › generated › numpy.maximum.html
numpy.maximum — NumPy v2.4 Manual
Element-wise maximum of two arrays, ignores NaNs.
NumPy
numpy.org › devdocs › reference › generated › numpy.maximum.html
numpy.maximum — NumPy v2.6.dev0 Manual
Element-wise maximum of two arrays, ignores NaNs.
02:25
Python Numpy Max Function - YouTube
03:11
NumPy argmax() Tutorial: Find Index of Maximum Value in Arrays ...
03:39
NumPy np.max() Tutorial: Find Maximum Values in Arrays | Python ...
04:24
Calculate Max & Min of NumPy Array in Python (Example) | np.max ...
numpy maximum of array
NumPy
numpy.org › doc › 2.3 › reference › generated › numpy.max.html
numpy.max — NumPy v2.3 Manual
The maximum value of an array along a given axis, ignoring any NaNs.
Top answer 1 of 3
69
With this setup:
>>> A = np.array([0,1,2])
>>> B = np.array([1,0,3])
>>> C = np.array([3,0,4])
You can either do:
>>> np.maximum.reduce([A,B,C])
array([3, 1, 4])
Or:
>>> np.vstack([A,B,C]).max(axis=0)
array([3, 1, 4])
I would go with the first option.
2 of 3
22
You can use reduce. It repeatedly applies a binary function to a list of values...
For A, B and C given in question...
np.maximum.reduce([A,B,C])
array([3,1,4])
It first computes the np.maximum of A and B and then computes the np.maximum of (np.maximum of A and B) and C.
Real Python
realpython.com › numpy-max-maximum
NumPy's max() and maximum(): Find Extreme Values in Arrays – Real Python
October 22, 2025 - You can use this built-in max() to find the maximum element in a one-dimensional NumPy array, but it has no support for arrays with more dimensions. When dealing with NumPy arrays, you should stick to NumPy’s own maximum functions and methods.
GeeksforGeeks
geeksforgeeks.org › python › numpy-maximum-in-python
numpy.maximum() in Python - GeeksforGeeks
December 19, 2025 - numpy.maximum() is a NumPy function that compares two arrays (or scalars) element-wise and returns a new array containing the maximum value at each position. If any compared element is NaN, the NaN is returned.
Medium
medium.com › @amit25173 › understanding-element-wise-maximum-in-numpy-43916b1c2002
Understanding Element-wise Maximum in NumPy | by Amit Yadav | Medium
March 6, 2025 - So, if you’re dealing with NumPy arrays, stick with np.maximum().
NumPy
numpy.org › doc › 2.3 › reference › generated › numpy.maximum.html
numpy.maximum — NumPy v2.3 Manual
Element-wise maximum of two arrays, ignores NaNs.
DataCamp
datacamp.com › doc › numpy › max
NumPy max()
The `max()` function is used to compute the maximum value of elements in a NumPy array either globally or along a specific axis.
NumPy
numpy.org › doc › 2.1 › reference › generated › numpy.maximum.html
numpy.maximum — NumPy v2.1 Manual
Element-wise maximum of two arrays, ignores NaNs.
Programiz
programiz.com › python-programming › numpy › methods › maximum
NumPy maximum() (With Examples)
Numpy Broadcasting · The maximum() function is used to find the maximum value between the corresponding elements of two arrays.
NumPy
numpy.org › doc › 2.2 › reference › generated › numpy.maximum.html
numpy.maximum — NumPy v2.2 Manual
Element-wise maximum of two arrays, ignores NaNs.
JAX Documentation
docs.jax.dev › en › latest › _autosummary › jax.numpy.maximum.html
jax.numpy.maximum — JAX documentation
An array containing the element-wise maximum of x and y.
NumPy
numpy.org › devdocs › reference › generated › numpy.max.html
numpy.max — NumPy v2.6.dev0 Manual
The maximum value of an array along a given axis, ignoring any NaNs.
NumPy
numpy.org › doc › stable › reference › generated › numpy.maximum.html
numpy.maximum — NumPy v2.5 Manual
Element-wise maximum of two arrays, ignores NaNs.
NumPy
numpy.org › doc › 2.2 › reference › generated › numpy.max.html
numpy.max — NumPy v2.2 Manual
The maximum value of an array along a given axis, ignoring any NaNs.
Top answer 1 of 2
84
numpy.maximum.accumulate works for me.
>>> import numpy
>>> numpy.maximum.accumulate(numpy.array([11,12,13,20,19,18,17,18,23,21]))
array([11, 12, 13, 20, 20, 20, 20, 20, 23, 23])
2 of 2
3
As suggested, there is scipy.maximum.accumulate:
In [9]: x
Out[9]: [1, 3, 2, 5, 4]
In [10]: scipy.maximum.accumulate(x)
Out[10]: array([1, 3, 3, 5, 5])
Codecademy
codecademy.com › docs › python:numpy › built-in functions › .max()
Python:NumPy | Built-in Functions | .max() | Codecademy
July 2, 2025 - Returns the maximum value of an array or maximum values along a specified axis.
Vultr Docs
docs.vultr.com › python › third party › numpy › max()
Python Numpy max() - Find Maximum Value
November 18, 2024 - Create a one-dimensional NumPy array. Use max() to find the maximum value.
LinkedIn
linkedin.com › posts › realpython-com_numpys-max-and-maximum-find-extreme-activity-7238199410856235008-c3gI
NumPy's max() and maximum values for Arrays
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