The built-in max takes a key function, you can pass that as abs:
>>> max([3, 7, -10], key=abs)
-10
You can call abs again on the result to normalise the result:
>>> abs(max([3, 7, -10], key=abs))
10
Profound Academy
profound.academy › python-introduction › min-max-abs-DZ25fuVqi5ass7kZdK1v
min max abs - Introduction to Python
November 1, 2024 - When dealing with computations, in many cases it’s required to compute min or max values among several values. To help with those operations python provides built-in functions min(), max(), and abs() to compute the minimum, maximum, and the absolute value correspondingly.
Top answer 1 of 5
84
The built-in max takes a key function, you can pass that as abs:
>>> max([3, 7, -10], key=abs)
-10
You can call abs again on the result to normalise the result:
>>> abs(max([3, 7, -10], key=abs))
10
2 of 5
13
max(max(a),-min(a))
It's the fastest for now, since no intermediate list is created (for 100 000 values):
In [200]: %timeit max(max(a),-min(a))
100 loops, best of 3: 8.82 ms per loop
In [201]: %timeit abs(max(a,key=abs))
100 loops, best of 3: 13.8 ms per loop
In [202]: %timeit max(map(abs,a))
100 loops, best of 3: 13.2 ms per loop
In [203]: %timeit max(abs(n) for n in a)
10 loops, best of 3: 19.9 ms per loop
In [204]: %timeit np.abs(a).max()
100 loops, best of 3: 11.4 ms per loop
python - How to find values with minimal absolute values in several columns ignoring NaNs? - Stack Overflow
I have the following two pandas time series (but the question is also applicable to numpy array): NaN NaN NaN 2 NaN 1 NaN 0 NaN ... More on stackoverflow.com
math - Elegant mechanism to determine smallest magnitude number but preserve sign in Python - Stack Overflow
I have a Pythonic need to determine the minimum number in terms of absolute value, but preserve its sign. Below is the code I use to do this now. Is there a more elegant mechanism either More on stackoverflow.com
arrays - Find absolute maximum or minimum at specific position in list by Python - Stack Overflow
I am trying to get the absolute maximum value of each array without considering the second value in the array. More on stackoverflow.com
python - Finding the largest absolute difference in a list - Code Review Stack Exchange
I'm moving away from map, reduce and filter in favour of list comprehensions. I like list comps but I feel like this is getting on the unreadable side. Is this the most idiomatic way of achieving ... More on codereview.stackexchange.com
Blender Artists
blenderartists.org › coding › python support
lowest absolute value - Python Support - Blender Artists Community
January 1, 2017 - I tried x = min(abs(a), abs(b), abs(c), abs(d)) the problem is this way I lose the pos/neg sign So, I ended up doing this: if abs(a) <= abs(b): x = a if abs(a) <= abs(c): x = a if abs(a) <= abs(d): x = a else: x = d else: x = c else: x = b if ...
alpharithms
alpharithms.com › home › articles › programming › python abs(): the absolute value built-in function
Python abs(): The Absolute Value Built-in Function - αlphαrithms
June 16, 2022 - The Python abs() function is part of the standard built-in functions and provides a utility to calculate an absolute value. This function can be used to convert static values to their absolute value as well as dynamic values. In this article, I’ll cover the basic syntax used for Python’s absolute value function, how to use […]
GitHub
gist.github.com › yaojenkuo › f54e5308e9e76b36d2ac986ea6f3fc1d
kaggle_learn_py_day2_06.py · GitHub
GitHub Gist: instantly share code, notes, and snippets.
Top answer 1 of 2
1
Let, df the dataframe with two columns, apply conditional absolute minimum over rows using axis=1
Here, x[np.argmin(x.abs())] checks the row index with absolute minimum and return the the original value with sign.
Also, we would need pd.isnull(x.min()) check for 'All-NaN slice encountered i.e when both the columns have NaN values.
In [3]: df.apply(lambda x: x.min() if pd.isnull(x.min()) else
x[np.argmin(x.abs())], axis=1)
Out[3]:
0 NaN
1 2
2 1
3 0
4 -1
5 -2
6 -3
7 -4
8 4
9 3
10 2
dtype: float64
2 of 2
1
OK, after reading and understanding your question and not being able to find a vectorised approach, we can define a custom function and call apply and pass each row.
So this will check if either column is null if so return the min value, it then compares the abs value of either column and then returns the column that has smallest abs value but the original value including sign:
In [269]:
def func(x):
if pd.isnull(x.a) or pd.isnull(x.b):
return x.min()
elif np.abs(x.a) < np.abs(x.b):
return x.a
else:
return x.b
df.apply(lambda row: func(row), axis = 1)
Out[269]:
0 NaN
1 2
2 1
3 0
4 -1
5 -2
6 -3
7 -4
8 4
9 3
10 2
dtype: float64
GeeksforGeeks
geeksforgeeks.org › dsa › minimum-absolute-value-of-k-arri-for-all-possible-values-of-k-over-the-range-0-n-1
Minimum absolute value of (K – arr[i]) for all possible values of K over the range [0, N – 1] - GeeksforGeeks
July 23, 2025 - # Python program for the above approach # Function to find the minimum absolute # value of (K - arr[i]) for each possible # value of K over the range [0, N - 1]| def minimumDistance(arr, N): ind = 0; prev = arr[ind]; s = len(arr); # Traverse ...
Real Python
realpython.com › python-absolute-value
How to Find an Absolute Value in Python – Real Python
June 4, 2025 - In this case, you take a squared number to the power of one-half (0.5) or one over two (½), which is the same as calculating the square root. Note that both Python implementations based on the algebraic definition suffer from a slight deficiency: ... >>> def absolute_value(x): ...
Programiz
programiz.com › python-programming › methods › built-in › abs
Python abs()
Become a certified Python programmer. Try Programiz PRO! ... The abs() function returns the absolute value of the given number.
PyQuestHub
pyquesthub.com › understanding-basic-math-operations-in-python-with-abs-min-and-max-functions
Basic Math Operations in Python: Using abs, min, and max Functions
November 21, 2024 - Using the abs function: The abs() function takes a number as input and returns its absolute value. In the example, we assign the value -10 to the variable negative_number, and calling abs(negative_number) gives us 10. Using the min function: The min() function is used to find the smallest number from a list of numbers...
W3Schools
w3schools.com › python › ref_func_abs.asp
Python abs() Function
Python Examples Python Compiler Python Exercises Python Quiz Python Challenges Python Server Python Syllabus Python Study Plan Python Interview Q&A Python Bootcamp Python Certificate Python Training ... The abs() function returns the absolute value of the specified number.
Kaggle
kaggle.com › learn-forum › 130109
Question: Exercise Functions and Getting Help | Data Science and Machine Learning | Kaggle
Question: Exercise Functions and Getting Help.
TradingCode
tradingcode.net › python › math › rare-absolute
Absolute values of uncommon Python values • TradingCode
When we use Python’s abs() function, we often work with integers and floating-point value. But abs() has a less-known feature: it can also work with uncommon values. Let’s have a look. In Python, we get the absolute value of numbers with the abs() function.
Dfrieds
dfrieds.com › python › minimum-absolute-difference.html
Minimum Absolute Difference (via Leetcode) - dan_friedman_learnings
# if absolute difference of pair is equal to min_absolute_difference: # append pair as list to min_pairs_list # else if absolute difference pair is less than min_absolute_difference: # reassign min_absolute_difference to be new absolute difference of pair # if min_pairs_list is empty: # append pair as list to min_pairs_list # else: # we don't want to keep old pairs in min_pairs_list that contain higher abs value among pairs...
Server Academy
serveracademy.com › blog › python-absolute-value-abs-tutorial
Python Absolute Value Abs() Tutorial - Server Academy
November 12, 2024 - For example, the absolute value ... normalization. In Python, the simplest way to calculate the absolute value is to use the abs() function....
LearnDataSci
learndatasci.com › solutions › python-absolute-value
Python Absolute Value – abs() for real and complex numbers – LearnDataSci
The sign of the number alludes to which direction along the line the number is; positive values are along the positive axis, and negative ones are along the negative axis. In the quick example shown in the introduction, -5 is a real number. In regards to Python, real numbers are numbers that are integers or floats. The following example demonstrates how we can apply the abs function to a list of integers: real_number_list = [-12, -6, 0, 4, 8] for number in real_number_list: absolute_value = abs(number) print(f'Number: {number}, Absolute Value: {absolute_value}')
Career Karma
careerkarma.com › blog › python › python absolute value: a step-by-step guide
Python Absolute Value: A Step-By-Step Guide | Career Karma
December 1, 2023 - The Python abs() method returns the absolute value of a number. The absolute value of a number is the number’s distance from 0. This makes any negative number positive, while positive numbers are unaffected.
Top answer 1 of 5
2
You should just code as you would write the steps:
outlist = [] # create an empty output list
for x in data: # for each sublist in data
val = max(abs(x[0]), abs(x[2])) # find max of absolute of 1st and 3rd
outlist.append(val) # add above value to output list
print(outlist) # print the output list
Output:
[1.01201792, 2.68189991, 5.92202221, 10.19026759, 15.30091085]
If there may be more than 3 elements in sublists, you can use following:
outlist = [] # create an empty output list
for x in data: # for each sublist in data
x = [x[0]]+x[2:] # create a new list without 2nd element
val = max(x) # find max of new list
outlist.append(val) # add above value to output list
print(outlist) # print the output list
2 of 5
1
A numpy oneliner. Probably faster than the other approaches depending on the actual size of your data. Convert data to numpy array, slice so you only have the first and last item, convert into absolute values and finally take the max over axis 1.
maxs = np.abs(np.array(data)[:, [0,2]]).max(axis=1)
Broken down:
import numpy as np
data = [([-1.01201792, 2.5, 0.68665077]), ([-2.5, 0.5, 2.68189991]), ([-2.5, 3.5, 5.92202221]), ([-2.5, 5.5, 10.19026759]), ([-2.5, 6.5, 15.30091085])]
arr = np.array(data) # convert into array
first_last = arr[:, [0,2]] # only keep the first and last item of each sublist
absol = np.abs(first_last) # convert to absolute values
maxs = absol.max(axis=1) # get the max value on the first axis
print(maxs)
Top answer 1 of 2
6
A more idiomatic and readable solution would be to use itertools.combinations(list, 2) to take all pairs.
max(abs(a) - abs(b) for a, b in itertools.combinations(int_list, 2))
However, that is O(n2). A smarter O(n) solution would be to subtract the minimum absolute value from the maximum absolute value.
absolutes = [abs(elem) for elem in int_list]
print max(absolutes) - min(absolutes)
2 of 2
1
An alternative, purely functional style approach that builds on itertools.combinations too is this:
max(itertools.starmap(operator.sub, itertools.combinations(map(abs, int_list), 2)))