CODEWITHSUNDEEP
pythonlist
A1122
A1122

Reputation: 1354

find the min and max values of nested list by index of element in nested list

I have a nested list like the following:

x = [[1,  5, 3,  4], 
     [5, 10, 7,  8], 
     [9,  9, 2, 12]]

I need to find to find the min and max values of the nested list transposed such that the result for min is:

1, 5, 2, 4  # 1 is the min of first column (1, 5, 9) a.s.o

and the max should be:

9, 10, 7, 12

I tried to convert it into a dataframe first and then doing max and min on the different axis but all doesn't come up as the result I want.

Upvotes: 3

Views: 3345

Answers (3)

RomanPerekhrest
RomanPerekhrest

Reputation: 92854

Simply with numpy module:

import numpy as np

x = np.array([[1,  5, 3,  4], [5, 10, 7,  8], [9,  9, 2, 12]])
print(np.min(x, 0))    # [1 5 2 4]
print(np.max(x, 0))    # [ 9 10  7 12]

Upvotes: 1

Aaditya Ura
Aaditya Ura

Reputation: 12669

You can use list comprehension or other way:

print([min(item) for item in zip(*x)])

is same as:

min_list=[]
for i in zip(*x):
    min_list.append(min(i))
print(min_list)

output:

[1, 5, 2, 4]

For max:

print([max(item) for item in zip(*x)])

is same as:

max_list=[]
for i in zip(*x):
    max_list.append(max(i))

print(max_list)

output:

[9, 10, 7, 12]

Upvotes: 1

user2390182
user2390182

Reputation: 73450

You can do the following using the built-in map, min, max functions and the zip(*...) transpositioning pattern:

min_x = list(map(min, zip(*x)))
max_x = list(map(max, zip(*x)))

Or as pointed out by Chris_Rands, this shortened form will also work:

min_x = list(map(min, *x))
max_x = list(map(max, *x))

Or use comprehensions:

min_x = [min(col) for col in zip(*x)]
max_x = [max(col) for col in zip(*x)]

If you desperately want to do it one line:

min_x, max_x = zip(*[(min(col), max(col)) for col in zip(*x)])

Upvotes: 7

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