Python finding min. value in every column in 2D array

Question

I have a 2D array, and I would like to find the min. value in every column and minus this min value in every column.

For example,

array = [
[1, 2, 4],
[2, 4, 6],
[5, 7, 9]]

The smallest values in columns are 1, 2, 4.

I would like the result to be

array = [
[0, 0, 0],
[1, 2, 2],
[4, 5, 5]]

How can I achieve this?

if you have real numpy.array() or pandas.DataFrame() then you could use array.min() or maybe array.min(axis=???). And maybe even array = array - array.min() — furas
– furas, Commented Mar 11, 2020 at 4:21
Please follow the numpy documenation for basics array-array.min(0) — Naga kiran
– Naga kiran, Commented Mar 11, 2020 at 4:22

furas · Accepted Answer · 2020-03-11 04:24:52Z

2

If you use real numpy.array or pandas.DataFrame then you have arr.min(axis=0) and arr - arr.min(axis=0)

For numpy.array

import numpy as np

data = [
    [1, 2, 4],
    [2, 4, 6],
    [5, 7, 9]
]

arr = np.array(data)

print( arr.min(axis=0) )

print( arr - arr.min(axis=0) )

Result

[1 2 4]

[[0 0 0]
 [1 2 2]
 [4 5 5]]

Similar for pandas.DataFrame

import pandas as pd

data = [
    [1, 2, 4],
    [2, 4, 6],
    [5, 7, 9]
]

df = pd.DataFrame(data)

print( df.min(axis=0) )

print( df - df.min(axis=0) )

Result

0    1
1    2
2    4
dtype: int64

   0  1  2
0  0  0  0
1  1  2  2
2  4  5  5

answered Mar 11, 2020 at 4:24

furas

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