How to store maximum values in an array to a dataframe's column in Pandas

Question

I want to store the maximum values in the array below into a dataframe's column

# dataset 
import pandas as pd

data = {'product_name': ['laptop', 'printer', 'tablet', 'desk', 'chair','Watch'],
        'price': [1200, 150, 300, 450, 200,90],
        'class':['good','bad','bad','good','bad','good']
        }

df = pd.DataFrame(data)

print(df)
#####################################################
arr = [[0.11085975, 0.88914025],
 [0.69934523, 0.30065477],
 [0.6325009 , 0.36749908],
 [0.8115895 , 0.18841055],
 [0.8882814 , 0.11171862],
 [0.891402  , 0.10859799]]

My attempt

df['max_score'] = np.max(arr) # this only returns `0.891402`

Kindly share your code, thanks in advance.

mozway · Accepted Answer · 2022-11-24 07:16:13Z

3

Unlike pandas, that defaults to axis=0 for most 2D operations, numpy defaults to axis=None, creating a single scalar. See numpy.ndarray.max

Use axis=1:

df['max_score'] = np.max(arr, axis=1)

Output:

  product_name  price class  max_score
0       laptop   1200  good   0.889140
1      printer    150   bad   0.699345
2       tablet    300   bad   0.632501
3         desk    450  good   0.811589
4        chair    200   bad   0.888281
5        Watch     90  good   0.891402

answered Nov 24, 2022 at 7:16

mozway

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