CODEWITHSUNDEEP
pythonpandasdataframe
Kirsteen Ng
Kirsteen Ng

Reputation: 111

Pandas Dataframe: Find the index of maximum value for each column using idxmax()

I have a dataframe 156 x 9 with no null values and I am trying to find the index of the maximum value of each column. I tried the following

    country_list = []
    keys = []
    for i in range(len(col)):
        country = df.loc[df[col[i]].idxmax()]['Country or region']
        country_list.append(country)
        keys.append(col[i])

The columns available are

In[65]:df.columns
Out[65]: 
Index(['Overall rank', 'Country or region', 'Score', 'GDP per capita',
       'Social support', 'Healthy life expectancy',
       'Freedom to make life choices', 'Generosity',
       'Perceptions of corruption'],
      dtype='object')

But I got the error of for using idxmax TypeError: reduction operation 'argmax' not allowed for this dtype

Any help appreciated, thank you!

Upvotes: 1

Views: 1305

Answers (2)

programmer pro
programmer pro

Reputation: 179

You can try this :-

import numpy as np

col_names = df.columns
max_val_index = []

for col in col_names:
    max_val_index.append(np.argmax(df[col]))

The max index value will be stored in max_val_index

Upvotes: 0

jezrael
jezrael

Reputation: 862581

Error means there are some non numeric column(s).

Select only numeric columns by DataFrame.select_dtypes and then use DataFrame.idxmax:

df = pd.DataFrame({
        'A':list('abcdef'),
         'B':[4,5,4,5,5,4],
         'C':[7,8,9,4,2,3],
         'D':[1,3,5,7,1,0],
         'E':[5,3,6,9,2,4],
         'F':list('aaabbb')
})

print (df)
   A  B  C  D  E  F
0  a  4  7  1  5  a
1  b  5  8  3  3  a
2  c  4  9  5  6  a
3  d  5  4  7  9  b
4  e  5  2  1  2  b
5  f  4  3  0  4  b

df1 = df.select_dtypes(np.number).idxmax()
print (df1)
B    1
C    2
D    3
E    3
dtype: int64

Upvotes: 6

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