CODEWITHSUNDEEP
pythonpython-3.xpandas
a1234
a1234

Reputation: 821

pandas max value in row & return df with value and column name

I have the following dataframe:

    a    b    c    d    e
    1   .90  .95  .83  .56
   .95  .96  .87  .83  .63
   .83  .87  .83  .95  .81

How do I find the max value per row and the column it came from, so that it looks like:

a   1
b  .96
d  .95

Upvotes: 3

Views: 3277

Answers (4)

Abishek Aditya
Abishek Aditya

Reputation: 812

maxRow = df.idxmax(1)
maxValue = df.max(1)
print(pd.concat([maxRow , maxValue],1))

The maxRow variable gives the id of the maximum valued row in the dataframe,the 1 to to set the axis to row instead of column, Similarly, the maxValue gets the maxValues of the rows pd.concat is to zip these two lists into a dataframe

Upvotes: 1

anky
anky

Reputation: 75080

using np.argmax and df.lookup:

s=pd.Series(df.columns[np.argmax(df.values,axis=1)])
final=pd.DataFrame(df.lookup(s.index,s),s)

Upvotes: 5

Celius Stingher
Celius Stingher

Reputation: 18367

You can use idxmax() function:

import pandas as pd
a = {'a':[100,95,83],'b':[90,96,87],'c':[95,87,83],'d':[83,83,95],'e':[56,63,81]}
df = pd.DataFrame(a)
print(df)

Dataframe looks like this:

     a   b   c   d   e
0  100  90  95  83  56
1   95  96  87  83  63
2   83  87  83  95  81

Using the function idxmax we get which column does the max value per row belong:

print(df.idxmax(axis=1))

Output:

0    a
1    b
2    d

Concatenating it with the original dataframe, to the get the corresponing value, given the column it belongs to.

df_result = pd.concat([df.idxmax(axis=1),df.max(axis=1)],axis=1)
print(df_result)

Output:

   0    1
0  a  100
1  b   96
2  d   95

Upvotes: 2

Code Different
Code Different

Reputation: 93151

Try this:

result = df.max(axis=1)
result.index = df.idxmax(axis=1)

Upvotes: 5

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