Applying function to multiple columns in pandas dataframe to make 1 new column

Question

I’m trying to apply a function that:

takes the value of each cell in a column divided by the mean of its respective column.

Then create a column called [‘Score’] that has the sum of each cell value in a row computed from step 1.

My code so far:

import pandas as pd
df = pd.DataFrame(pd.read_excel('fruits.xlsx'))
def func(column):
    out = df[column].values / df[column].mean()
    return out

Im really unsure of how to execute this with pandas properly.

Asked By: mosesjs

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Source

Answer 1

Try this one will calculate exactly what you need in one single line:

df['Score'] = df.apply(lambda x: sum([x[i]/df[i].mean() for i in df.columns]),axis=1)

Answered By: lackti

Answer 2

Can you post the output to:

df[0]

or

df.head()

This will help me answer your question properly.

Answered By: Jasper Tresidder

Answer 3

you can make the output as a column in the dataframe

df["Score"] = df[<col_name>] / df[<col_name>].mean()

and you can use

df["Score"] = df[<col_name>].values / df[<col_name>].mean()

I tested both and both gave me the same output in the dataframe

Answered By: Mahmoud Abdelaziz

Answer 4

You can do it like this

df = pd.DataFrame([[1,2,3],[4,5,6],[7,8,9]], columns=['a', 'b', 'c'])
df['score'] = df.div(df.mean()).sum(axis=1)

Output

    a   b   c   score
0   1   2   3   1.15
1   4   5   6   3.00
2   7   8   9   4.85

Answered By: bui

Applying function to multiple columns in pandas dataframe to make 1 new column

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