How can I divide each row with a particular column's value at that row?

Question

Suppose I have this table;

A  B  C
2  1  4
1  8  2
...

I try to divide each row with column C value, then I get;

A     B    C
0.5  0.25  4
0.5   4    2

How can I do it in pandas dataframe

Answer 1

Use the built in div function and pass param axis=0 :

In [123]:

df[['A','B']] = df[['A','B']].div(df['C'],axis=0)
df
Out[123]:
     A     B  C
0  0.5  0.25  4
1  0.5  4.00  2

Answer 2

You can simply do df[col] = df[col] / df[col2] where col and col2 could be 'A' and 'C' , for example.

The code below will divide A and B by C in turn. You can ignore the first part, that's just be setting the DataFrame up.

import pandas as pd
from io import StringIO

s = '''A  B  C
2  1  4
1  8  2'''

df = pd.read_csv(StringIO(s), sep='\s+')
print(df)
#    A  B  C
# 0  2  1  4
# 1  1  8  2

df['A']  = df['A'] / df['C'] # or df['A']  /= df['C']
df['B'] = df['B'] / df['C'] # or df['B'] /= df['C']
print(df)
#      A     B  C
# 0  0.5  0.25  4
# 1  0.5  4.00  2

To make this easier (if you have multiple columns) you could have a list of column names ['A', 'B'] and then iterate over it

for x in ['A', 'B']:
    df[x] /= df['C']

Answer 3

for x in ['A', 'B']: df[x] /= df['C']

Does the 'C' shoulbe in the last column? Because loop stops when df('C')/df('C')