CODEWITHSUNDEEP
pythonpandas
Jammy
Jammy

Reputation: 423

Pandas conditional multiplication

I have the following pandas DataFrame and I'm trying to do a little clean up. In my case, I'm receiving product 'a' data in raw decimal form whereas I need it to be percent to align with the formatting for the other products.

How do I scale the success_rate and market_penetration_rate by 100 in my dataframe only in cases when product = a?

import pandas as pd

df = pd.DataFrame({'product' : ['a', 'a', 'c', 'c', 'd', 'b', 'a', 'b', 'c'],
               'success_rate' : [0.2, 1.0, 67.0, 71.5, 23.2, 71.0, 0.44, 59.3, 12.7],
               'market_penetration_rate' : [0.82, 0.64, 77.5, 12.5, 22.5, 88.0, 0.34, 98.2, 87.4]})

+----------+--------------+-------------------------+
| product  | success_rate | market_penetration_rate |
|          |              |                         |
| a        | 0.2          | 0.82                    |
|          |              |                         |
| a        | 1            | 0.64                    |
|          |              |                         |
| c        | 67           | 77.5                    |
|          |              |                         |
| c        | 71.5         | 12.5                    |
|          |              |                         |
| d        | 23.2         | 22.5                    |
|          |              |                         |
| b        | 71           | 88                      |
|          |              |                         |
| a        | 0.44         | 0.34                    |
|          |              |                         |
| b        | 59.3         | 98.2                    |
|          |              |                         |
| c        | 12.7         | 87.4                    |
+----------+--------------+-------------------------+

Upvotes: 4

Views: 10622

Answers (2)

Happy001
Happy001

Reputation: 6383

In [7]: print df.loc[df['product']=='a', ['market_penetration_rate', 'success_rate']] * 100
   market_penetration_rate  success_rate
0                       82            20
1                       64           100
6                       34            44

Or if you want to scale in-place, 

In [8]: df.loc[df['product']=='a', ['market_penetration_rate', 'success_rate']] *= 100

Upvotes: 16

jtitusj
jtitusj

Reputation: 3086

try this:

df.apply(lambda row: row[['success_rate', 'market_penetration_rate']]*100 if row['product'] == 'a' 
     else row[['success_rate', 'market_penetration_rate']], axis=1)

Upvotes: 1

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