Increase the value of a column based on values in another column

user_14760141 0
Viewed 38

I am trying to increase the price of on the red pens in this example by 10%. Below is what I have have tried but it increases all the prices once it finds a match

import pandas as pd


df = pd.DataFrame({'item':['red ballpoint pen','red felt tip pen', 'blue ballpoint pen','red eraser',],
                   'price':[1.50,2.00,1.50,.50]})
for x in df['item']:

if 'red' in x and 'pen' in x:
    df['price'] =  df['price']*.10 + df['price']

I can filter the item column and get the pens but I cannot figure out how to update the price in place without increasing the price on all items

Any help would be greatly appreciated

pandas python
3 Answers

Use loc and str.contains:

m = df['item'].str.contains('red') & df['item'].str.contains('pen')
df.loc[m, 'price'] *= 1.10
user_25356110

This will use np.where() to find where both pen and red exist

df['price'] = np.where((df['item'].str.contains('red')) & (df['item'].str.contains('pen')), df['price'] * 1.10, df['price'])
df
user_177504310

You can just use pandas to do this in a oneliner:

df.loc[df.item.str.contains('pen') & df.item.str.contains('red'), 'price'] *= 1.1
user_74758380
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