Is there a way to add or subtract to an existing dataframe?
For example, given the code below:
import pandas as pd
Apple= pd.DataFrame({'Product':['MacBook', 'iPhone', 'iPad', 'Apple Watch'],
'Inventory':['999', '333', '666', '190']})
Is there a way to add 150 to an existing inventory so that the number of Apple Watches is 340?
Use loc along with a boolean selection to update the column:
Apple.loc[Apple.Product.eq('Apple Watch'), 'Inventory'] += 150
Product Inventory
0 MacBook 999
1 iPhone 333
2 iPad 666
3 Apple Watch 340
In the example you've provided in your question, Inventory contains strings. If this is the same in your actual data, you need to cast to int first:
Apple.Inventory = Apple.Inventory.astype(int)
First convert your series of strings to an int series:
df['Inventory'] = df['Inventory'].astype(int)
You can then use pd.DataFrame.loc:
df.loc[df['Product'] == 'Apple Watch', 'Inventory'] += 150
Alternatively, you can make Product your index and then update:
df = df.set_index('Product')
df.loc['Apple Watch', 'Inventory'] += 150
Using either method, if you have multiple products with the same name, their inventory will each be increased by 150.
if you define your items as int , you can do it this way:
import pandas as pd
Apple= pd.DataFrame({'Product':['MacBook', 'iPhone', 'iPad', 'Apple Watch'],
'Inventory':['999', '333', '666', 190]})
Apple.Inventory[Apple.Product == 'Apple Watch'] += 150
print(Apple)
Apple.loc[Apple.Product.eq('Apple Watch'), 'Inventory'] += 150pandas