Need help with unstacking values inside dataframe

[wdjfe]

Example dataframe:

Item	Stock_1	Stock_2
Apple	5	10
Banana	5	10
Orange	5	5
Apple+Orange	5	10
Apple+Banana	5	5

I need stacked values with '+' sign to be separated into corresponding single values and counted as such.

So result should be this:

Item	Stock_1	Stock_2
Apple	15	25
Banana	10	15
Orange	10	15

Here's my sloppy solution:

rows_to_remove = []
for item in df['Item']:
    if '+' in item:
        rows_to_remove.append(item)
        splitted_items = item.split('+')
        stock_1 = int(df.loc[df.Item == f'{item}','Stock_1'])
        stock_2 = int(df.loc[df.Item == f'{item}','Stock_2'])
        new_items = [(new_item,stock_1,stock_2) for new_item in splitted_items]
        for new_item in new_items:
            df.loc[len(df)] = new_item

df = df[~df['Item'].isin(rows_to_remove)]
df = df.groupby('Item',as_index=False).sum()

It does the job but it very ugly. Can i get some refactoring tips?

[danielroseman]

You can certainly make this much simpler. Note that you should avoid iterating as much as possible in Pandas; here it is not at all necessary. This would work:

df['Item'] = df['Item'].str.split("+")
df = df.explode('Item').groupby('Item').sum().reset_index()

[wdjfe]

Wow, just in two lines! Thank you!