python - Duplicate row based on value in different column

Question

I have a dataframe of transactions. Each row represents a transaction of two item (think of it like a transaction of 2 event tickets or something). I want to duplicate each row based on the quantity sold.

Here's example code:

# dictionary of transactions

d = {
    '1': ['20',  'NYC', '2'],
    '2': ['30',  'NYC', '2'],
    '3': ['5',   'NYC', '2'],
    '4': ['300', 'LA',  '2'],
    '5': ['30',  'LA',  '2'],
    '6': ['100', 'LA',  '2']
}

columns=['Price', 'City', 'Quantity']

# create dataframe and rename columns

df = pd.DataFrame.from_dict(
    data=d, orient='index'
)
df.columns = columns

This produces a dataframe that looks like this

Price   City    Quantity
20       NYC         2
30       NYC         2
5        NYC         2
300      LA          2
30       LA          2
100      LA          2

So in the case above, each row will transform into two duplicate rows. If the 'quantity' column was 3, then that row would transform into three duplicate rows.

Answer 1

Answer by using repeat

df.loc[df.index.repeat(df.Quantity)]
Out[448]: 
  Price City Quantity
1    20  NYC        2
1    20  NYC        2
2    30  NYC        2
2    30  NYC        2
3     5  NYC        2
3     5  NYC        2
4   300   LA        2
4   300   LA        2
5    30   LA        2
5    30   LA        2
6   100   LA        2
6   100   LA        2