Pandas, replicate every row that have a more than one value

Question

I have a pandas Data Frame.

I want to replicate every row in the Data Frame that in the column 'quantity' has more than one and change the value of that row to -1 for every created until it reaches one.

            Item  Weight  Bags    Must  quantity  must quantity  bags column  length assigned bag
0     planes bag    8.50  planes   v       1              1          6                None
1  Full Bandolera   3.76  planes   v       3              2          6                None
2  tail             0.30  planes  <NA>     3              2          6                None
3  central wing     1.08  planes  <NA>     3              2          6                None
4  engine           0.44  planes  <NA>     3              2          6                None
5  height steer     0.12  planes  <NA>     3              2          6                None
6  dihedral         0.40  planes  <NA>     3              2          6                None   
7  pods bag         8.72  pods     v       1              1          4                None
8  Pod              1.74  pods     v       3              2          4                None
9  optic            0.86  pods     v       2              2          4                None
10 thermal          1.20  pods     v       3              2          4                None

So, for example, the Full Bandolera row's quantity will become 1 and there will be two duplicates of it.

            Item  Weight  Bags    Must  quantity  must quantity  bags column  length assigned bag
0     planes bag    8.50  planes   v       1              1          6                None
1  Full Bandolera   3.76  planes   v       1              2          6                None
2  Full Bandolera   3.76  planes   v       1              2          6                None
3  Full Bandolera   3.76  planes   v       1              2          6                None
4  tail             0.30  planes  <NA>     3              2          6                None
5  central wing     1.08  planes  <NA>     3              2          6                None
6  engine           0.44  planes  <NA>     3              2          6                None
7  height steer     0.12  planes  <NA>     3              2          6                None
8  dihedral         0.40  planes  <NA>     3              2          6                None   
9  pods bag         8.72  pods     v       1              1          4                None
10  Pod              1.74  pods     v       3              2          4                None
11 optic            0.86  pods     v       2              2          4                None
12 thermal          1.20  pods     v       3              2          4                None

So far, Iv'e got this code:

    def multiply_row(cls):
        print(cls.df.dtypes)
        for row in cls.df.iterrows():
            while row['quantity'] > 1:
                row_to_list = list(row)
                listed_row = row_to_list.copy()
                add_to_df = tuple(listed_row)
                cls.df.append(add_to_df)
                row['quantity'] = row['quantity'] - 1
                return cls.df

output:

 while row['quantity'] > 1:
TypeError: tuple indices must be integers or slices, not str


Item                   string
Weight                float64
Bags                   string
Must                   object
quantity                int64
must quantity           int64
category               object
bags column length      int64
assigned bag           object
assigned_bag           object

I'm very not sure of the method I wrote, I'm very new to pandas.

UPDATE:

using Quang Hoang's answer, no errors are being raised.

Yet, the Data Frame remains the same.

    def multiply_row():
        for idx, row in df.iterrows():
            while row['quantity'] > 1:
                (df.loc[df.index.repeat(df.quantity)]
                 .assign(quantity=1))
                return df

returns the exact same Data Frame.

Answer 1

I think repeat :

(df.loc[df.index.repeat(df.quantity)]
   .assign(quantity=1)
 )