Splitting two integer values in a cell separated by a comma using Pandas-CodePudding

I have this column with some cells that have two values, first value is price after discount and second value is price after discount. I need to separate these values into two cells before and after discount I have tried the following methods but neither of them works so if anyone have any suggestions how to make or how to edit the code to do it.
Column Example:
Price
row 1: 79.9,99.9
row 2: 59.9
row 3: 49.9,89.9
row 4: 59.9

Method 1:

for z in x['1Month Price']:
x['1Month Price'].split(',')

Error:

    AttributeError                            Traceback (most recent call last)
<ipython-input-32-1b04b6fed466> in <module>
----> 1 x['1_Month_bf'] = x['1Month Price'].split(',', expand = True)
      2 x.head()

~\anaconda3\lib\site-packages\pandas\core\generic.py in __getattr__(self, name)
   5463             if self._info_axis._can_hold_identifiers_and_holds_name(name):
   5464                 return self[name]
-> 5465             return object.__getattribute__(self, name)
   5466 
   5467     def __setattr__(self, name: str, value) -> None:

AttributeError: 'Series' object has no attribute 'split'

Method 2:

    x['1_Month_bf'] = x['1Month Price'].apply(lambda z: z.split(',')[0])
x.head()

Error:

AttributeError                            Traceback (most recent call last)
<ipython-input-33-aa7ce98376af> in <module>
----> 1 x['1_Month_bf'] = x['1Month Price'].apply(lambda z: z.split(',')[0])
      2 x.head()

~\anaconda3\lib\site-packages\pandas\core\series.py in apply(self, func, convert_dtype, args, **kwds)
   4136             else:
   4137                 values = self.astype(object)._values
-> 4138                 mapped = lib.map_infer(values, f, convert=convert_dtype)
   4139 
   4140         if len(mapped) and isinstance(mapped[0], Series):

pandas\_libs\lib.pyx in pandas._libs.lib.map_infer()

<ipython-input-33-aa7ce98376af> in <lambda>(z)
----> 1 x['1_Month_bf'] = x['1Month Price'].apply(lambda z: z.split(',')[0])
      2 x.head()

AttributeError: 'int' object has no attribute 'split'

CodePudding user response：

Try with str.split. First convert each rows as string to avoid the 2nd error then split your strings then convert them as float.

df[['discount', 'price']] = (
    df['1Month Price'].astype(str).str.split(',', expand=True).astype(float)
)
print(df)

# Output
  1Month Price  discount  price
0    79.9,99.9      79.9   99.9
1         59.9      59.9    NaN
2    49.9,89.9      49.9   89.9
3         59.9      59.9    NaN

CodePudding user response：

df[['Price A', 'Price B']] = df['Price'].str.split(',', expand=True)

Outcome

   Price       Price A  Price B
0  79.9,99.9    79.9     99.9
1       59.9    59.9     None
2  49.9,89.9    49.9     89.9
3       59.9    59.9     None