split a series into multiple pandas columns

I have a pandas dataframe, one of the columns has a series in there. The structure is as follows:

Date          Col1
2022-01-02    'Amt_Mean                 2022.0\nAmt_Med                   5.0\nAmt_Std     877.0\ndtype: float64'


2022-01-03    'Amt_Mean                 2025.0\nAmt_Med                   75.0\nAmt_Std     27.0\ndtype: float64'

I want to reshape this such that I get the following output

Date        Amt_Mean   Amt_Med   Amt_Std
2022-01-02  2022.0     5.0       877.0
2022-01-03  2025.0     75.0      27.0

How can I achieve this? I tried df['Col1'][0][1] which gives me the first amount and I can potentially for loop it, but seems there should be a more easy (pythonic) way of doing this.
Thanks!

>Solution :

Some string processing to convert each string into a dict, convert those to a dataframe, and concatenate that with the original:

new_df = pd.DataFrame([dict(re.split(r'\s+', y) for y in x.split('\n')[:-1]) for x in df['Col1']])
df = pd.concat([df.drop('Col1', axis=1), new_df], axis=1)

Output:

>>> df
         Date Amt_Mean Amt_Med Amt_Std
0  2022-01-02   2022.0     5.0   877.0
1  2022-01-03   2025.0    75.0    27.0