Converting string to date format 0000-00-00 before extracting year and month information

I have a string column (object type):

Date
2020-06-15
2019-07-23
Data non available

How can I convert the string Data non available and/or any missing values to the format 0000-00-00, before extracting the month and the year?

I can convert the Date column to datetime, and extract information on year and month from the other rows, but then I get this error:

ParserError: Unknown string format: Data not available

My code:

df['Date'] = pd.to_datetime(df['Date'])
df['Date_Year'], df['Date_month'] = df['Date'].dt.year, df['Date'].dt.month

Expected output:

Date             Date_Year        Date_month
2020-06-15          2020              06
2019-07-23          2019              07
Data non available  0000              00

>Solution :

I’d replace Data not available with NaT (Not A Time – NaN equivalent for dates/times) before you call to_datetime:

df['Date'] = df['Date'].replace({'Data non available': pd.NaT})

Then

df['Date'] = pd.to_datetime(df['Date'])
df['Date_Year'], df['Date_month'] = df['Date'].dt.year, df['Date'].dt.month

Output:

>>> df
        Date  Date_Year  Date_month
0 2020-06-15     2020.0         6.0
1 2019-07-23     2019.0         7.0
2        NaT        NaN         NaN