Convert the account_opened column to datetime, while making sure the date format is inferred and that erroneous formats

Here's the code to convert the account_opened column to datetime, while making sure the date format is inferred and that erroneous formats that raise error return a missing value: ```python # Print the header of account_opened print(banking['account_opened'].head()) # Convert account_opened to datetime banking['account_opened'] = pd.to_datetime(banking['account_opened'], # Infer datetime format infer_datetime_format=True, # Return missing value for error errors='coerce') ``` In this code, we use the `pd.to_datetime()` function to convert the `account_opened` column to datetime. We pass the column as the first argument to the function. We set the `infer_datetime_format` parameter to `True` to allow Pandas to automatically infer the datetime format from the data. We set the `errors` parameter to `'coerce'` to return a missing value (NaT) for any erroneous format that raises an error during conversion. After running this code, the `account_opened` column will be converted to datetime format with any erroneous formats replaced with missing values.