This PR handles all the cases of inconsistent datetime related pd.to_numeric handling from Issue 42380 and is compatible with pandas/io/parsers/base_parser.py

1. pandas/_libs/lib.pyx contains the core/common logic for datetime related pd.to_numeric handling, and is a singular place which handles scalar values, pd.Datetime, pd.TimeStamp and Series(input_value).apply(partial(to_numeric))
   

   pandas/pandas/_libs/lib.pyx

   Line 2453 in 083f01a

   elif convert_datetime and (PyDate_Check(val) or cnp.is_datetime64_object(val)):

2. pd.Timedelta is returned as the direct value, and pd.Timestamp with Timezones are handled with the default np.datetime64 UTC conversion.
   


3. The removal of elif lib.is_np_dtype(values_dtype, "mM"): values = values.view(np.int64) in pandas/core/tools/numeric.py addresses the bug where int value of NaT are returned (Issue 42380).

4. Introduces convert_datetime flag in maybe_convert_numeric, as this function is used by both pd.to_numeric and the base_parsers, e.g., excel reader. The default behavior for pd.to_numeric on datetimes is to convert to numeric, while the default behavior on base_parsers is to not convert.

• closes BUG: pd.to_numeric has an inconsistent behavior for datetime objects #43280
• Passes tests from BUG: pd.to_numeric has an inconsistent behavior for datetime objects #43280 and related linked PR discussions
• [] All code checks passed.
• Added an entry in the latest doc/source/whatsnew/v3.0.0.rst file