fix: convert pandas Timestamp to Snowflake-compatible string in write_pandas (closes #991)

[botbikamordehai2-sketch]

What

When writing a pandas DataFrame with a datetime64[ns] column to Snowflake using write_pandas, the generated SQL includes timestamps in a format that Snowflake interprets as an invalid date (e.g., '2013-02-10 00:00:00' may be misformatted or include microseconds/timezone that Snowflake cannot parse). The issue is in _extract_schema_and_data_from_pandas_df where Timestamp objects are converted to strings without explicit formatting, causing invalid date errors.

Fix

In the _extract_schema_and_data_from_pandas_df function, when handling pd.Timestamp values, convert them to a string in the ISO 8601 format '%Y-%m-%d %H:%M:%S.%f' (or using '%Y-%m-%d %H:%M:%S' for non-microsecond) which is a valid Snowflake timestamp literal. For timezone-aware timestamps, first normalize to UTC and then remove the timezone to align with Snowflake's default behavior of ignoring timezone offsets. This ensures that write_pandas generates safe SQL literals that Snowflake can parse.

Closes #991

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