PNDSPY1025¶

Message Pandas < pandas.core.arrays.datetimes.DatetimeArray.tz_convert > has a partial mapping with a few scenarios not supported in Snowpark.

Category Warning

Description¶

This issue appears when the SMA detects the use of a pandas element that has a direct equivalent in Snowpark pandas, but some scenarios might behave differently than pandas.

Reason: N if timezone format is not supported. Only timezones listed in pytz.all_timezones are supported. For example, UTC is supported but UTC+/-, such as UTC+09:00, is not supported.

Scenario¶

A method with a few scenarios that aren’t supported in Snowpark.

Input¶

The following example shows a method with a few unsupported scenarios in Snowpark.

import pandas as pd

s = pd.Series(pd.date_range('2023-01-01', periods=3))
result = s.dt.tz_convert

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Output¶

The SMA adds the EWI PNDSPY1025 to the output code to let you know that this element has a few scenarios that aren’t supported in Snowpark.

import snowflake.snowpark.modin.pandas as pd

#EWI: PNDSPY1025 => pandas.core.arrays.datetimes.DatetimeArray.tz_convert has a partial mapping, with few scenarios not supported. Check Snowpark pandas documentation for more detail.
s = pd.Series(pd.date_range('2023-01-01', periods=3))
result = s.dt.tz_convert

Copy

Recommended fix¶

Timezone handling difference: N if timezone format is not supported. Only timezones listed in pytz.all_timezones are supported. For example, UTC is supported but UTC+/-, such as UTC+09:00, is not supported.

When working with timezones in Snowpark pandas:

Ensure your timezone strings are valid IANA timezone names (e.g., ‘UTC’, ‘America/New_York’)
Test timezone conversions with sample data before running on full dataset
Consider using .to_pandas() for complex timezone operations if results differ

Additional recommendations¶

Check the Snowpark pandas documentation to verify which scenarios aren’t supported for that specific element.