PNDSPY1026¶
Message Pandas < pandas.core.arrays.datetimes.DatetimeArray.tz_localize > 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 ambiguous or nonexistent are set to a non-default value. N if timezone format is not supported. Only timezones listed in pytz.all_timezones are supported. For example, UTC is supported but UTC+/-
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_localize
Output¶
The SMA adds the EWI PNDSPY1026 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: PNDSPY1026 => pandas.core.arrays.datetimes.DatetimeArray.tz_localize 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_localize
Recommended fix¶
Timezone handling difference: N if ambiguous or nonexistent are set to a non-default value. N if timezone format is not supported. Only timezones listed in pytz.all_timezones are supported. For example, UTC is supported but UTC+/-
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.