PNDSPY1232¶

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.

Missing or Unsupported Parameters: errors

Reason: N if errors is given or converting from string type.

Scenario¶

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

import pandas as pd

df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})
result = pd.to_timedelta(df)

import snowflake.snowpark.modin.pandas as pd

#EWI: PNDSPY1232 => pandas.core.tools.timedeltas.to_timedelta has a partial mapping, with few scenarios not supported. Check Snowpark pandas documentation for more detail.
df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})
result = pd.to_timedelta(df)

Recommended fix¶

The parameter errors is not supported in Snowpark pandas. If your code uses this parameter, consider one of these approaches:

1. Remove the parameter: If the parameter is not essential for your use case, simply remove it from the function call.

2. Use default behavior: The function will work with default values for the unsupported parameter.

3. Post-process with native pandas: If the parameter is critical, collect the result using .to_pandas() and apply the operation with native pandas:

   # Convert to native pandas for unsupported parameter
   result = df.to_pandas().to_timedelta(errors=value)
   

   Copy

Data type consideration: N if errors is given or converting from string type.

Ensure data types are compatible:

• Check column dtypes with df.dtypes before the operation

• Use .astype() to convert columns to expected types

• Numeric operations may require explicit casting: df['col'].astype(float)

Additional recommendations¶

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