Description
I'm proposing to extend Expand Dict dataframe transformation that implements Polars' column unnest functionality. Currently, marimo has an Expand Dict feature, but it fails when a column contains null values, throwing the error: 'NoneType' object cannot be converted to 'PyDict'.
Suggested solution
The native Polars method df.unnest("column_name") handles null values gracefully without failing. This new transformation would leverage the Polars unnest method directly, making it more robust when working with dictionaries that contain null values.
It would allow users to flatten nested dictionaries into separate columns without having to pre-process the data to handle null values.
I am willing to submit a PR to implement this functionality if desired.
Alternative
No response
Additional context
Error message:
Description
I'm proposing to extend
Expand Dictdataframe transformation that implements Polars' column unnest functionality. Currently, marimo has anExpand Dictfeature, but it fails when a column contains null values, throwing the error:'NoneType' object cannot be converted to 'PyDict'.Suggested solution
The native Polars method df.unnest("column_name") handles null values gracefully without failing. This new transformation would leverage the Polars unnest method directly, making it more robust when working with dictionaries that contain null values.
It would allow users to flatten nested dictionaries into separate columns without having to pre-process the data to handle null values.
I am willing to submit a PR to implement this functionality if desired.
Alternative
No response
Additional context
Error message:
