Niels Bantilan

hi @benjaminbluhm, sorry for the delay in responding! So the main function to look at is [`_serialize_dataframe_stats`](https://github.com/pandera-dev/pandera/blob/dev/pandera/io.py#L70-L84) Right now it outputs a `dict` where keys are check names and values...

hey @cdagnino, I'd recommend using built-in checks or explicitly handle na case in lambda function `element_wise=True`. The issue you're coming up against is happening because the element-wise function doesn't know...

hi @parayamelo can you provide a minimally reproducible example of the behavior you're seeing?

@cdagnino yes I think a better error message would help here. The output of an element-wise `Check` function must always a boolean, so outputing an NA value should not be...

hi @suned sorry for the long reply-time! currently this isn't quite possible, but we're working on adding more flexibility to the data synthesis strategy functionality: - https://github.com/pandera-dev/pandera/issues/561 - https://github.com/pandera-dev/pandera/discussions/648 Will...

hi @RNKuhns, can you elaborate on the column checks for which you want to generate data? It'll help with the design and implementation of making the data synthesis strategy customization...

hi @RNKuhns feel free to find a time here! https://calendly.com/niels-bantilan/30min

high-level approach: 1. Generate "multi-column" data strategy 2. Generate single column data strategy 3. Somehow merge the two dataframes tactically: 1. segment the dataframe schemas into two separate schemas using...

Hi @will-gp thanks for the bug report, I do think the use case you describe should be supported. > However, the following calls to infer_dtype would produce a dtype estimate...

> However, after further thinking, I think that overcomplicates things. I think just changing skipna from True to False would suffice. Let me know what you think. Agreed! I think...