Niels Bantilan

Not sure if the `pa.date32` type is important in your use case, but a workaround here would be to convert all the columns containing dates into pandas-supported `datetime64` before calling...

See discussion in #849: basically this issue is blocked by `pyproject.toml` and poetry having better compatibility with setuptools.

thanks for you help @roshcagra! yes the approach described by @jeffzi is the way to go. Out of curiosity, I have a few questions (as someone who hasn't used `geopandas`...

Thanks for the detailed analysis @m-richards, and I'm glad you're finding pandera useful! It seems like GeoSeries and GeoDataFrame already does a lot of heavy lifting in terms of checking...

Hi @bukosabino, yes! this is an open issue https://github.com/pandera-dev/pandera/issues/393. Would you be open to making a contribution on this front?

> Also, any option to generate the SchemaModel using [infer_schema](https://pandera.readthedocs.io/en/stable/reference/generated/pandera.schema_inference.infer_schema.html)? Once the `DataFrameSchema.to_model` method is implemented it should be pretty straightforward to output a `SchemaModel` from `infer_schema`. Another related feature...

closing this in to merge with #393

hey @Anders-E, the user warning you're seeing is because _checks_ should be reusable but by assigning a `Column` object to a variable ```python positive_check = pa.Column(pa.Int, pa.Check.greater_than_or_equal_to(0)) ``` You're basically...

hey @Anders-E, a contribution on that front would be very welcome. I think better than improving the warning message, we can make this case invalid: - in `DataFrameSchema.__init__`, check whether...

yes, please do! make sure to base your changes off of the `dev` branch and make a PR against that branch when it's ready! Also be sure to check out...