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#### Design Data Types Library That Supports Both PySpark & Pandas
Hi, I have multiple data types I commonly work with, sometimes in pandas and sometimes in pyspark.
I don't want to create 2 pan…
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**Describe the bug**
A clear and concise description of what the bug is.
- [X] I have checked that this issue has not already been reported.
- [X] I have confirmed this bug exists on the latest v…
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**Describe the bug**
A clear and concise description of what the bug is.
Pydantic models always throw `is_instance_of` validation errors if a `pandera.typing.pyspark.DataFrame` type is used. Pydan…
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Right now, `pandera`'s type-checking support is done using a special `pandera.typing.DataFrame` that is generic over a schema. This is a problem, since it causes lots of confusion with type-checkers t…
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**Is your feature request related to a problem? Please describe.**
Currently, strategies are limited by the `hypothesis.extras.pandas` convention of how to define a dataframe. Namely, the strategy …
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**Describe the bug**
Pandas handles the default `int` type differently on Windows and Linux. On Linux`int` is interpreted as `int64` but on Windows as `int32`. Since Pandera always maps `int` to `…
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**Describe the bug**
A clear and concise description of what the bug is.
- [*] I have checked that this issue has not already been reported.
- [*] I have confirmed this bug exists on the latest v…
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Hi to whom it concerns
Thanks to the great work by the pandera's team, it really helps me with validating a huge number of datasets.
I encountered the following issue.
Context Screenshot:
![pa…
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I would like to use pandera to validate columns that are missing in the dataframe but are nullable, so they can be safely added. Would it be possible? Perhaps with some new config key like `coerce_col…
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**Is your feature request related to a problem? Please describe.**
Pandera doesn't officially support python 3.11 (as reflected in CI/CD test suite)
**Describe the solution you'd like**
Add p…