Pandera DataFrame support

Environment data

VS Code version: 1.94.2
Data Wrangler Extension version (available under the Extensions sidebar): 1.12.0
Jupyter Extension version (available under the Extensions sidebar): v2024.9.1
Python Extension version (available under the Extensions sidebar): v2024.16.1
OS (Windows | Mac | Linux distro) and version: Windows Subsystem for Linux - Ubuntu 20.04
Pandas version: 2.2.2
Python and/or Anaconda version: 3.11
Type of virtual environment used (N/A | venv | virtualenv | conda | ...): venv

Expected behaviour

Pandera is a framework to perform data validation/sanitation on Pandas DataFrames, similar to Pydantic for dataclasses. Validation can be performed by casting a Pandas DataFrame to the Pandera DataFrame subclass. As the Pandera DataFrame is a subclasses of the Pandas Dataframe, it should support all functionality of Pandas DataFrames and thus Data Wrangler should also be able to process them.

Actual behaviour

When trying to inspect a Pandera DataFrame with Data Wrangler the following error comes up:

Type 'pandera.typing.pandas.DataFrame' is not currently supported in Data Wrangler. Please open a feature request on the Data Wrangler GitHub repository.

Steps to reproduce:

import pandas as pd
import pandera as pa
from pandera.typing import DataFrame

class ExampleModel(pa.DataFrameModel):
    pass

A = pd.DataFrame(["a", "b", "c"])

B = DataFrame[ExampleModel](A)

One way to bypass the problem is to cast the Pandera DataFrame back to a Pandas DataFrame, after which it can be inspected with Data Wrangler. However, this is quite cumbersome to do every time you want to inspect a Pandera DataFrame.

C = pd.DataFrame(B)

microsoft / vscode-data-wrangler