dataframes

In pandas assert_frame_equals has the check_exact flag which allows for inexact number comparisons with tolerances defined by the rtol (relative tolerance) and atol (absolute tolerance). This would be nice to have in polars as well, since it allows for ignoring floating point rounding error

Describe the bug
pa.errors.SchemaErrors.failure_cases only returns the first 10 failure_cases

• I have checked that this issue has not already been reported.
• I have confirmed this bug exists on the latest version of pandera. 0.6.5
• (optional) I have confirmed this bug exists on the master branch of pandera.

Note: Please read [this guide](https://matthewrocklin.c

Thanks for this library, it made my pandas workflow clean & easy to maintain.

Feature Request:
pd.merge is a common operation when dealing with 2 or more data frames & pipeline stage for this is missing.
Currently, I am implementing a custom pipeline stage pdp.Merge from PdPipelineStage & would like to contribute.

Currently we don't test (or document) that Eland should work with data streams, we should probably test that everything works properly.

Code coverage should be added to the Travis config (perhaps the cabal file and/or the stack options need to be changed in order to account for hpc coverage generation); currently in Travis there is only a project key.
This tool uploads hpc coverage reports to codecov.io .

Add a few useful date/time types from time (https://hackage.haskell.org/package/time) , e.g.

• POSIXTime
• Date
  etc.

A checklist for where to add things :

• prim constructors go in here : https://github.com/ocramz/heidi/blob/master/src/Data/Generics/Encode/Internal/Prim.hs#L25
• Heidi instances go here : https://github.com/ocramz/heidi/blob/master/src/Data/Generics