Pandera

Release Notes

- this release drops support for python 2.7: 4d38a4db3eefc13a940b6e47f848583df6f1979d
- add explanatory error message to check_input decorator: c1a36161cc4b94d47320a6b940bbfad71b631ba0
- add test code snippets to sphinx documentation: ca5b39d329b3572d2889dd52a41ea97da6ef1534
- add type hinting: f67050dd2a40cc03ba790300062317198fbc240c
- modularize pandera code: ffd57d85d4983bb085ca0cd0af1fba59970ff6db
- more builtin data type support: b01eef07015dc76cae4b2a5be060417be3288c11
- add citation information: 60612547ec136bf3b52a6ba89c71970c39f2ea4d
- update repo links : `cosmicBboy -> pandera-dev`: e6782f1cb213ed3135fb30768c8edf1c6fa8c536
- add dev installation instructions: f7950ad9636a971beffc0054518871aeb937faab
- improve formatting and wording of sphinx documentation: 7310d0debe94e762d36f30d95d016bf1efb8e51c
- make SchemaError message formatting functions private: fc071d656c40b1063921aecc14997ed2b90b1072
- add docstrings to error classes: ed4e8f846d649b6b89dc13d1fc88ba8c3d0bfc2a
- add human-readable __str__ and __repr__ methods to DataFrameSchema: 954d8a21497ada4b77d02fd556f8646a0c618a28
- update requirements.txt, remove enum34: db87b21f3672ae7d2475427454523e68f8793c1a

Release Notes

- Added support for `MultiIndex` column and and index validation
- `DataFrameSchema` can validate head, tail, or a random sample of dataframe
- `Check`s and `Hypothesis` checks now support dataframe-level (wide) data validation

Add testing support for python 3.7, improved documentation

This release adds a few nifty features to `pandera`, special thanks to mastersplinter and ralbertazzi:

- We now have official [documentation](https://pandera.readthedocs.io/en/latest/)! Thanks to mastersplinter on the work here.
- the `Check` class now has a `groupby` argument, which enables the user to assert properties on subsets of the `Column` of interest. This opens up the possibility to compare the values or aggregates of values of subsets of a column 42.
- the introduction of hypothesis tests through the `Hypothesis` class, which is a subclass of the `Check` class. This enables the user to run hypothesis tests on their dataframe as part of a `DataFrameSchema` definition. Refer to the [documentation](https://pandera.readthedocs.io/en/latest/hypothesis.html) for more info #43.
- `Column`s now have a `required` argument (default = True), where `required=False` means that the column is optional 23.
- `SeriesSchemaBase` now has an `allow_duplicates` argument (default = True) 24
- add informative errors to `check_input` and `check_output` decorators 902f1990c3f0ebc07074faee3f3c7e123600a872
- `DataFrameSchema(..., strict=True)` means that all columns in the dataframe need to be specified in the schema `columns`. 34
- improved error messaging in general.
- improved CI (codecoverage).

This release adds two new features to `pandera`.

Improved error reporting

Now failure cases in column checks are displayed in a much more compact format,
where the failure cases, the index of the dataframe where those failures occur, and the
count of failure cases are shown to the user, e.g.

failure cases:
index count
failure_case
foo1 [0] 1
foo2 [1] 1
foo3 [2] 1


Coerce option in `DataFrameSchema` and `Column`

Now the user can `coerce` the dataframe when calling `schema.validate` so that
the columns are cast into the expected data-type before performing `Check`s.