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Validation Library for pandas' DataFrame and Series.

Results 8 pandas-validator issues
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Sometimes we want to validate that a ```DataFrame``` contains certain columns, without necessarily worrying about what is the content of that column. In my case I am parsing a file...

Instead of `validate()`, we have to use `is_valid()` like this: ``` validator = SampleDataFrameValidator() validator.is_valid(df) ``` However, it is not suitable for English grammar. In English, the example means validator...

Version 0.5.0's behavior is that if a ColumnValidator is specified, when validating a data frame without the target column label it throws a KeyError. I would think it should return...

I want to save a vlidator class in a file or database, Is there any methods can serialize and unserialize a vlidator class?

sometimes it is nice to check if columns contain no more (or none at all) of the NAN/NAT/None values. Will be happy to PR

help wanted

When DataframeValidator raises ValidationError, I wanted to know which columns have type errors. I modified it to do so. I changed only error messages of ColumnValidators, didn't change ones of...

I want to implement the following validators of pandas DataFrame's column. - [x] IntegerColumnValidator - [x] FloatColumnValidator - [x] CharColumnValidator - [x] ChoiceColumnValidator -> CategoricalColumnValidator - [ ] DateTimeColumnValidator

task

For example ``` class SampleDataFrameValidator(pv.DataFrameValidator): row_num = 5 column_num = 2 label1 = pv.IntegerColumnValidator('label1', min_value=0, max_value=10) label2 = pv.FloatColumnValidator('label2', min_value=0, max_value=10) metadata = { 'metadata1': str 'metadata2': int } ```