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pandas DataFrame validation library

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# Pandas DataFrame Validator

`pd-validator` is a pandas wrapper library for validating DataFrames against a user-defined schema.

>>> import pandas as pd
>>> from pd_validator import Schema
>>> from pd_validator import Report

>>> df = pd.read_csv('data.csv')
>>> df
col_1 col_2
1 BC
2 D

>>> rules = {'col_1': {'dtype': int,
'length': 1,
'range': [0,1],
'required': True,
'codes': False,
'regex': False},
'col_2': {'dtype': str,
'length': 1,
'range': False,
'required': False,
'codes': ['A', 'B', 'C'],
'regex': False}

>>> schema = Schema(rules=rules)

>>> report = Report(df=df, schema=schema())
>>> report()
col_1 col_2 inval_line inval_col inval_val err_msg
1 BC 2 col_2 BC Invalid length: 1 char max
1 BC 2 col_2 BC Invalid code: ['A', 'B', 'C'] required
2 D 3 col_2 D Invalid code: ['A', 'B', 'C'] required
A B 1 col_1 A Invalid dtype: int required
A B 1 col_1 A Invalid range: [0, 1] required
2 D 3 col_1 2 Invalid range: [0, 1] required
NaN A 4 col_1 NaN Missing value: col_1 required


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