================
.. image:: https://travis-ci.org/c-bata/pandas-validator.svg?branch=master :target: https://travis-ci.org/c-bata/pandas-validator
.. image:: https://badge.fury.io/py/pandas_validator.svg :target: http://badge.fury.io/py/pandas_validator
.. image:: https://readthedocs.org/projects/pandas-validator/badge/?version=latest :target: https://readthedocs.org/projects/pandas-validator/?badge=latest :alt: Documentation Status
Validates the pandas object such as DataFrame and Series. And this can define validator like django form class.
When we wrangle our data with pandas, We use DataFrame
frequently.
DataFrame
is very powerfull and easy to handle.
But DataFrame
has no it's schema, so It allows irregular values without being aware of it.
We are confused by these values and affect the results of data wrangling.
pandas-schema
offers the functions for validating DataFrame
or Series
objects and generating factory data.
.. code-block:: python
import pandas as pd
import pandas_validator as pv
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)
validator = SampleDataFrameValidator()
df = pd.DataFrame({'label1': [0, 1, 2, 3, 4], 'label2': [5.0, 6.0, 7.0, 8.0, 9.0]})
validator.is_valid(df) # True.
df = pd.DataFrame({'label1': [11, 12, 13, 14, 15], 'label2': [5.0, 6.0, 7.0, 8.0, 9.0]})
validator.is_valid(df) # False.
df = pd.DataFrame({'label1': [0, 1, 2], 'label2': [5.0, 6.0, 7.0]})
validator.is_valid(df) # False
.. code-block:: console
$ pip install pandas_validator
Please see the following demo written by ipython notebook.
Demo in Japanese <https://github.com/c-bata/pandas-validator/blob/master/example/pandas_validator_example_ja.ipynb>
_Demo in English <https://github.com/c-bata/pandas-validator/blob/master/example/pandas_validator_example_en.ipynb>
_This software is licensed under the MIT License.
Github <https://github.com/c-bata/pandas-validator>
_PyPI <https://pypi.python.org/pypi/pandas_validator>
_.validate(df)
method is deprecated. Please use .is_valid(df, raise_exception=True)
Initial release.
Support integer series validator
Support float series validator
Support dataframe validator
Testing on python2.7 and python 3.4
Create this project.
Version | Tag | Published |
---|---|---|
0.5.0 | 6yrs ago | |
0.4.0 | 7yrs ago | |
0.3.2 | 7yrs ago | |
0.3.1 | 7yrs ago |