Validates the pandas object such as DataFrame and Series. And this can define validator like django form class.
Why bugs occur in Data Wrangling with pandasWhen 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-validator offers the functions for validating DataFrame or Series objects.
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
$ pip install pandas_validator
Please see the following demo written by ipython notebook.
This software is licensed under the MIT License.
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