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Project description
Symbolic Constraints
Website: https://abogical.github.io/symconstraints/
Validate and impute your dataset with mathematical expressions.
Symbolic Constraints, or symconstraints
for short, allows you to express your dataset rules
using mathematical equations and expressions. It makes use of the powerful SymPy Computer Algebra System to analyze
mathematical expressions and infer all possible validation and imputation methods to your datasets.
Installation
Symbolic constraints can be installed via pip
:
pip install symconstraints
Features
🪄 Automatic inference
symconstraints
uses SymPy to rearrange your formulas and find new ways to validate and impute your data.
Example
Given the constraints $a < 3b$ and $c > b^2 + 1$:
>>> from symconstraints import Constraints, symbols
>>> a, b, c = symbols('a b c')
>>> constraints = Constraints([a < 3*b, c > b**2 + 1])
>>> for validation in constraints.validations
... print(validation)
Validation: (b, a) => [a < 3*b] inferred by (a < 3*b)
Validation: (b, c) => [c > b**2 + 1] inferred by (c > b**2 + 1)
Validation: (a, c) => [a/3 < sqrt(c - 1)] inferred by (c > b**2 + 1, a < 3*b)
It automatically infers that $\frac{a}{3} < \sqrt{c-1}$.
🧩 Integrations
Integrates with popular data science tools such as Pandas. Saving you time to help you clean your datasets with little code.
scikit-learn and Pandera integrations are currently under development.
Example
>>> import pandas as pd
>>> from symconstraints import Constraints
>>> from symconstraints.pandas import symbols, check, set_invalid_all, impute
>>> from sympy import Eq
>>> df = pd.DataFrame(
... {
... "height": [5, 6, 8, 9],
... "width": [3, 5, 7, None],
... "area": [14, 30, None, 18],
... },
... dtype=float,
... )
>>> height, width, area = symbols(df, ["height", "width", "area"])
>>> constraints = Constraints([height > width, Eq(area, width * height)])
>>> check_result = check(constraints, df)
>>> df = set_invalid_all(check_result, df)
>>> df
height width area
0 NaN NaN NaN
1 6.0 5.0 30.0
2 8.0 7.0 NaN
3 9.0 NaN 18.0
>>> imputed_df = impute(constraints, df)
>>> imputed_df
height width area
0 NaN NaN NaN
1 6.0 5.0 30.0
2 8.0 7.0 56.0
3 9.0 2.0 18.0
License
symconstraints
is distributed under the terms of the MIT license.
Project details
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