Symbolic Constraints

Website: https://abogical.github.io/symconstraints/

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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.