The `PandasBackend` is a computational backend in the featuretools library for Python. It is designed to work with the pandas library, providing functionality to perform computations and transformations on tabular data. The `PandasBackend` allows users to leverage the powerful data manipulation capabilities of pandas, such as filtering, aggregating, and merging data, in order to generate and engineer features for machine learning tasks. It seamlessly integrates with the featuretools library, enabling users to easily extract relevant information from their data using pandas operations and create informative features for predictive modeling.
Python PandasBackend - 60 examples found. These are the top rated real world Python examples of featuretools.computational_backends.PandasBackend extracted from open source projects. You can rate examples to help us improve the quality of examples.