Visions
Project description
And these visions of data types, they kept us up past the dawn.
Visions provides an extensible suite of tools to support common data analysis operations including
type inference on unknown data
casting data types
automated data summarization
Documentation
Full documentation can be found here.
Installation
You can install visions via pip:
pip install visionsAlternatives and more details can be found in the documentation.
Supported frameworks
These frameworks are supported out-of-the-box in addition to native Python types:
Pandas (feature complete)
Numpy (boolean, complex, date time, float, integer, string, time deltas, string, objects)
Spark (boolean, categorical, date, date time, float, integer, numeric, object, string)
Python (string, float, integer, date time, time delta, boolean, categorical, object, complex - other datatypes are untested)
Contributing and support
Contributions to visions are welcome. For more information, please visit the Community contributions page. The the Github issues tracker is used for reporting bugs, feature requests and support questions.
Acknowledgements
This package is part of the dylan-profiler project. The package is core component of pandas-profiling. More information can be found here. This work was partially supported by SIDN Fonds.
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