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
Full documentation can be found here.
You can install visions via pip:
pip install visions
Alternatives and more details can be found in the documentation.
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.
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