data-analysis, data-science, hacktoberfest, numpy, pandas, python, spark, type-inference, type-system
pip install visions==0.7.5



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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.

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.


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.