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Bump version up to v1.0.27
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CHANGES.rst

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Release notes
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=============
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Version 1.0.27, May 2022
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------------------------
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* Multiple performance updates, thanks to Simon Brugman.
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* Use pandas functions to infer datatypes and return numpy arrays.
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* Turn of unnecessary specialize function (slow) for Count objects.
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Version 1.0.26, Apr 2022
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------------------------
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* Added tutorial notebook with exercises.
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* Fixed 2d heatmap for categorical histograms, where one column was accidentally dropped.
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Version 1.0.25, Apr 2021
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* Improve null handling in pandas dataframes, by inferring datatype using pandas' infer_dtype function.

README.rst

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aggregators can be filled from ROOT TTrees hundreds of times more quickly by JIT-compiling a specialized C++ filler.
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Histograms and other aggregators may also be converted into CUDA code for inclusion in a GPU workflow. And if
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PyCUDA is available, they can also be filled from Numpy arrays by JIT-compiling the CUDA code.
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This Python implementation of histogrammar been tested to guarantee compatibility with its Scala implementation.
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Latest Python release: v1.0.26 (April 2022).
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Latest Python release: v1.0.27 (May 2022).
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Announcements
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=============

histogrammar/version.py

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import re
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name = "histogrammar"
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__version__ = "1.0.26"
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version = "1.0.26"
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full_version = "1.0.26"
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__version__ = "1.0.27"
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version = "1.0.27"
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full_version = "1.0.27"
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release = True
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version_info = tuple(re.split(r"[-\.]", __version__))

setup.py

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MAJOR = 1
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REVISION = 0
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PATCH = 26
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PATCH = 27
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DEV = False
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# NOTE: also update version at: README.rst
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