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Release notes

Version 1.0.34, Dec 2024

  • Fix typo in build pipeline Python versions config list.
  • Fix error in SparselyBin __eq__ method.
  • Fix test utility corner case error (test_numpy.twosigfigs function).
  • Fix error in test context manager for pandas which prevented execution of tests.
  • Fix error in expected bin count in test_numpy.test_n_bins test.
  • Prevent logging zero execution time TestNumpy class.
  • Remove Python 3.8 environment from build pipeline.
  • Support numpy >= 2.0.0 (np.string_ -> np.bytes_, np.unicode_ -> np.str_).
  • Remove uses of pd.util.testing.makeMixedDataFrame not available in pandas >= 2.0.0.
  • Switch from 'pkg_resources' to 'importlib' module for resolving package files.
  • Switch from 'distutils.spawn' to 'shutil.which' for finding nvcc command.
  • Remove unused test_gpu.twosigfigs function.
  • Refactor tests with Numpy() and Pandas() context managers to use single 'with' statement.
  • Switch from setup.py to pyproject.toml
  • Add numpy<2,pandas<2 test environment to build pipeline test matrix

Version 1.0.33, Dec 2022

  • fix of get_sub_hist() when Bin histogram is filled only with nans.

Version 1.0.32, Sep 2022

  • Support for decimal datetype in pandas and spark.

Version 1.0.31, Aug 2022

  • fix of spark df timestamp datatype detection (#59)
  • fix for invalid bin_edges for SparselyBin histogram (#60)

Version 1.0.30, June 2022

  • Fix for machine-level rounding error, which can show up on in num_bins() call of Bin histogram.
  • supersedes broken v1.0.29

Version 1.0.28, June 2022

  • Multiple performance updates, to Bin, SparselyBin and Categorize histograms.
  • SparselyBin, Categorize: optimized filling with 1-d and 2-d numpy arrays
  • Bin, SparselyBin, Categorize: (fast) numpy arrays for bin-centers and bin-labels.
  • Count: new, fast filling option when float weight is known.
  • util.py: faster get_datatype() and get_ndim() functions.

Version 1.0.27, May 2022

  • Multiple performance updates, thanks to Simon Brugman.
  • Use pandas functions to infer datatypes and return numpy arrays.
  • Turn of unnecessary specialize function (slow) for Count objects.

Version 1.0.26, Apr 2022

  • Added tutorial notebook with exercises.
  • Fixed 2d heatmap for categorical histograms, where one column was accidentally dropped.

Version 1.0.25, Apr 2021

  • Improve null handling in pandas dataframes, by inferring datatype using pandas' infer_dtype function.
  • nans in bool columns get converted to "NaN", so the column keeps True and False values in Categorize.
  • columns of type object get converted to strings using to_string(), of type string uses only_str().

Version 1.0.24, Apr 2021

  • Categorize histogram now handles nones and nans in friendlier way, they are converted to "NaN".
  • make_histogram() now casts spark nulls to nan in case of numeric columns. scala interprets null as 0.
  • SparselyBin histograms did not add up nanflow when added. Now fixed.
  • Added unit test for doing checks on null conversion to nans
  • Use new histogrammar-scala jar files, v1.0.20
  • Added histogrammar-scala v1.0.20 jar files to tests/jars/