v1.0.34

What's Changed

• FIX: small fixes to make unit tests pass for numpy<2 and pandas<2 by @mbaak in #66
• Support Numpy >= 2.0.0 and Pandas >= 2.0.0 by @mkopec87 in #65
• • Switch from setup.py to pyproject.toml by @mkopec87 in #68

New Contributors

• @mkopec87 made their first contribution in #65

Full Changelog: v1.0.33...v1.0.34

v1.0.33

Dec 2022: fix of get_sub_hist() when Bin histogram is filled only with nans.

v1.0.32

Support for decimal datetype in pandas and spark.

v1.0.31

Two fixes:

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

v1.0.30

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

• Supersedes v1.0.29

v1.0.29

Version 1.0.29, June 2022

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

v1.0.28, June 2022

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.

v1.0.27

Version 1.0.27, May 2022

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

v1.0.26

What's Changed

• FIX: show edge of heatmap for categorical histograms by @mbaak in #47

v1.0.25

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, not "1" and "0".
• columns of type object get converted to strings using to_string(), of type string uses only_str().