What’s new in 0.23.2 (July 5, 2018) — pandas 2.2.3 documentation (original) (raw)

This is a minor bug-fix release in the 0.23.x series and includes some small regression fixes and bug fixes. We recommend that all users upgrade to this version.

Note

pandas 0.23.2 is first pandas release that’s compatible with Python 3.7 (GH 20552)

Warning

Starting January 1, 2019, pandas feature releases will support Python 3 only. See Dropping Python 2.7 for more.

What’s new in v0.23.2

Logical reductions over entire DataFrame#

DataFrame.all() and DataFrame.any() now accept axis=None to reduce over all axes to a scalar (GH 19976)

In [1]: df = pd.DataFrame({"A": [1, 2], "B": [True, False]})

In [2]: df.all(axis=None) Out[2]: False

This also provides compatibility with NumPy 1.15, which now dispatches to DataFrame.all. With NumPy 1.15 and pandas 0.23.1 or earlier, numpy.all() will no longer reduce over every axis:

NumPy 1.15, pandas 0.23.1

np.any(pd.DataFrame({"A": [False], "B": [False]})) A False B False dtype: bool

With pandas 0.23.2, that will correctly return False, as it did with NumPy < 1.15.

In [3]: np.any(pd.DataFrame({"A": [False], "B": [False]})) Out[3]: False

Fixed regressions#

Build changes#

Bug fixes#

Conversion

Indexing

I/O

Categorical

Timezones

Timedelta

Contributors#

A total of 17 people contributed patches to this release. People with a “+” by their names contributed a patch for the first time.