What’s new in 0.23.1 (June 12, 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.
Warning
Starting January 1, 2019, pandas feature releases will support Python 3 only. See Dropping Python 2.7 for more.
What’s new in v0.23.1
Fixed regressions#
Comparing Series with datetime.date
We’ve reverted a 0.23.0 change to comparing a Series holding datetimes and a datetime.date
object (GH 21152). In pandas 0.22 and earlier, comparing a Series holding datetimes and datetime.date
objects would coerce the datetime.date
to a datetime before comparing. This was inconsistent with Python, NumPy, and DatetimeIndex, which never consider a datetime and datetime.date
equal.
In 0.23.0, we unified operations between DatetimeIndex and Series, and in the process changed comparisons between a Series of datetimes and datetime.date
without warning.
We’ve temporarily restored the 0.22.0 behavior, so datetimes and dates may again compare equal, but restore the 0.23.0 behavior in a future release.
To summarize, here’s the behavior in 0.22.0, 0.23.0, 0.23.1:
0.22.0... Silently coerce the datetime.date
import datetime pd.Series(pd.date_range('2017', periods=2)) == datetime.date(2017, 1, 1) 0 True 1 False dtype: bool
0.23.0... Do not coerce the datetime.date
pd.Series(pd.date_range('2017', periods=2)) == datetime.date(2017, 1, 1) 0 False 1 False dtype: bool
0.23.1... Coerce the datetime.date with a warning
pd.Series(pd.date_range('2017', periods=2)) == datetime.date(2017, 1, 1) /bin/python:1: FutureWarning: Comparing Series of datetimes with 'datetime.date'. Currently, the 'datetime.date' is coerced to a datetime. In the future pandas will not coerce, and the values not compare equal to the 'datetime.date'. To retain the current behavior, convert the 'datetime.date' to a datetime with 'pd.Timestamp'. #!/bin/python3 0 True 1 False dtype: bool
In addition, ordering comparisons will raise a TypeError
in the future.
Other fixes
- Reverted the ability of to_sql() to perform multivalue inserts as this caused regression in certain cases (GH 21103). In the future this will be made configurable.
- Fixed regression in the DatetimeIndex.date and DatetimeIndex.timeattributes in case of timezone-aware data: DatetimeIndex.time returned a tz-aware time instead of tz-naive (GH 21267) and DatetimeIndex.datereturned incorrect date when the input date has a non-UTC timezone (GH 21230).
- Fixed regression in
pandas.io.json.json_normalize()
when called withNone
values in nested levels in JSON, and to not drop keys with value asNone
(GH 21158, GH 21356). - Bug in to_csv() causes encoding error when compression and encoding are specified (GH 21241, GH 21118)
- Bug preventing pandas from being importable with -OO optimization (GH 21071)
- Bug in
Categorical.fillna()
incorrectly raising aTypeError
whenvalue
the individual categories are iterable andvalue
is an iterable (GH 21097, GH 19788) - Fixed regression in constructors coercing NA values like
None
to strings when passingdtype=str
(GH 21083) - Regression in pivot_table() where an ordered
Categorical
with missing values for the pivot’sindex
would give a mis-aligned result (GH 21133) - Fixed regression in merging on boolean index/columns (GH 21119).
Performance improvements#
- Improved performance of
CategoricalIndex.is_monotonic_increasing()
,CategoricalIndex.is_monotonic_decreasing()
andCategoricalIndex.is_monotonic()
(GH 21025) - Improved performance of
CategoricalIndex.is_unique()
(GH 21107)
Bug fixes#
Groupby/resample/rolling
- Bug in DataFrame.agg() where applying multiple aggregation functions to a DataFrame with duplicated column names would cause a stack overflow (GH 21063)
- Bug in
GroupBy.ffill()
andGroupBy.bfill()
where the fill within a grouping would not always be applied as intended due to the implementations’ use of a non-stable sort (GH 21207) - Bug in
GroupBy.rank()
where results did not scale to 100% when specifyingmethod='dense'
andpct=True
- Bug in pandas.DataFrame.rolling() and pandas.Series.rolling() which incorrectly accepted a 0 window size rather than raising (GH 21286)
Data-type specific
- Bug in Series.str.replace() where the method throws
TypeError
on Python 3.5.2 (GH 21078) - Bug in Timedelta where passing a float with a unit would prematurely round the float precision (GH 14156)
- Bug in pandas.testing.assert_index_equal() which raised
AssertionError
incorrectly, when comparing two CategoricalIndex objects with paramcheck_categorical=False
(GH 19776)
Sparse
- Bug in
SparseArray.shape
which previously only returned the shapeSparseArray.sp_values
(GH 21126)
Indexing
- Bug in Series.reset_index() where appropriate error was not raised with an invalid level name (GH 20925)
- Bug in interval_range() when
start
/periods
orend
/periods
are specified with floatstart
orend
(GH 21161) - Bug in
MultiIndex.set_names()
where error raised for aMultiIndex
withnlevels == 1
(GH 21149) - Bug in IntervalIndex constructors where creating an
IntervalIndex
from categorical data was not fully supported (GH 21243, GH 21253) - Bug in
MultiIndex.sort_index()
which was not guaranteed to sort correctly withlevel=1
; this was also causing data misalignment in particular DataFrame.stack() operations (GH 20994, GH 20945, GH 21052)
Plotting
- New keywords (sharex, sharey) to turn on/off sharing of x/y-axis by subplots generated with pandas.DataFrame().groupby().boxplot() (GH 20968)
I/O
- Bug in IO methods specifying
compression='zip'
which produced uncompressed zip archives (GH 17778, GH 21144) - Bug in DataFrame.to_stata() which prevented exporting DataFrames to buffers and most file-like objects (GH 21041)
- Bug in read_stata() and
StataReader
which did not correctly decode utf-8 strings on Python 3 from Stata 14 files (dta version 118) (GH 21244) - Bug in IO JSON read_json() reading empty JSON schema with
orient='table'
back to DataFrame caused an error (GH 21287)
Reshaping
- Bug in concat() where error was raised in concatenating Series with numpy scalar and tuple names (GH 21015)
- Bug in concat() warning message providing the wrong guidance for future behavior (GH 21101)
Other
- Tab completion on Index in IPython no longer outputs deprecation warnings (GH 21125)
- Bug preventing pandas being used on Windows without C++ redistributable installed (GH 21106)
Contributors#
A total of 30 people contributed patches to this release. People with a “+” by their names contributed a patch for the first time.
- Adam J. Stewart
- Adam Kim +
- Aly Sivji
- Chalmer Lowe +
- Damini Satya +
- Dr. Irv
- Gabe Fernando +
- Giftlin Rajaiah
- Jeff Reback
- Jeremy Schendel +
- Joris Van den Bossche
- Kalyan Gokhale +
- Kevin Sheppard
- Matthew Roeschke
- Max Kanter +
- Ming Li
- Pyry Kovanen +
- Stefano Cianciulli
- Tom Augspurger
- Uddeshya Singh +
- Wenhuan
- William Ayd
- chris-b1
- gfyoung
- h-vetinari
- nprad +
- ssikdar1 +
- tmnhat2001
- topper-123
- zertrin +