forked from pandas-dev/pandas
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathv0.18.1.txt
342 lines (219 loc) · 15.7 KB
/
v0.18.1.txt
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
.. _whatsnew_0181:
v0.18.1 (April ??, 2016)
------------------------
This is a minor bug-fix release from 0.18.0 and includes a large number of
bug fixes along several new features, enhancements, and performance improvements.
We recommend that all users upgrade to this version.
Highlights include:
- Custom business hour offset, see :ref:`here <whatsnew_0181.enhancements.custombusinesshour>`.
.. contents:: What's new in v0.18.1
:local:
:backlinks: none
.. _whatsnew_0181.new_features:
New features
~~~~~~~~~~~~
.. _whatsnew_0181.enhancements.custombusinesshour:
Custom Business Hour
^^^^^^^^^^^^^^^^^^^^
The ``CustomBusinessHour`` is a mixture of ``BusinessHour`` and ``CustomBusinessDay`` which
allows you to specify arbitrary holidays. For details,
see :ref:`Custom Business Hour <timeseries.custombusinesshour>` (:issue:`11514`)
.. ipython:: python
from pandas.tseries.offsets import CustomBusinessHour
from pandas.tseries.holiday import USFederalHolidayCalendar
bhour_us = CustomBusinessHour(calendar=USFederalHolidayCalendar())
# Friday before MLK Day
dt = datetime(2014, 1, 17, 15)
dt + bhour_us
# Tuesday after MLK Day (Monday is skipped because it's a holiday)
dt + bhour_us * 2
.. _whatsnew_0181.enhancements:
Enhancements
~~~~~~~~~~~~
.. _whatsnew_0181.partial_string_indexing:
Partial string indexing on ``DateTimeIndex`` when part of a ``MultiIndex``
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Partial string indexing now matches on ``DateTimeIndex`` when part of a ``MultiIndex`` (:issue:`10331`)
.. ipython:: python
dft2 = pd.DataFrame(np.random.randn(20, 1),
columns=['A'],
index=pd.MultiIndex.from_product([pd.date_range('20130101',
periods=10,
freq='12H'),
['a', 'b']]))
dft2
dft2.loc['2013-01-05']
idx = pd.IndexSlice
dft2 = dft2.swaplevel(0, 1).sort_index()
dft2.loc[idx[:, '2013-01-05'], :]
.. _whatsnew_0181.other:
Other Enhancements
^^^^^^^^^^^^^^^^^^
- ``pd.read_csv()`` now supports opening ZIP files that contains a single CSV, via extension inference or explict ``compression='zip'`` (:issue:`12175`)
- ``pd.read_csv()`` now supports opening files using xz compression, via extension inference or explicit ``compression='xz'`` is specified; ``xz`` compressions is also supported by ``DataFrame.to_csv`` in the same way (:issue:`11852`)
- ``pd.read_msgpack()`` now always gives writeable ndarrays even when compression is used (:issue:`12359`).
- ``interpolate()`` now supports ``method='akima'`` (:issue:`7588`).
- ``Index.take`` now handles ``allow_fill`` and ``fill_value`` consistently (:issue:`12631`)
.. ipython:: python
idx = pd.Index([1., 2., 3., 4.], dtype='float')
idx.take([2, -1]) # default, allow_fill=True, fill_value=None
idx.take([2, -1], fill_value=True)
- ``Index`` now supports ``.str.get_dummies()`` which returns ``MultiIndex``, see :ref:`Creating Indicator Variables <text.indicator>` (:issue:`10008`, :issue:`10103`)
.. ipython:: python
idx = pd.Index(['a|b', 'a|c', 'b|c'])
idx.str.get_dummies('|')
.. _whatsnew_0181.sparse:
Sparse changes
~~~~~~~~~~~~~~
These changes conform sparse handling to return the correct types and work to make a smoother experience with indexing.
``SparseArray.take`` now returns scalar for scalar input, ``SparseArray`` for others. Also now it handles negative indexer as the same rule as ``Index`` (:issue:`10560`, :issue:`12796`)
.. ipython:: python
s = pd.SparseArray([np.nan, np.nan, 1, 2, 3, np.nan, 4, 5, np.nan, 6])
s.take(0)
s.take([1, 2, 3])
- Bug in ``SparseSeries[]`` indexing with ``Ellipsis`` raises ``KeyError`` (:issue:`9467`)
- Bug in ``SparseSeries.loc[]`` with list-like input raises ``TypeError`` (:issue:`10560`)
- Bug in ``SparseSeries.iloc[]`` with scalar input may raise ``IndexError`` (:issue:`10560`)
- Bug in ``SparseSeries.loc[]``, ``.iloc[]`` with ``slice`` returns ``SparseArray``, rather than ``SparseSeries`` (:issue:`10560`)
- Bug in ``SparseDataFrame.loc[]``, ``.iloc[]`` may results in dense ``Series``, rather than ``SparseSeries`` (:issue:`12787`)
- Bug in ``SparseArray`` addition ignores ``fill_value`` of right hand side (:issue:`12910`)
- Bug in ``SparseArray`` mod raises ``AttributeError (:issue:`12910`)
- Bug in ``SparseArray`` pow calculates ``1 ** np.nan`` as ``np.nan`` which must be 1 (:issue:`12910`)
- Bug in ``SparseSeries.__repr__`` raises ``TypeError`` when it is longer than ``max_rows`` (:issue:`10560`)
- Bug in ``SparseSeries.shape`` ignores ``fill_value`` (:issue:`10452`)
- Bug in ``SparseSeries`` and ``SparseArray`` may have different ``dtype`` from its dense values (:issue:`12908`)
- Bug in ``SparseSeries.reindex`` incorrectly handle ``fill_value`` (:issue:`12797`)
- Bug in ``SparseArray.to_frame()`` results in ``DataFrame``, rather than ``SparseDataFrame`` (:issue:`9850`)
- Bug in ``SparseArray.to_dense()`` does not preserve ``dtype`` (:issue:`10648`)
- Bug in ``SparseArray.to_dense()`` incorrectly handle ``fill_value`` (:issue:`12797`)
- Bug in ``pd.concat()`` of ``SparseSeries`` results in dense (:issue:`10536`)
- Bug in ``SparseArray.shift()`` may raise ``NameError`` or ``TypeError`` (:issue:`12908`)
.. _whatsnew_0181.api:
API changes
~~~~~~~~~~~
- ``.searchsorted()`` for ``Index`` and ``TimedeltaIndex`` now accept a ``sorter`` argument to maintain compatibility with numpy's ``searchsorted`` function (:issue:`12238`)
- ``Period`` and ``PeriodIndex`` now raises ``IncompatibleFrequency`` error which inherits ``ValueError`` rather than raw ``ValueError`` (:issue:`12615`)
- ``Series.apply`` for category dtype now applies passed function to each ``.categories`` (not ``.codes``), and returns "category" dtype if possible (:issue:`12473`)
- ``read_csv`` will now raise a ``TypeError`` if ``parse_dates`` is neither a boolean, list, or dictionary (:issue:`5636`)
- The default for ``.query()/.eval()`` is now ``engine=None``, which will use ``numexpr`` if it's installed; otherwise it will fallback to the ``python`` engine. This mimics the pre-0.18.1 behavior if ``numexpr`` is installed (and which Previously, if numexpr was not installed, ``.query()/.eval()`` would raise). (:issue:`12749`)
- ``pd.show_versions()`` now includes ``pandas_datareader`` version (:issue:`12740`)
- Provide a proper ``__name__`` and ``__qualname__`` attributes for generic functions (:issue:`12021`)
- ``pd.concat(ignore_index=True)`` now uses ``RangeIndex`` as default (:issue:`12695`)
.. _whatsnew_0181.apply_resample:
Using ``.apply`` on groupby resampling
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Using ``apply`` on resampling groupby operations (using a ``pd.TimeGrouper``) now has the same output types as similar ``apply`` calls on other groupby operations. (:issue:`11742`).
.. ipython:: python
df = pd.DataFrame({'date': pd.to_datetime(['10/10/2000', '11/10/2000']), 'value': [10, 13]})
df
Previous behavior:
.. code-block:: ipython
In [1]: df.groupby(pd.TimeGrouper(key='date', freq='M')).apply(lambda x: x.value.sum())
Out[1]:
...
TypeError: cannot concatenate a non-NDFrame object
# Output is a Series
In [2]: df.groupby(pd.TimeGrouper(key='date', freq='M')).apply(lambda x: x[['value']].sum())
Out[2]:
date
2000-10-31 value 10
2000-11-30 value 13
dtype: int64
New Behavior:
.. ipython:: python
# Output is a Series
df.groupby(pd.TimeGrouper(key='date', freq='M')).apply(lambda x: x.value.sum())
# Output is a DataFrame
df.groupby(pd.TimeGrouper(key='date', freq='M')).apply(lambda x: x[['value']].sum())
.. _whatsnew_0181.read_csv_exceptions:
Changes in ``read_csv`` exceptions
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
In order to standardize the ``read_csv`` API for both the C and Python engines, both will now raise an
``EmptyDataError``, a subclass of ``ValueError``, in response to empty columns or header (:issue:`12493`, :issue:`12506`)
Previous behaviour:
.. code-block:: python
In [1]: df = pd.read_csv(StringIO(''), engine='c')
...
ValueError: No columns to parse from file
In [2]: df = pd.read_csv(StringIO(''), engine='python')
...
StopIteration
New behaviour:
.. code-block:: python
In [1]: df = pd.read_csv(StringIO(''), engine='c')
...
pandas.io.common.EmptyDataError: No columns to parse from file
In [2]: df = pd.read_csv(StringIO(''), engine='python')
...
pandas.io.common.EmptyDataError: No columns to parse from file
In addition to this error change, several others have been made as well:
- ``CParserError`` is now a ``ValueError`` instead of just an ``Exception`` (:issue:`12551`)
- A ``CParserError`` is now raised instead of a generic ``Exception`` in ``read_csv`` when the C engine cannot parse a column
- A ``ValueError`` is now raised instead of a generic ``Exception`` in ``read_csv`` when the C engine encounters a ``NaN`` value in an integer column
- A ``ValueError`` is now raised instead of a generic ``Exception`` in ``read_csv`` when ``true_values`` is specified, and the C engine encounters an element in a column containing unencodable bytes
- ``pandas.parser.OverflowError`` exception has been removed and has been replaced with Python's built-in ``OverflowError`` exception
- ``read_csv`` no longer allows a combination of strings and integers for the ``usecols`` parameter (:issue:`12678`)
.. _whatsnew_0181.deprecations:
Deprecations
^^^^^^^^^^^^
- The method name ``Index.sym_diff()`` is deprecated and can be replaced by ``Index.symmetric_difference()`` (:issue:`12591`)
- The method name ``Categorical.sort()`` is deprecated in favor of ``Categorical.sort_values()`` (:issue:`12882`)
.. _whatsnew_0181.performance:
Performance Improvements
~~~~~~~~~~~~~~~~~~~~~~~~
- Improved performance of ``DataFrame.to_sql`` when checking case sensitivity for tables. Now only checks if table has been created correctly when table name is not lower case. (:issue:`12876`)
.. _whatsnew_0181.bug_fixes:
Bug Fixes
~~~~~~~~~
- ``usecols`` parameter in ``pd.read_csv`` is now respected even when the lines of a CSV file are not even (:issue:`12203`)
- Bug in ``groupby.transform(..)`` when ``axis=1`` is specified with a non-monotonic ordered index (:issue:`12713`)
- Bug in ``Period`` and ``PeriodIndex`` creation raises ``KeyError`` if ``freq="Minute"`` is specified. Note that "Minute" freq is deprecated in v0.17.0, and recommended to use ``freq="T"`` instead (:issue:`11854`)
- Bug in ``.resample(...).count()`` with a ``PeriodIndex`` always raising a ``TypeError`` (:issue:`12774`)
- Bug in ``.resample(...)`` with a ``PeriodIndex`` casting to a ``DatetimeIndex`` when empty (:issue:`12868`)
- Bug in ``.resample(...)`` with a ``PeriodIndex`` when resampling to an existing frequency (:issue:`12770`)
- Bug in printing data which contains ``Period`` with different ``freq`` raises ``ValueError`` (:issue:`12615`)
- Bug in numpy compatibility of ``np.round()`` on a ``Series`` (:issue:`12600`)
- Bug in ``Series`` construction with ``Categorical`` and ``dtype='category'`` is specified (:issue:`12574`)
- Bugs in concatenation with a coercable dtype was too aggressive. (:issue:`12411`, :issue:`12045`, :issue:`11594`, :issue:`10571`)
- Bug in ``float_format`` option with option not being validated as a callable. (:issue:`12706`)
- Bug in ``GroupBy.filter`` when ``dropna=False`` and no groups fulfilled the criteria (:issue:`12768`)
- Bug in ``__name__`` of ``.cum*`` functions (:issue:`12021`)
- Bug in ``.astype()`` of a ``Float64Inde/Int64Index`` to an ``Int64Index`` (:issue:`12881`)
- Bug in roundtripping an integer based index in ``.to_json()/.read_json()`` when ``orient='index'`` (the default) (:issue:`12866`)
- Bug in ``.drop()`` with a non-unique ``MultiIndex``. (:issue:`12701`)
- Bug in ``.concat`` of datetime tz-aware and naive DataFrames (:issue:`12467`)
- Bug in correctly raising a ``ValueError`` in ``.resample(..).fillna(..)`` when passing a non-string (:issue:`12952`)
- Bug in ``Timestamp.__repr__`` that caused ``pprint`` to fail in nested structures (:issue:`12622`)
- Bug in ``Timedelta.min`` and ``Timedelta.max``, the properties now report the true minimum/maximum ``timedeltas`` as recognized by Pandas. See :ref:`documentation <timedeltas.limitations>`. (:issue:`12727`)
- Bug in ``.quantile()`` with interpolation may coerce to ``float`` unexpectedly (:issue:`12772`)
- Bug in ``.quantile()`` with empty Series may return scalar rather than empty Series (:issue:`12772`)
- Bug in ``.loc`` with out-of-bounds in a large indexer would raise ``IndexError`` rather than ``KeyError`` (:issue:`12527`)
- Bug in resampling when using a ``TimedeltaIndex`` and ``.asfreq()``, would previously not include the final fencepost (:issue:`12926`)
- Bug in equality testing with a ``Categorical`` in a ``DataFrame`` (:issue:`12564`)
- Bug in ``GroupBy.first()``, ``.last()`` returns incorrect row when ``TimeGrouper`` is used (:issue:`7453`)
- Bug in ``read_csv`` with the C engine when specifying ``skiprows`` with newlines in quoted items (:issue:`10911`, `12775`)
- Bug in ``value_counts`` when ``normalize=True`` and ``dropna=True`` where nulls still contributed to the normalized count (:issue:`12558`)
- Bug in ``Panel.fillna()`` ignoring ``inplace=True`` (:issue:`12633`)
- Bug in ``read_csv`` when specifying ``names``, ```usecols``, and ``parse_dates`` simultaneously with the C engine (:issue:`9755`)
- Bug in ``read_csv`` when specifying ``delim_whitespace=True`` and ``lineterminator`` simultaneously with the C engine (:issue:`12912`)
- Bug in ``Series.rename``, ``DataFrame.rename`` and ``DataFrame.rename_axis`` not treating ``Series`` as mappings to relabel (:issue:`12623`).
- Clean in ``.rolling.min`` and ``.rolling.max`` to enhance dtype handling (:issue:`12373`)
- Bug in ``groupby`` where complex types are coerced to float (:issue:`12902`)
- Bug in ``Series.map`` raises ``TypeError`` if its dtype is ``category`` or tz-aware ``datetime`` (:issue:`12473`)
- Bug in index coercion when falling back from ```RangeIndex``` construction (:issue:`12893`)
- Bug in slicing subclassed ``DataFrame`` defined to return subclassed ``Series`` may return normal ``Series`` (:issue:`11559`)
- Bug in ``.str`` accessor methods may raise ``ValueError`` if input has ``name`` and the result is ``DataFrame`` or ``MultiIndex`` (:issue:`12617`)
- Bug in ``DataFrame.last_valid_index()`` and ``DataFrame.first_valid_index()`` on empty frames (:issue:`12800`)
- Bug in ``CategoricalIndex.get_loc`` returns different result from regular ``Index`` (:issue:`12531`)
- Bug in ``PeriodIndex.resample`` where name not propagated (:issue:`12769`)
- Bug in ``concat`` raises ``AttributeError`` when input data contains tz-aware datetime and timedelta (:issue:`12620`)
- Bug in ``concat`` doesn't handle empty ``Series`` properly (:issue:`11082`)
- Bug in ``pivot_table`` when ``margins=True`` and ``dropna=True`` where nulls still contributed to margin count (:issue:`12577`)
- Bug in ``pivot_table`` when ``dropna=False`` where table index/column names disappear (:issue:`12133`)
- Bug in ``crosstab`` when ``margins=True`` and ``dropna=False`` which raised (:issue:`12642`)
- Bug in ``Series.name`` when ``name`` attribute can be a hashable type (:issue:`12610`)
- Bug in ``.describe()`` resets categorical columns information (:issue:`11558`)
- Bug where ``loffset`` argument was not applied when calling ``resample().count()`` on a timeseries (:issue:`12725`)
- ``pd.read_excel()`` now accepts path objects (e.g. ``pathlib.Path``, ``py.path.local``) for the file path, in line with other ``read_*`` functions (:issue:`12655`)
- ``pd.read_excel()`` now accepts column names associated with keyword argument ``names``(:issue `12870`)
- Bug in ``fill_value`` is ignored if the argument to a binary operator is a constant (:issue `12723`)