forked from pandas-dev/pandas
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathv0.20.0.txt
322 lines (190 loc) · 10.7 KB
/
v0.20.0.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
.. _whatsnew_0200:
v0.20.0 (????, 2016)
--------------------
This is a major release from 0.19 and includes a small number of API changes, several new features,
enhancements, and performance improvements along with a large number of bug fixes. We recommend that all
users upgrade to this version.
Highlights include:
- Building pandas for development now requires ``cython >= 0.23`` (:issue:`14831`)
Check the :ref:`API Changes <whatsnew_0200.api_breaking>` and :ref:`deprecations <whatsnew_0200.deprecations>` before updating.
.. contents:: What's new in v0.20.0
:local:
:backlinks: none
.. _whatsnew_0200.enhancements:
New features
~~~~~~~~~~~~
.. _whatsnew_0200.enhancements.dataio_dtype:
``dtype`` keyword for data IO
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
The ``dtype`` keyword argument in the :func:`read_csv` function for specifying the types of parsed columns is now supported with the ``'python'`` engine (:issue:`14295`). See the :ref:`io docs <io.dtypes>` for more information.
.. ipython:: python
data = "a,b\n1,2\n3,4"
pd.read_csv(StringIO(data), engine='python').dtypes
pd.read_csv(StringIO(data), engine='python', dtype={'a':'float64', 'b':'object'}).dtypes
The ``dtype`` keyword argument is also now supported in the :func:`read_fwf` function for parsing
fixed-width text files, and :func:`read_excel` for parsing Excel files.
.. ipython:: python
data = "a b\n1 2\n3 4"
pd.read_fwf(StringIO(data)).dtypes
pd.read_fwf(StringIO(data), dtype={'a':'float64', 'b':'object'}).dtypes
.. _whatsnew_0200.enhancements.groupby_access:
Groupby Enhancements
^^^^^^^^^^^^^^^^^^^^
Strings passed to ``DataFrame.groupby()`` as the ``by`` parameter may now reference either column names or index level names (:issue:`5677`)
.. ipython:: python
arrays = [['bar', 'bar', 'baz', 'baz', 'foo', 'foo', 'qux', 'qux'],
['one', 'two', 'one', 'two', 'one', 'two', 'one', 'two']]
index = pd.MultiIndex.from_arrays(arrays, names=['first', 'second'])
df = pd.DataFrame({'A': [1, 1, 1, 1, 2, 2, 3, 3],
'B': np.arange(8)},
index=index)
df
df.groupby(['second', 'A']).sum()
.. _whatsnew_0200.enhancements.compressed_urls:
Better support for compressed URLs in ``read_csv``
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
The compression code was refactored (:issue:`12688`). As a result, reading
dataframes from URLs in :func:`read_csv` or :func:`read_table` now supports
additional compression methods: ``xz``, ``bz2``, and ``zip`` (:issue:`14570`).
Previously, only ``gzip`` compression was supported. By default, compression of
URLs and paths are now both inferred using their file extensions. Additionally,
support for bz2 compression in the python 2 c-engine improved (:issue:`14874`).
.. ipython:: python
url = 'https://github.com/{repo}/raw/{branch}/{path}'.format(
repo = 'pandas-dev/pandas',
branch = 'master',
path = 'pandas/io/tests/parser/data/salaries.csv.bz2',
)
df = pd.read_table(url, compression='infer') # default, infer compression
df = pd.read_table(url, compression='bz2') # explicitly specify compression
df.head(2)
.. _whatsnew_0200.enhancements.other:
Other enhancements
^^^^^^^^^^^^^^^^^^
- ``Series.sort_index`` accepts parameters ``kind`` and ``na_position`` (:issue:`13589`, :issue:`14444`)
- ``pd.read_excel`` now preserves sheet order when using ``sheetname=None`` (:issue:`9930`)
- Multiple offset aliases with decimal points are now supported (e.g. '0.5min' is parsed as '30s') (:issue:`8419`)
- New ``UnsortedIndexError`` (subclass of ``KeyError``) raised when indexing/slicing into an
unsorted MultiIndex (:issue:`11897`). This allows differentiation between errors due to lack
of sorting or an incorrect key. See :ref:`here <advanced.unsorted>`
- ``pd.cut`` and ``pd.qcut`` now support datetime64 and timedelta64 dtypes (:issue:`14714`, :issue:`14798`)
- ``Series`` provides a ``to_excel`` method to output Excel files (:issue:`8825`)
- The ``usecols`` argument in ``pd.read_csv`` now accepts a callable function as a value (:issue:`14154`)
- ``pd.DataFrame.plot`` now prints a title above each subplot if ``suplots=True`` and ``title`` is a list of strings (:issue:`14753`)
- ``pd.Series.interpolate`` now supports timedelta as an index type with ``method='time'`` (:issue:`6424`)
- ``pandas.io.json.json_normalize()`` gained the option ``errors='ignore'|'raise'``; the default is ``errors='raise'`` which is backward compatible. (:issue:`14583`)
- ``.select_dtypes()`` now allows the string 'datetimetz' to generically select datetimes with tz (:issue:`14910`)
.. _whatsnew_0200.api_breaking:
Backwards incompatible API changes
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. _whatsnew.api_breaking.index_map
Map on Index types now return other Index types
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
- ``map`` on an ``Index`` now returns an ``Index``, not a numpy array (:issue:`12766`)
.. ipython:: python
idx = Index([1, 2])
idx
mi = MultiIndex.from_tuples([(1, 2), (2, 4)])
mi
Previous Behavior:
.. code-block:: ipython
In [5]: idx.map(lambda x: x * 2)
Out[5]: array([2, 4])
In [6]: idx.map(lambda x: (x, x * 2))
Out[6]: array([(1, 2), (2, 4)], dtype=object)
In [7]: mi.map(lambda x: x)
Out[7]: array([(1, 2), (2, 4)], dtype=object)
In [8]: mi.map(lambda x: x[0])
Out[8]: array([1, 2])
New Behavior:
.. ipython:: python
idx.map(lambda x: x * 2)
idx.map(lambda x: (x, x * 2))
mi.map(lambda x: x)
mi.map(lambda x: x[0])
- ``map`` on a ``Series`` with ``datetime64`` values may return ``int64`` dtypes rather than ``int32``
.. ipython:: python
s = Series(date_range('2011-01-02T00:00', '2011-01-02T02:00', freq='H').tz_localize('Asia/Tokyo'))
s
Previous Behavior:
.. code-block:: ipython
In [9]: s.map(lambda x: x.hour)
Out[9]:
0 0
1 1
2 2
dtype: int32
New Behavior:
.. ipython:: python
s.map(lambda x: x.hour)
.. _whatsnew_0200.api_breaking.s3:
S3 File Handling
^^^^^^^^^^^^^^^^
pandas now uses `s3fs <http://s3fs.readthedocs.io/>`_ for handling S3 connections. This shouldn't break
any code. However, since s3fs is not a required dependency, you will need to install it separately, like ``boto``
in prior versions of pandas. (:issue:`11915`).
.. _whatsnew_0200.api_breaking.partial_string_indexing:
Partial String Indexing Changes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
:ref:`DatetimeIndex Partial String Indexing <timeseries.partialindexing>` now works as exact match, provided that string resolution coincides with index resolution, including a case when both are seconds (:issue:`14826`). See :ref:`Slice vs. Exact Match <timeseries.slice_vs_exact_match>` for details.
.. ipython:: python
df = DataFrame({'a': [1, 2, 3]}, DatetimeIndex(['2011-12-31 23:59:59',
'2012-01-01 00:00:00',
'2012-01-01 00:00:01']))
Previous Behavior:
.. code-block:: ipython
In [4]: df['2011-12-31 23:59:59']
Out[4]:
a
2011-12-31 23:59:59 1
In [5]: df['a']['2011-12-31 23:59:59']
Out[5]:
2011-12-31 23:59:59 1
Name: a, dtype: int64
New Behavior:
.. code-block:: ipython
In [4]: df['2011-12-31 23:59:59']
KeyError: '2011-12-31 23:59:59'
In [5]: df['a']['2011-12-31 23:59:59']
Out[5]: 1
.. _whatsnew_0200.api:
Other API Changes
^^^^^^^^^^^^^^^^^
- ``CParserError`` has been renamed to ``ParserError`` in ``pd.read_csv`` and will be removed in the future (:issue:`12665`)
- ``SparseArray.cumsum()`` and ``SparseSeries.cumsum()`` will now always return ``SparseArray`` and ``SparseSeries`` respectively (:issue:`12855`)
.. _whatsnew_0200.deprecations:
Deprecations
^^^^^^^^^^^^
- ``SparseArray.to_dense()`` has deprecated the ``fill`` parameter, as that parameter was not being respected (:issue:`14647`)
- ``SparseSeries.to_dense()`` has deprecated the ``sparse_only`` parameter (:issue:`14647`)
- ``Series.repeat()`` has deprecated the ``reps`` parameter in favor of ``repeats`` (:issue:`12662`)
- ``Index.repeat()`` and ``MultiIndex.repeat()`` have deprecated the ``n`` parameter in favor of ``repeats`` (:issue:`12662`)
- ``Categorical.searchsorted()`` and ``Series.searchsorted()`` have deprecated the ``v`` parameter in favor of ``value`` (:issue:`12662`)
- ``TimedeltaIndex.searchsorted()``, ``DatetimeIndex.searchsorted()``, and ``PeriodIndex.searchsorted()`` have deprecated the ``key`` parameter in favor of ``value`` (:issue:`12662`)
.. _whatsnew_0200.prior_deprecations:
Removal of prior version deprecations/changes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
- ``pd.to_datetime`` and ``pd.to_timedelta`` have dropped the ``coerce`` parameter in favor of ``errors`` (:issue:`13602`)
.. _whatsnew_0200.performance:
Performance Improvements
~~~~~~~~~~~~~~~~~~~~~~~~
- Improved performance of ``pd.wide_to_long()`` (:issue:`14779`)
- Increased performance of ``pd.factorize()`` by releasing the GIL with ``object`` dtype when inferred as strings (:issue:`14859`)
.. _whatsnew_0200.bug_fixes:
Bug Fixes
~~~~~~~~~
- Bug in ``TimedeltaIndex`` addition where overflow was being allowed without error (:issue:`14816`)
- Bug in ``DataFrame`` construction in which unsigned 64-bit integer elements were being converted to objects (:issue:`14881`)
- Bug in ``astype()`` where ``inf`` values were incorrectly converted to integers. Now raises error now with ``astype()`` for Series and DataFrames (:issue:`14265`)
- Bug in ``DataFrame(..).apply(to_numeric)`` when values are of type decimal.Decimal. (:issue:`14827`)
- Bug in ``describe()`` when passing a numpy array which does not contain the median to the ``percentiles`` keyword argument (:issue:`14908`)
- Bug in ``DataFrame.sort_values()`` when sorting by multiple columns where one column is of type ``int64`` and contains ``NaT`` (:issue:`14922`)
- Bug in ``pd.read_msgpack()`` in which ``Series`` categoricals were being improperly processed (:issue:`14901`)
- Bug in ``Series.ffill()`` with mixed dtypes containing tz-aware datetimes. (:issue:`14956`)
- Bug in ``Series`` construction with a datetimetz (:issue:`14928`)
- Bug in ``Series.unique()`` in which unsigned 64-bit integers were causing overflow (:issue:`14721`)
- Bug in ``pd.unique()`` in which unsigned 64-bit integers were causing overflow (:issue:`14915`)
- Require at least 0.23 version of cython to avoid problems with character encodings (:issue:`14699`)
- Bug in converting object elements of array-like objects to unsigned 64-bit integers (:issue:`4471`)
- Bug in ``pd.pivot_table()`` where no error was raised when values argument was not in the columns (:issue:`14938`)
- Bug in HTML display with MultiIndex and truncation (:issue:`14882`)