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2011-09-20 BUG: pivot should raise exception if there are duplicate entries,
1 =============
2 Release Notes
3 =============
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4
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5 This is the list of changes to pandas between each release. For full details,
6 see the commit logs at http://github.com/wesm/pandas
7
8
9 pandas 0.4.1
10 ============
11
12 **Release date:** Not yet released
13
14 This is a bug fix release
15
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2011-09-22 ENH: get_dtype_counts publicized and added dtypes property
16 **New features / modules**
17
18 - Added new `DataFrame` methods `get_dtype_counts` and property `dtypes`
19
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20 **Bug fixes**
21
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2011-09-22 BUG: handling of Series input to DataFrame constructor
22 - Fixed DataFrame constructor bug causing downstream problems (e.g. .copy()
23 failing) when passing a Series as the values along with a column name and
24 index
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2011-09-22 DOC: update release notes
25 - Fixed single-key groupby on DataFrame with as_index=False (GH #160)
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26
1ba56251 »
2011-09-21 ENH: added ignore_index option to DataFrame.append, and speed optimiz…
27 **Improvements to existing features**
28
29 - Some speed enhancements with internal Index type-checking function
30
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31 pandas 0.4
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32 ==========
33
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34 What is it
35 ----------
36
6cad5358 »
2011-06-27 added generic rolling_apply function
37 **pandas** is a library of powerful labeled-axis data structures, statistical
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2011-07-24 TST: raise exception when try to create empty int columns
38 tools, and general code for working with relational data sets, including time
39 series and cross-sectional data. It was designed with the practical needs of
40 statistical modeling and large, inhomogeneous data sets in mind. It is
41 particularly well suited for, among other things, financial data analysis
42 applications.
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43
44 Where to get it
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2011-09-20 BUG: pivot should raise exception if there are duplicate entries,
45 ---------------
2dc78dce »
2011-06-03 moving around unit tests, working on fancy get/setitem for objects. f…
46
47 Source code: http://github.com/wesm/pandas
48 Binary installers on PyPI: http://pypi.python.org/pypi/pandas
49 Documentation: http://pandas.sourceforge.net
50
51 Release notes
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52 -------------
2dc78dce »
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53
42b0b018 »
2011-09-12 DOC: doc warning fixes
54 **Release date:** 9/12/2011
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55
56 **New features / modules**
57
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58 - `pandas.core.sparse` module: "Sparse" (mostly-NA, or some other fill value)
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59 versions of `Series`, `DataFrame`, and `Panel`. For low-density data, this
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60 will result in significant performance boosts, and smaller memory
61 footprint. Added `to_sparse` methods to `Series`, `DataFrame`, and
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62 `Panel`. See online documentation for more on these
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63 - Fancy indexing operator on Series / DataFrame, e.g. via .ix operator. Both
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64 getting and setting of values is supported; however, setting values will only
65 currently work on homogeneously-typed DataFrame objects. Things like:
66
67 * series.ix[[d1, d2, d3]]
68 * frame.ix[5:10, ['C', 'B', 'A']], frame.ix[5:10, 'A':'C']
69 * frame.ix[date1:date2]
70
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71 - Significantly enhanced `groupby` functionality
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72
73 * Can groupby multiple keys, e.g. df.groupby(['key1', 'key2']). Iteration with
74 multiple groupings products a flattened tuple
75 * "Nuisance" columns (non-aggregatable) will automatically be excluded from
76 DataFrame aggregation operations
77 * Added automatic "dispatching to Series / DataFrame methods to more easily
78 invoke methods on groups. e.g. s.groupby(crit).std() will work even though
79 `std` is not implemented on the `GroupBy` class
80
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2011-09-05 TST: test coverage
81 - Hierarchical / multi-level indexing
82
83 * New the `MultiIndex` class. Integrated `MultiIndex` into `Series` and
84 `DataFrame` fancy indexing, slicing, __getitem__ and __setitem,
85 reindexing, etc. Added `level` keyword argument to `groupby` to enable
86 grouping by a level of a `MultiIndex`
87
88 - New data reshaping functions: `stack` and `unstack` on DataFrame and Series
89
90 * Integrate with MultiIndex to enable sophisticated reshaping of data
91
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92 - `Index` objects (labels for axes) are now capable of holding tuples
93 - `Series.describe`, `DataFrame.describe`: produces an R-like table of summary
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94 statistics about each data column
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95 - `DataFrame.quantile`, `Series.quantile` for computing sample quantiles of data
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96 across requested axis
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97 - Added general `DataFrame.dropna` method to replace `dropIncompleteRows` and
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98 `dropEmptyRows`, deprecated those.
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99 - `Series` arithmetic methods with optional fill_value for missing data,
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100 e.g. a.add(b, fill_value=0). If a location is missing for both it will still
101 be missing in the result though.
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102 - fill_value option has been added to `DataFrame`.{add, mul, sub, div} methods
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103 similar to `Series`
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104 - Boolean indexing with `DataFrame` objects: data[data > 0.1] = 0.1 or
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105 data[data> other] = 1.
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106 - `pytz` / tzinfo support in `DateRange`
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107
108 * `tz_localize`, `tz_normalize`, and `tz_validate` methods added
109
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110 - Added `ExcelFile` class to `pandas.io.parsers` for parsing multiple sheets out
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111 of a single Excel 2003 document
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112 - `GroupBy` aggregations can now optionally *broadcast*, e.g. produce an object
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113 of the same size with the aggregated value propagated
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114 - Added `select` function in all data structures: reindex axis based on
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115 arbitrary criterion (function returning boolean value),
116 e.g. frame.select(lambda x: 'foo' in x, axis=1)
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117 - `DataFrame.consolidate` method, API function relating to redesigned internals
118 - `DataFrame.insert` method for inserting column at a specified location rather
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119 than the default __setitem__ behavior (which puts it at the end)
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120 - `HDFStore` class in `pandas.io.pytables` has been largely rewritten using
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121 patches from Jeff Reback from others. It now supports mixed-type `DataFrame`
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122 and `Series` data and can store `Panel` objects. It also has the option to
123 query `DataFrame` and `Panel` data. Loading data from legacy `HDFStore`
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124 files is supported explicitly in the code
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125 - Added `set_printoptions` method to modify appearance of DataFrame tabular
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126 output
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127 - `rolling_quantile` functions; a moving version of `Series.quantile` /
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128 `DataFrame.quantile`
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129 - Generic `rolling_apply` moving window function
130 - New `drop` method added to `Series`, `DataFrame`, etc. which can drop a set of
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131 labels from an axis, producing a new object
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132 - `reindex` methods now sport a `copy` option so that data is not forced to be
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133 copied then the resulting object is indexed the same
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134 - Added `sort_index` methods to Series and Panel. Renamed `DataFrame.sort`
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135 to `sort_index`. Leaving `DataFrame.sort` for now.
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136 - Added ``skipna`` option to statistical instance methods on all the data
137 structures
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138 - `pandas.io.data` module providing a consistent interface for reading time
139 series data from several different sources
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140
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141 **Improvements to existing features**
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142
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143 * The 2-dimensional `DataFrame` and `DataMatrix` classes have been extensively
144 redesigned internally into a single class `DataFrame`, preserving where
145 possible their optimal performance characteristics. This should reduce
146 confusion from users about which class to use.
147
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148 * Note that under the hood there is a new essentially "lazy evaluation"
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149 scheme within respect to adding columns to DataFrame. During some
150 operations, like-typed blocks will be "consolidated" but not before.
151
152 * `DataFrame` accessing columns repeatedly is now significantly faster than
153 `DataMatrix` used to be in 0.3.0 due to an internal Series caching mechanism
154 (which are all views on the underlying data)
155 * Column ordering for mixed type data is now completely consistent in
156 `DataFrame`. In prior releases, there was inconsistent column ordering in
157 `DataMatrix`
158 * Improved console / string formatting of DataMatrix with negative numbers
159 * Improved tabular data parsing functions, `read_table` and `read_csv`:
160
161 * Added `skiprows` and `na_values` arguments to `pandas.io.parsers` functions
162 for more flexible IO
163 * `parseCSV` / `read_csv` functions and others in `pandas.io.parsers` now can
164 take a list of custom NA values, and also a list of rows to skip
165
166 * Can slice `DataFrame` and get a view of the data (when homogeneously typed),
167 e.g. frame.xs(idx, copy=False) or frame.ix[idx]
168 * Many speed optimizations throughout `Series` and `DataFrame`
169 * Eager evaluation of groups when calling ``groupby`` functions, so if there is
170 an exception with the grouping function it will raised immediately versus
171 sometime later on when the groups are needed
172 * `datetools.WeekOfMonth` offset can be parameterized with `n` different than 1
173 or -1.
174 * Statistical methods on DataFrame like `mean`, `std`, `var`, `skew` will now
175 ignore non-numerical data. Before a not very useful error message was
176 generated. A flag `numeric_only` has been added to `DataFrame.sum` and
177 `DataFrame.count` to enable this behavior in those methods if so desired
178 (disabled by default)
179 * `DataFrame.pivot` generalized to enable pivoting multiple columns into a
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180 `DataFrame` with hierarhical columns
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181 * `DataFrame` constructor can accept structured / record arrays
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182 * `Panel` constructor can accept a dict of DataFrame-like objects. Do not
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183 need to use `from_dict` anymore (`from_dict` is there to stay, though).
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184
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185 **API Changes**
186
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187 * The `DataMatrix` variable now refers to `DataFrame`, will be removed within
188 two releases
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189 * `WidePanel` is now known as `Panel`. The `WidePanel` variable in the pandas
190 namespace now refers to the renamed `Panel` class
191 * `LongPanel` and `Panel` / `WidePanel` now no longer have a common
192 subclass. `LongPanel` is now a subclass of `DataFrame` having a number of
193 additional methods and a hierarchical index instead of the old
194 `LongPanelIndex` object, which has been removed. Legacy `LongPanel` pickles
195 may not load properly
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196 * Cython is now required to build `pandas` from a development branch. This was
197 done to avoid continuing to check in cythonized C files into source
198 control. Builds from released source distributions will not require Cython
199 * Cython code has been moved up to a top level `pandas/src` directory. Cython
200 extension modules have been renamed and promoted from the `lib` subpackage to
201 the top level, i.e.
202
203 * `pandas.lib.tseries` -> `pandas._tseries`
204 * `pandas.lib.sparse` -> `pandas._sparse`
205
206 * `DataFrame` pickling format has changed. Backwards compatibility for legacy
207 pickles is provided, but it's recommended to consider PyTables-based
208 `HDFStore` for storing data with a longer expected shelf life
209 * A `copy` argument has been added to the `DataFrame` constructor to avoid
210 unnecessary copying of data. Data is no longer copied by default when passed
211 into the constructor
212 * Handling of boolean dtype in `DataFrame` has been improved to support storage
213 of boolean data with NA / NaN values. Before it was being converted to float64
214 so this should not (in theory) cause API breakage
215 * To optimize performance, Index objects now only check that their labels are
216 unique when uniqueness matters (i.e. when someone goes to perform a
217 lookup). This is a potentially dangerous tradeoff, but will lead to much
218 better performance in many places (like groupby).
219 * Boolean indexing using Series must now have the same indices (labels)
220 * Backwards compatibility support for begin/end/nPeriods keyword arguments in
221 DateRange class has been removed
222 * More intuitive / shorter filling aliases `ffill` (for `pad`) and `bfill` (for
223 `backfill`) have been added to the functions that use them: `reindex`,
224 `asfreq`, `fillna`.
225 * `pandas.core.mixins` code moved to `pandas.core.generic`
226 * `buffer` keyword arguments (e.g. `DataFrame.toString`) renamed to `buf` to
227 avoid using Python built-in name
228 * `DataFrame.rows()` removed (use `DataFrame.index`)
229 * Added deprecation warning to `DataFrame.cols()`, to be removed in next release
230 * `DataFrame` deprecations and de-camelCasing: `merge`, `asMatrix`,
231 `toDataMatrix`, `_firstTimeWithValue`, `_lastTimeWithValue`, `toRecords`,
232 `fromRecords`, `tgroupby`, `toString`
233 * `pandas.io.parsers` method deprecations
234
235 * `parseCSV` is now `read_csv` and keyword arguments have been de-camelCased
236 * `parseText` is now `read_table`
237 * `parseExcel` is replaced by the `ExcelFile` class and its `parse` method
238
239 * `fillMethod` arguments (deprecated in prior release) removed, should be
240 replaced with `method`
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241 * `Series.fill`, `DataFrame.fill`, and `Panel.fill` removed, use `fillna`
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242 instead
243 * `groupby` functions now exclude NA / NaN values from the list of groups. This
244 matches R behavior with NAs in factors e.g. with the `tapply` function
245 * Removed `parseText`, `parseCSV` and `parseExcel` from pandas namespace
246 * `Series.combineFunc` renamed to `Series.combine` and made a bit more general
247 with a `fill_value` keyword argument defaulting to NaN
248 * Removed `pandas.core.pytools` module. Code has been moved to
249 `pandas.core.common`
250 * Tacked on `groupName` attribute for groups in GroupBy renamed to `name`
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251 * Panel/LongPanel `dims` attribute renamed to `shape` to be more conformant
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252 * Slicing a `Series` returns a view now
253 * More Series deprecations / renaming: `toCSV` to `to_csv`, `asOf` to `asof`,
254 `merge` to `map`, `applymap` to `apply`, `toDict` to `to_dict`,
255 `combineFirst` to `combine_first`. Will print `FutureWarning`.
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256 * `DataFrame.to_csv` does not write an "index" column label by default
257 anymore since the output file can be read back without it. However, there
258 is a new ``index_label`` argument. So you can do ``index_label='index'`` to
259 emulate the old behavior
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2011-09-06 DOC: time series docs, timeRule->time_rule renaming
260 * `datetools.Week` argument renamed from `dayOfWeek` to `weekday`
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2011-09-06 DOC: more time series docs and release notes
261 * `timeRule` argument in `shift` has been deprecated in favor of using the
262 `offset` argument for everything. So you can still pass a time rule string
263 to `offset`
b808ce2b »
2011-06-06 DateRange unit test coverage, tz_validate impl
264
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265 **Bug fixes**
266
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267 * Column ordering in `pandas.io.parsers.parseCSV` will match CSV in the presence
268 of mixed-type data
269 * Fixed handling of Excel 2003 dates in `pandas.io.parsers`
270 * `DateRange` caching was happening with high resolution `DateOffset` objects,
271 e.g. `DateOffset(seconds=1)`. This has been fixed
272 * Fixed __truediv__ issue in `DataFrame`
273 * Fixed `DataFrame.toCSV` bug preventing IO round trips in some cases
274 * Fixed bug in `Series.plot` causing matplotlib to barf in exceptional cases
275 * Disabled `Index` objects from being hashable, like ndarrays
276 * Added `__ne__` implementation to `Index` so that operations like ts[ts != idx]
277 will work
278 * Added `__ne__` implementation to `DataFrame`
279 * Bug / unintuitive result when calling `fillna` on unordered labels
280 * Bug calling `sum` on boolean DataFrame
281 * Bug fix when creating a DataFrame from a dict with scalar values
282 * Series.{sum, mean, std, ...} now return NA/NaN when the whole Series is NA
283 * NumPy 1.4 through 1.6 compatibility fixes
284 * Fixed bug in bias correction in `rolling_cov`, was affecting `rolling_corr`
285 too
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2011-09-07 DOC: stats docs
286 * R-square value was incorrect in the presence of fixed and time effects in
287 the `PanelOLS` classes
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2011-09-12 DOC: doc warning fixes
288 * `HDFStore` can handle duplicates in table format, will take
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289
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290 Thanks
291 ------
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292 - Joon Ro
293 - Michael Pennington
294 - Chris Uga
295 - Chris Withers
296 - Jeff Reback
297 - Ted Square
298 - Craig Austin
299 - William Ferreira
300 - Daniel Fortunov
301 - Tony Roberts
302 - Martin Felder
303 - John Marino
304 - Tim McNamara
305 - Justin Berka
306 - Dieter Vandenbussche
1f11fe28 »
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307 - Shane Conway
308 - Skipper Seabold
309 - Chris Jordan-Squire
0f67e888 »
2011-06-14 hasty in removing matrix.py, need for legacy pickles
310
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311 pandas 0.3
312 ==========
2aeb176b »
2010-09-19 misc documentation, some work on rpy2 interface. near git migration
313
d07fbc87 »
2011-02-19 0.3.0 release notes
314 This major release of pandas represents approximately 1 year of continuous
315 development work and brings with it many new features, bug fixes, speed
316 enhancements, and general quality-of-life improvements. The most significant
2666731e »
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317 change from the 0.2 release has been the completion of a rigorous unit test
318 suite covering all of the core functionality.
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319
d07fbc87 »
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320 What is it
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321 ----------
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322
323 **pandas** is a library of labeled data structures, statistical models, and
324 general code for working with time series and cross-sectional data. It was
325 designed with the practical needs of statistical modeling and large,
326 inhomogeneous data sets in mind.
327
328 Where to get it
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329 ---------------
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330
331 Source code: http://github.com/wesm/pandas
332 Binary installers on PyPI: http://pypi.python.org/pypi/pandas
333 Documentation: http://pandas.sourceforge.net
334
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335 Release notes
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336 -------------
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337
338 **Release date:** February 20, 2011
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339
340 **New features / modules**
341
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342 * DataFrame / DataMatrix classes
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343
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344 * `corrwith` function to compute column- or row-wise correlations between two
345 objects
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346 * Can boolean-index DataFrame objects, e.g. df[df > 2] = 2, px[px > last_px] = 0
347 * Added comparison magic methods (__lt__, __gt__, etc.)
348 * Flexible explicit arithmetic methods (add, mul, sub, div, etc.)
349 * Added `reindex_like` method
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350
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351 * WidePanel
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352
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353 * Added `reindex_like` method
354
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355 * `pandas.io`: IO utilities
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356
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357 * `pandas.io.sql` module
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358
359 * Convenience functions for accessing SQL-like databases
360
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361 * `pandas.io.pytables` module
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362
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363 * Added (still experimental) HDFStore class for storing pandas data
364 structures using HDF5 / PyTables
365
366 * `pandas.core.datetools`
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367
368 * Added WeekOfMonth date offset
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369
370 * `pandas.rpy` (experimental) module created, provide some interfacing /
371 conversion between rpy2 and pandas
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372
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373 **Improvements**
374
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375 * Unit test coverage: 100% line coverage of core data structures
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376
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377 * Speed enhancement to rolling_{median, max, min}
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378
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379 * Column ordering between DataFrame and DataMatrix is now consistent: before
380 DataFrame would not respect column order
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381
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382 * Improved {Series, DataFrame}.plot methods to be more flexible (can pass
383 matplotlib Axis arguments, plot DataFrame columns in multiple subplots, etc.)
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384
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385 **API Changes**
386
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387 * Exponentially-weighted moment functions in `pandas.stats.moments`
388 have a more consistent API and accept a min_periods argument like
389 their regular moving counterparts.
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390
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391 * **fillMethod** argument in Series, DataFrame changed to **method**,
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392 `FutureWarning` added.
393
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394 * **fill** method in Series, DataFrame/DataMatrix, WidePanel renamed to
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395 **fillna**, `FutureWarning` added to **fill**
396
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397 * Renamed **DataFrame.getXS** to **xs**, `FutureWarning` added
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398
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399 * Removed **cap** and **floor** functions from DataFrame, renamed to
400 **clip_upper** and **clip_lower** for consistency with NumPy
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401
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402 **Bug fixes**
403
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404 * Fixed bug in IndexableSkiplist Cython code that was breaking
405 rolling_max function
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406
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407 * Numerous numpy.int64-related indexing fixes
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408
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409 * Several NumPy 1.4.0 NaN-handling fixes
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410
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411 * Bug fixes to pandas.io.parsers.parseCSV
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412
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413 * Fixed `DateRange` caching issue with unusual date offsets
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414
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415 * Fixed bug in `DateRange.union`
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416
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417 * Fixed corner case in `IndexableSkiplist` implementation
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