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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
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8 pandas 0.4.2
9 ============
10
11 **Release date:** not yet released
12
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13 pandas 0.4.1
14 ============
15
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16 **Release date:** 9/25/2011
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17
0af7cfa @wesm ENH: speed up assert_almost_equal
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18 This is primarily a bug fix release but includes some new features and
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19 improvements
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20
dca3c5c @wesm ENH: get_dtype_counts publicized and added dtypes property
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21 **New features / modules**
22
23 - Added new `DataFrame` methods `get_dtype_counts` and property `dtypes`
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24 - Setting of values using ``.ix`` indexing attribute in mixed-type DataFrame
25 objects has been implemented (fixes GH #135)
26 - `read_csv` can read multiple columns into a `MultiIndex`. DataFrame's
27 `to_csv` method will properly write out a `MultiIndex` which can be read
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28 back (PR #151, thanks to Skipper Seabold)
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29 - Wrote fast time series merging / joining methods in Cython. Will be
30 integrated later into DataFrame.join and related functions
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31 - Added `ignore_index` option to `DataFrame.append` for combining unindexed
32 records stored in a DataFrame
33
34 **Improvements to existing features**
35
36 - Some speed enhancements with internal Index type-checking function
37 - `DataFrame.rename` has a new `copy` parameter which can rename a DataFrame
38 in place
39 - Enable unstacking by level name (PR #142)
40 - Enable sortlevel to work by level name (PR #141)
41 - `read_csv` can automatically "sniff" other kinds of delimiters using
42 `csv.Sniffer` (PR #146)
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43 - Improved speed of unit test suite by about 40%
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44 - Exception will not be raised calling `HDFStore.remove` on non-existent node
45 with where clause
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46 - Optimized `_ensure_index` function resulting in performance savings in
47 type-checking Index objects
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48
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49 **Bug fixes**
50
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51 - Fixed DataFrame constructor bug causing downstream problems (e.g. .copy()
52 failing) when passing a Series as the values along with a column name and
53 index
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54 - Fixed single-key groupby on DataFrame with as_index=False (GH #160)
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55 - `Series.shift` was failing on integer Series (GH #154)
56 - `unstack` methods were producing incorrect output in the case of duplicate
57 hierarchical labels. An exception will now be raised (GH #147)
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58 - Calling `count` with level argument caused reduceat failure or segfault in
59 earlier NumPy (GH #169)
60 - Fixed `DataFrame.corrwith` to automatically exclude non-numeric data (GH
61 #144)
62 - Unicode handling bug fixes in `DataFrame.to_string` (GH #138)
63 - Excluding OLS degenerate unit test case that was causing platform specific
64 failure (GH #149)
65 - Skip blosc-dependent unit tests for PyTables < 2.2 (PR #137)
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66 - Calling `copy` on `DateRange` did not copy over attributes to the new object
67 (GH #168)
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68 - Fix bug in `HDFStore` in which Panel data could be appended to a Table with
69 different item order, thus resulting in an incorrect result read back
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70
71 Thanks
72 ------
73 - Yaroslav Halchenko
74 - Jeff Reback
75 - Skipper Seabold
76 - Dan Lovell
77 - Nick Pentreath
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78
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79 pandas 0.4
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80 ==========
81
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82 What is it
83 ----------
84
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85 **pandas** is a library of powerful labeled-axis data structures, statistical
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86 tools, and general code for working with relational data sets, including time
87 series and cross-sectional data. It was designed with the practical needs of
88 statistical modeling and large, inhomogeneous data sets in mind. It is
89 particularly well suited for, among other things, financial data analysis
90 applications.
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91
92 Where to get it
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93 ---------------
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94
95 Source code: http://github.com/wesm/pandas
96 Binary installers on PyPI: http://pypi.python.org/pypi/pandas
97 Documentation: http://pandas.sourceforge.net
98
99 Release notes
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100 -------------
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101
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102 **Release date:** 9/12/2011
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103
104 **New features / modules**
105
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106 - `pandas.core.sparse` module: "Sparse" (mostly-NA, or some other fill value)
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107 versions of `Series`, `DataFrame`, and `Panel`. For low-density data, this
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108 will result in significant performance boosts, and smaller memory
109 footprint. Added `to_sparse` methods to `Series`, `DataFrame`, and
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110 `Panel`. See online documentation for more on these
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111 - Fancy indexing operator on Series / DataFrame, e.g. via .ix operator. Both
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112 getting and setting of values is supported; however, setting values will only
113 currently work on homogeneously-typed DataFrame objects. Things like:
114
115 * series.ix[[d1, d2, d3]]
116 * frame.ix[5:10, ['C', 'B', 'A']], frame.ix[5:10, 'A':'C']
117 * frame.ix[date1:date2]
118
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119 - Significantly enhanced `groupby` functionality
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120
121 * Can groupby multiple keys, e.g. df.groupby(['key1', 'key2']). Iteration with
122 multiple groupings products a flattened tuple
123 * "Nuisance" columns (non-aggregatable) will automatically be excluded from
124 DataFrame aggregation operations
125 * Added automatic "dispatching to Series / DataFrame methods to more easily
126 invoke methods on groups. e.g. s.groupby(crit).std() will work even though
127 `std` is not implemented on the `GroupBy` class
128
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129 - Hierarchical / multi-level indexing
130
131 * New the `MultiIndex` class. Integrated `MultiIndex` into `Series` and
132 `DataFrame` fancy indexing, slicing, __getitem__ and __setitem,
133 reindexing, etc. Added `level` keyword argument to `groupby` to enable
134 grouping by a level of a `MultiIndex`
135
136 - New data reshaping functions: `stack` and `unstack` on DataFrame and Series
137
138 * Integrate with MultiIndex to enable sophisticated reshaping of data
139
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140 - `Index` objects (labels for axes) are now capable of holding tuples
141 - `Series.describe`, `DataFrame.describe`: produces an R-like table of summary
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142 statistics about each data column
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143 - `DataFrame.quantile`, `Series.quantile` for computing sample quantiles of data
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144 across requested axis
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145 - Added general `DataFrame.dropna` method to replace `dropIncompleteRows` and
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146 `dropEmptyRows`, deprecated those.
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147 - `Series` arithmetic methods with optional fill_value for missing data,
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148 e.g. a.add(b, fill_value=0). If a location is missing for both it will still
149 be missing in the result though.
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150 - fill_value option has been added to `DataFrame`.{add, mul, sub, div} methods
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151 similar to `Series`
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152 - Boolean indexing with `DataFrame` objects: data[data > 0.1] = 0.1 or
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153 data[data> other] = 1.
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154 - `pytz` / tzinfo support in `DateRange`
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155
156 * `tz_localize`, `tz_normalize`, and `tz_validate` methods added
157
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158 - Added `ExcelFile` class to `pandas.io.parsers` for parsing multiple sheets out
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159 of a single Excel 2003 document
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160 - `GroupBy` aggregations can now optionally *broadcast*, e.g. produce an object
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161 of the same size with the aggregated value propagated
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162 - Added `select` function in all data structures: reindex axis based on
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163 arbitrary criterion (function returning boolean value),
164 e.g. frame.select(lambda x: 'foo' in x, axis=1)
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165 - `DataFrame.consolidate` method, API function relating to redesigned internals
166 - `DataFrame.insert` method for inserting column at a specified location rather
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167 than the default __setitem__ behavior (which puts it at the end)
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168 - `HDFStore` class in `pandas.io.pytables` has been largely rewritten using
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169 patches from Jeff Reback from others. It now supports mixed-type `DataFrame`
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170 and `Series` data and can store `Panel` objects. It also has the option to
171 query `DataFrame` and `Panel` data. Loading data from legacy `HDFStore`
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172 files is supported explicitly in the code
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173 - Added `set_printoptions` method to modify appearance of DataFrame tabular
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174 output
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175 - `rolling_quantile` functions; a moving version of `Series.quantile` /
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176 `DataFrame.quantile`
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177 - Generic `rolling_apply` moving window function
178 - New `drop` method added to `Series`, `DataFrame`, etc. which can drop a set of
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179 labels from an axis, producing a new object
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180 - `reindex` methods now sport a `copy` option so that data is not forced to be
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181 copied then the resulting object is indexed the same
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182 - Added `sort_index` methods to Series and Panel. Renamed `DataFrame.sort`
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183 to `sort_index`. Leaving `DataFrame.sort` for now.
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184 - Added ``skipna`` option to statistical instance methods on all the data
185 structures
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186 - `pandas.io.data` module providing a consistent interface for reading time
187 series data from several different sources
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188
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189 **Improvements to existing features**
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190
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191 * The 2-dimensional `DataFrame` and `DataMatrix` classes have been extensively
192 redesigned internally into a single class `DataFrame`, preserving where
193 possible their optimal performance characteristics. This should reduce
194 confusion from users about which class to use.
195
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196 * Note that under the hood there is a new essentially "lazy evaluation"
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197 scheme within respect to adding columns to DataFrame. During some
198 operations, like-typed blocks will be "consolidated" but not before.
199
200 * `DataFrame` accessing columns repeatedly is now significantly faster than
201 `DataMatrix` used to be in 0.3.0 due to an internal Series caching mechanism
202 (which are all views on the underlying data)
203 * Column ordering for mixed type data is now completely consistent in
204 `DataFrame`. In prior releases, there was inconsistent column ordering in
205 `DataMatrix`
206 * Improved console / string formatting of DataMatrix with negative numbers
207 * Improved tabular data parsing functions, `read_table` and `read_csv`:
208
209 * Added `skiprows` and `na_values` arguments to `pandas.io.parsers` functions
210 for more flexible IO
211 * `parseCSV` / `read_csv` functions and others in `pandas.io.parsers` now can
212 take a list of custom NA values, and also a list of rows to skip
213
214 * Can slice `DataFrame` and get a view of the data (when homogeneously typed),
215 e.g. frame.xs(idx, copy=False) or frame.ix[idx]
216 * Many speed optimizations throughout `Series` and `DataFrame`
217 * Eager evaluation of groups when calling ``groupby`` functions, so if there is
218 an exception with the grouping function it will raised immediately versus
219 sometime later on when the groups are needed
220 * `datetools.WeekOfMonth` offset can be parameterized with `n` different than 1
221 or -1.
222 * Statistical methods on DataFrame like `mean`, `std`, `var`, `skew` will now
223 ignore non-numerical data. Before a not very useful error message was
224 generated. A flag `numeric_only` has been added to `DataFrame.sum` and
225 `DataFrame.count` to enable this behavior in those methods if so desired
226 (disabled by default)
227 * `DataFrame.pivot` generalized to enable pivoting multiple columns into a
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228 `DataFrame` with hierarhical columns
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229 * `DataFrame` constructor can accept structured / record arrays
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230 * `Panel` constructor can accept a dict of DataFrame-like objects. Do not
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231 need to use `from_dict` anymore (`from_dict` is there to stay, though).
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232
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233 **API Changes**
234
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235 * The `DataMatrix` variable now refers to `DataFrame`, will be removed within
236 two releases
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237 * `WidePanel` is now known as `Panel`. The `WidePanel` variable in the pandas
238 namespace now refers to the renamed `Panel` class
239 * `LongPanel` and `Panel` / `WidePanel` now no longer have a common
240 subclass. `LongPanel` is now a subclass of `DataFrame` having a number of
241 additional methods and a hierarchical index instead of the old
242 `LongPanelIndex` object, which has been removed. Legacy `LongPanel` pickles
243 may not load properly
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244 * Cython is now required to build `pandas` from a development branch. This was
245 done to avoid continuing to check in cythonized C files into source
246 control. Builds from released source distributions will not require Cython
247 * Cython code has been moved up to a top level `pandas/src` directory. Cython
248 extension modules have been renamed and promoted from the `lib` subpackage to
249 the top level, i.e.
250
251 * `pandas.lib.tseries` -> `pandas._tseries`
252 * `pandas.lib.sparse` -> `pandas._sparse`
253
254 * `DataFrame` pickling format has changed. Backwards compatibility for legacy
255 pickles is provided, but it's recommended to consider PyTables-based
256 `HDFStore` for storing data with a longer expected shelf life
257 * A `copy` argument has been added to the `DataFrame` constructor to avoid
258 unnecessary copying of data. Data is no longer copied by default when passed
259 into the constructor
260 * Handling of boolean dtype in `DataFrame` has been improved to support storage
261 of boolean data with NA / NaN values. Before it was being converted to float64
262 so this should not (in theory) cause API breakage
263 * To optimize performance, Index objects now only check that their labels are
264 unique when uniqueness matters (i.e. when someone goes to perform a
265 lookup). This is a potentially dangerous tradeoff, but will lead to much
266 better performance in many places (like groupby).
267 * Boolean indexing using Series must now have the same indices (labels)
268 * Backwards compatibility support for begin/end/nPeriods keyword arguments in
269 DateRange class has been removed
270 * More intuitive / shorter filling aliases `ffill` (for `pad`) and `bfill` (for
271 `backfill`) have been added to the functions that use them: `reindex`,
272 `asfreq`, `fillna`.
273 * `pandas.core.mixins` code moved to `pandas.core.generic`
274 * `buffer` keyword arguments (e.g. `DataFrame.toString`) renamed to `buf` to
275 avoid using Python built-in name
276 * `DataFrame.rows()` removed (use `DataFrame.index`)
277 * Added deprecation warning to `DataFrame.cols()`, to be removed in next release
278 * `DataFrame` deprecations and de-camelCasing: `merge`, `asMatrix`,
279 `toDataMatrix`, `_firstTimeWithValue`, `_lastTimeWithValue`, `toRecords`,
280 `fromRecords`, `tgroupby`, `toString`
281 * `pandas.io.parsers` method deprecations
282
283 * `parseCSV` is now `read_csv` and keyword arguments have been de-camelCased
284 * `parseText` is now `read_table`
285 * `parseExcel` is replaced by the `ExcelFile` class and its `parse` method
286
287 * `fillMethod` arguments (deprecated in prior release) removed, should be
288 replaced with `method`
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289 * `Series.fill`, `DataFrame.fill`, and `Panel.fill` removed, use `fillna`
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290 instead
291 * `groupby` functions now exclude NA / NaN values from the list of groups. This
292 matches R behavior with NAs in factors e.g. with the `tapply` function
293 * Removed `parseText`, `parseCSV` and `parseExcel` from pandas namespace
294 * `Series.combineFunc` renamed to `Series.combine` and made a bit more general
295 with a `fill_value` keyword argument defaulting to NaN
296 * Removed `pandas.core.pytools` module. Code has been moved to
297 `pandas.core.common`
298 * Tacked on `groupName` attribute for groups in GroupBy renamed to `name`
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299 * Panel/LongPanel `dims` attribute renamed to `shape` to be more conformant
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300 * Slicing a `Series` returns a view now
301 * More Series deprecations / renaming: `toCSV` to `to_csv`, `asOf` to `asof`,
302 `merge` to `map`, `applymap` to `apply`, `toDict` to `to_dict`,
303 `combineFirst` to `combine_first`. Will print `FutureWarning`.
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304 * `DataFrame.to_csv` does not write an "index" column label by default
305 anymore since the output file can be read back without it. However, there
306 is a new ``index_label`` argument. So you can do ``index_label='index'`` to
307 emulate the old behavior
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308 * `datetools.Week` argument renamed from `dayOfWeek` to `weekday`
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309 * `timeRule` argument in `shift` has been deprecated in favor of using the
310 `offset` argument for everything. So you can still pass a time rule string
311 to `offset`
b808ce2 @wesm DateRange unit test coverage, tz_validate impl
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312
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313 **Bug fixes**
314
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315 * Column ordering in `pandas.io.parsers.parseCSV` will match CSV in the presence
316 of mixed-type data
317 * Fixed handling of Excel 2003 dates in `pandas.io.parsers`
318 * `DateRange` caching was happening with high resolution `DateOffset` objects,
319 e.g. `DateOffset(seconds=1)`. This has been fixed
320 * Fixed __truediv__ issue in `DataFrame`
321 * Fixed `DataFrame.toCSV` bug preventing IO round trips in some cases
322 * Fixed bug in `Series.plot` causing matplotlib to barf in exceptional cases
323 * Disabled `Index` objects from being hashable, like ndarrays
324 * Added `__ne__` implementation to `Index` so that operations like ts[ts != idx]
325 will work
326 * Added `__ne__` implementation to `DataFrame`
327 * Bug / unintuitive result when calling `fillna` on unordered labels
328 * Bug calling `sum` on boolean DataFrame
329 * Bug fix when creating a DataFrame from a dict with scalar values
330 * Series.{sum, mean, std, ...} now return NA/NaN when the whole Series is NA
331 * NumPy 1.4 through 1.6 compatibility fixes
332 * Fixed bug in bias correction in `rolling_cov`, was affecting `rolling_corr`
333 too
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334 * R-square value was incorrect in the presence of fixed and time effects in
335 the `PanelOLS` classes
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336 * `HDFStore` can handle duplicates in table format, will take
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337
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338 Thanks
339 ------
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340 - Joon Ro
341 - Michael Pennington
342 - Chris Uga
343 - Chris Withers
344 - Jeff Reback
345 - Ted Square
346 - Craig Austin
347 - William Ferreira
348 - Daniel Fortunov
349 - Tony Roberts
350 - Martin Felder
351 - John Marino
352 - Tim McNamara
353 - Justin Berka
354 - Dieter Vandenbussche
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355 - Shane Conway
356 - Skipper Seabold
357 - Chris Jordan-Squire
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358
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359 pandas 0.3
360 ==========
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361
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362 This major release of pandas represents approximately 1 year of continuous
363 development work and brings with it many new features, bug fixes, speed
364 enhancements, and general quality-of-life improvements. The most significant
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365 change from the 0.2 release has been the completion of a rigorous unit test
366 suite covering all of the core functionality.
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367
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368 What is it
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369 ----------
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370
371 **pandas** is a library of labeled data structures, statistical models, and
372 general code for working with time series and cross-sectional data. It was
373 designed with the practical needs of statistical modeling and large,
374 inhomogeneous data sets in mind.
375
376 Where to get it
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377 ---------------
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378
379 Source code: http://github.com/wesm/pandas
380 Binary installers on PyPI: http://pypi.python.org/pypi/pandas
381 Documentation: http://pandas.sourceforge.net
382
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383 Release notes
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384 -------------
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385
386 **Release date:** February 20, 2011
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387
388 **New features / modules**
389
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390 * DataFrame / DataMatrix classes
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391
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392 * `corrwith` function to compute column- or row-wise correlations between two
393 objects
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394 * Can boolean-index DataFrame objects, e.g. df[df > 2] = 2, px[px > last_px] = 0
395 * Added comparison magic methods (__lt__, __gt__, etc.)
396 * Flexible explicit arithmetic methods (add, mul, sub, div, etc.)
397 * Added `reindex_like` method
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398
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399 * WidePanel
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400
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401 * Added `reindex_like` method
402
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403 * `pandas.io`: IO utilities
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404
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405 * `pandas.io.sql` module
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406
407 * Convenience functions for accessing SQL-like databases
408
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409 * `pandas.io.pytables` module
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410
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411 * Added (still experimental) HDFStore class for storing pandas data
412 structures using HDF5 / PyTables
413
414 * `pandas.core.datetools`
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415
416 * Added WeekOfMonth date offset
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417
418 * `pandas.rpy` (experimental) module created, provide some interfacing /
419 conversion between rpy2 and pandas
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420
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421 **Improvements**
422
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423 * Unit test coverage: 100% line coverage of core data structures
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424
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425 * Speed enhancement to rolling_{median, max, min}
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426
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427 * Column ordering between DataFrame and DataMatrix is now consistent: before
428 DataFrame would not respect column order
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429
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430 * Improved {Series, DataFrame}.plot methods to be more flexible (can pass
431 matplotlib Axis arguments, plot DataFrame columns in multiple subplots, etc.)
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432
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433 **API Changes**
434
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435 * Exponentially-weighted moment functions in `pandas.stats.moments`
436 have a more consistent API and accept a min_periods argument like
437 their regular moving counterparts.
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438
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439 * **fillMethod** argument in Series, DataFrame changed to **method**,
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440 `FutureWarning` added.
441
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442 * **fill** method in Series, DataFrame/DataMatrix, WidePanel renamed to
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443 **fillna**, `FutureWarning` added to **fill**
444
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445 * Renamed **DataFrame.getXS** to **xs**, `FutureWarning` added
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446
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447 * Removed **cap** and **floor** functions from DataFrame, renamed to
448 **clip_upper** and **clip_lower** for consistency with NumPy
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449
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450 **Bug fixes**
451
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452 * Fixed bug in IndexableSkiplist Cython code that was breaking
453 rolling_max function
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454
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455 * Numerous numpy.int64-related indexing fixes
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456
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457 * Several NumPy 1.4.0 NaN-handling fixes
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458
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459 * Bug fixes to pandas.io.parsers.parseCSV
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460
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461 * Fixed `DateRange` caching issue with unusual date offsets
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462
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463 * Fixed bug in `DateRange.union`
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464
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465 * Fixed corner case in `IndexableSkiplist` implementation
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