aligns the input to the Panel In [20]: p = pd.Panel(np.arange(16).reshape(2,4,2), ....: items=[’Item1’,’Item2’], ....: major_axis=pd.date_range(’2001/1/12’,periods=4), ....: minor_axis=[’A’,’B’],dtype=’float64’) ’pandas.core.panel.Panel’> Dimensions: 2 (items) x 4 (major_axis) x 2 (minor_axis) Items axis: Item1 to Item2 Major_axis axis: 2001-01-12 00:00:00 to 2001-01-15 00:00:00 1.2. v0.13.0 (January 3, 2014) 15 x 3 (minor_axis) Items axis: Item1 to Item2 Major_axis axis: 2001-01-12 00:00:00 to 2001-01-15 00:00:00 Minor_axis axis: A to C In [24]: p.loc[:,:,’C’] Out[24]: Item1 Item2 2001-01-12 30 32 2001-01-13

w dtype: object In [52]: s 0 NaN 1 NaN 2 NaN 3 w dtype: object In [53]: s.dropna().values.item() == ’w’ True The last element yielded by the iterator will be a Series containing the last element 0.236846 2000-01-08 0.323316 -0.584380 0.545657 In [50]: wp = Panel(randn(2, 5, 4), items=[’Item1’, ’Item2’], ....: major_axis=date_range(’1/1/2000’, periods=5), ....: minor_axis=[’A’, ’B’, ’C’, ’D’]) ’pandas.core.panel.Panel’> Dimensions: 2 (items) x 5 (major_axis) x 4 (minor_axis) Items axis: Item1 to Item2 Major_axis axis: 2000-01-01 00:00:00 to 2000-01-05 00:00:00 Minor_axis axis: A to D # storing

(GH6734) • stack and unstack now raise a ValueError when the level keyword refers to a non-unique item in the Index (previously raised a KeyError). (GH6738) • drop unused order argument from Series.sort; with xlwt (GH3710) • Refactor Block classes removing Block.items attributes to avoid duplication in item handling (GH6745, GH6988). • Testing statements updated to use specialized asserts (GH6175) 1.1 aligns the input to the Panel In [20]: p = pd.Panel(np.arange(16).reshape(2,4,2), ....: items=[’Item1’,’Item2’], ....: major_axis=pd.date_range(’2001/1/12’,periods=4), ....: minor_axis=[’A’,’B’],dtype=’float64’)

(GH7762, GH7032). • Bug in Series.str.cat with an index which was filtered as to not include the first item (GH7857) • Bug in Timestamp cannot parse nanosecond from string (GH7878) • Bug in Timestamp with a DataFrame which has unexpected results. Such indexing is no longer permitted (GH8444) • Bug in item assignment of a DataFrame with multi-index columns where right-hand-side columns were not aligned TypeError on inplace-setting with a .where and a non np.nan value as this is inconsistent with a set-item expression like df[mask] = None (GH7656) 1.4.2 Enhancements • Add dropna argument to value_counts

(GH7762, GH7032). • Bug in Series.str.cat with an index which was filtered as to not include the first item (GH7857) • Bug in Timestamp cannot parse nanosecond from string (GH7878) • Bug in Timestamp with a DataFrame which has unexpected results. Such indexing is no longer permitted (GH8444) • Bug in item assignment of a DataFrame with multi-index columns where right-hand-side columns were not aligned TypeError on inplace-setting with a .where and a non np.nan value as this is inconsistent with a set-item expression like df[mask] = None (GH7656) 1.3.2 Enhancements • Add dropna argument to value_counts

129 1.0000 dtype: float64 • A Spurious SettingWithCopy Warning was generated when setting a new item in a frame in some cases (GH8730) The following would previously report a SettingWithCopy Warning (GH7762, GH7032). • Bug in Series.str.cat with an index which was filtered as to not include the first item (GH7857) • Bug in Timestamp cannot parse nanosecond from string (GH7878) • Bug in Timestamp with a DataFrame which has unexpected results. Such indexing is no longer permitted (GH8444) • Bug in item assignment of a DataFrame with multi-index columns where right-hand-side columns were not aligned

and DataFrame for broadcasting values across a level (GH542, PR552, others) • Add attribute-based item access to Panel and add IPython completion (PR563) • Add logy option to Series.plot for log-scaling analysis toolkit, Release 0.7.3 • Can pass MaskedArray to Series constructor (PR563) • Add Panel item access via attributes and IPython completion (GH554) • Implement DataFrame.lookup, fancy-indexing collection of DataFrame objects, you may find the axis names slightly arbitrary: • items: axis 0, each item corresponds to a DataFrame contained inside • major_axis: axis 1, it is the index (rows) of each

From DataFrame using to_panel method . . . . . . . . . . . . . . . . . . . . . . . . . . 435 9.3.4 Item selection / addition / deletion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 436 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1577 pandas.Index.item . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1578 pandas.Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1604 pandas.CategoricalIndex.item . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1604 pandas.CategoricalIndex

From DataFrame using to_panel method . . . . . . . . . . . . . . . . . . . . . . . . . . 437 9.3.4 Item selection / addition / deletion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 437 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1581 pandas.Index.item . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1581 pandas.Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1607 pandas.CategoricalIndex.item . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1608 pandas.CategoricalIndex

and DataFrame for broadcasting values across a level (GH542, PR552, others) • Add attribute-based item access to Panel and add IPython completion (PR563) • Add logy option to Series.plot for log-scaling for potential speedups (GH595) • Can pass MaskedArray to Series constructor (PR563) • Add Panel item access via attributes and IPython completion (GH554) • Implement DataFrame.lookup, fancy-indexing collection of DataFrame objects, you may find the axis names slightly arbitrary: • items: axis 0, each item corresponds to a DataFrame contained inside • major_axis: axis 1, it is the index (rows) of each