. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 256 10.15 Dictionary-like get() method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 256 10.16 Advanced option max_info_rows, to disable null counts for large frames (GH5974) In [7]: max_info_rows = pd.get_option(’max_info_rows’) In [8]: df = DataFrame(dict(A = np.random.randn(10), ...: B = np.random.randn(10) Series.str.get_dummies vectorized string method (GH6021), to extract dummy/indicator vari- ables for separated string columns: In [23]: s = Series([’a’, ’a|b’, np.nan, ’a|c’]) In [24]: s.str.get_dummies(sep=’|’)

Fine-grained numpy errstate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 get_dummies now returns integer dtypes . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Downcast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 559 13.16 Dictionary-like get() method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 562 13.17 The select() append . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1114 pandas.HDFStore.get . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1114 pandas.HDFStore

Fine-grained numpy errstate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 get_dummies now returns integer dtypes . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Downcast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 561 13.16 Dictionary-like get() method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 564 13.17 The select() append . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1117 pandas.HDFStore.get . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1117 pandas.HDFStore

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 366 12.15 Dictionary-like get() method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 367 12.16 The select() array_split (GH8846) • Skip testing of histogram plots for matplotlib <= 1.2 (GH8648). • Bug where get_data_google returned object dtypes (GH3995) • Bug in DataFrame.stack(..., dropna=False) when the DataFrame’s data for the selected month. The month and year parameters have been undeprecated and can be used to get all options data for a given month. If an expiry date that is not valid is given, data for the next

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 282 10.15 Dictionary-like get() method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 283 10.16 Advanced idiom (GH6583), this was a regression from 0.13.1 • Added factorize functions to Index and Series to get indexer and unique values (GH7090) • describe on a DataFrame with a mix of Timestamp and string like Remove inferTimeRule keyword from Timestamp.offset() (GH391) • Remove name keyword from get_data_yahoo() and get_data_google() ( commit b921d1a ) • Remove offset keyword from DatetimeIndex constructor

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 441 13.15 Dictionary-like get() method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 443 13.16 The select() day') ....: Out[60]: x 1999-12-31 0 tolerance is also exposed by the lower level Index.get_indexer and Index.get_loc methods. • Added functionality to use the base argument when resampling a TimeDeltaIndex (October 9, 2015) 25 pandas: powerful Python data analysis toolkit, Release 0.17.0 • Bug in io.sql.get_schema when specifying multiple columns as primary key (GH10385). • Bug in groupby(sort=False) with

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 358 12.15 Dictionary-like get() method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 358 12.16 The select() data for the selected month. The month and year parameters have been undeprecated and can be used to get all options data for a given month. 1.1. v0.15.1 (November 9, 2014) 5 pandas: powerful Python data In [17]: from pandas.io.data import Options In [18]: aapl = Options(’aapl’,’yahoo’) In [19]: aapl.get_call_data().iloc[0:5,0:1] Out[19]: Last Strike Expiry Type Symbol 80 2014-11-14 call AAPL141114C00080000

Fine-grained numpy errstate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 1.8.1.10 get_dummies now returns integer dtypes . . . . . . . . . . . . . . . . . . . . . 91 1.8.1.11 Downcast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 653 12.18 Dictionary-like get() method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 656 12.19 The lookup() append . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1252 34.1.7.4 pandas.HDFStore.get . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1253 34.1.7.5 pandas.HDFStore.select

Fine-grained numpy errstate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 1.6.1.10 get_dummies now returns integer dtypes . . . . . . . . . . . . . . . . . . . . . 62 1.6.1.11 Downcast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 622 12.17 Dictionary-like get() method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 625 12.18 The select() append . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1213 34.1.7.4 pandas.HDFStore.get . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1214 34.1.7.5 pandas.HDFStore.select

are instances of SparseDataFrame. This change also affects routines using concat() internally, like get_dummies(), which now returns a DataFrame in all cases (previously a SparseDataFrame was returned if particular, 'bytes'-only data will raise an exception (except for Series.str.decode(), Series.str.get(), Series.str.len(), Series. str.slice()), see GH23163, GH23011, GH23551. Previous behavior: In [1]: Out[44]: False In [45]: pd.Interval(-10, 10, closed='both') in ii \\\\\\\\\\\\\\\Out[45]: False The get_loc() method now only returns locations for exact matches to Interval queries, as opposed to the previous