(November 14, 2012) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 1.6 v0.9.0 (October 7, 2012) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00001 1 5 1 00002 2 6 See the full release notes or issue tracker on GitHub for a complete list. 1.6 v0.9.0 (October 7, 2012) This is a major release from 0.8.1 and includes several new features and 1.8.2 NumPy datetime64 dtype and 1.6 dependency Time series data are now represented using NumPy’s datetime64 dtype; thus, pandas 0.8.0 now requires at least NumPy 1.6. It has been tested and verified

Fixes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 1.6 v0.19.0 (October 2, 2016) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 350 1.28.2 NumPy datetime64 dtype and 1.6 dependency . . . . . . . . . . . . . . . . . . . . . . . . . 350 1.28.3 Time series changes and improvements 1.5. v0.19.1 (November 3, 2016) 51 pandas: powerful Python data analysis toolkit, Release 0.20.3 1.6 v0.19.0 (October 2, 2016) This is a major release from 0.18.1 and includes number of API changes,

(February 3, 2014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 1.6 v0.13.0 (January 3, 2014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . notes or issue tracker on GitHub for a complete list of all API changes, Enhancements and Bug Fixes. 1.6 v0.13.0 (January 3, 2014) This is a major release from 0.12.0 and includes a number of API changes familiar with SQL but still learning pandas. • Comparison with R, idiom translations from R to pandas. 1.6. v0.13.0 (January 3, 2014) 75 pandas: powerful Python data analysis toolkit, Release 0.15.1 • Enhancing

(January 22, 2013) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 1.6 v0.10.0 (December 17, 2012) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . (GH2689, GH2629, GH2626) See the full release notes or issue tracker on GitHub for a complete list. 1.6 v0.10.0 (December 17, 2012) This is a major release from 0.9.1 and includes many new features and In [2]: df = pd.DataFrame(np.random.randn(6, 4), ...: index=pd.date_range(’1/1/2000’, periods=6)) 1.6. v0.10.0 (December 17, 2012) 59 pandas: powerful Python data analysis toolkit, Release 0.13.1 ..

Fixes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 ii 1.6 v0.17.0 (October 9, 2015) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 302 1.24.2 NumPy datetime64 dtype and 1.6 dependency . . . . . . . . . . . . . . . . . . . . . . . . . 302 1.24.3 Time series changes and improvements Development installed versions of pandas will now have PEP440 compliant version strings (GH9518) 1.6. v0.17.0 (October 9, 2015) 97 pandas: powerful Python data analysis toolkit, Release 0.19.1 • Development

(April 22, 2013) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 1.6 v0.10.1 (January 22, 2013) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . to < and >. (GH2919) See the full release notes or issue tracker on GitHub for a complete list. 1.6 v0.10.1 (January 22, 2013) This is a minor release from 0.10.0 and includes new features, enhancements string == ’foo’)] Out[10]: A B C string string2 2000-01-04 -0.761218 1.768215 0.152288 foo cool 1.6. v0.10.1 (January 22, 2013) 81 pandas: powerful Python data analysis toolkit, Release 0.14.0 [1 rows

(May 31 , 2014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 1.6 v0.13.1 (February 3, 2014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . (GH5198) 1.5. v0.14.0 (May 31 , 2014) 73 pandas: powerful Python data analysis toolkit, Release 0.15.2 1.6 v0.13.1 (February 3, 2014) This is a minor release from 0.13.0 and includes a small number of API 0 1 2 1 3 4 In [17]: pd.set_option(’show_dimensions’, True) In [18]: df Out[18]: 0 1 0 1 2 1.6. v0.13.1 (February 3, 2014) 75 pandas: powerful Python data analysis toolkit, Release 0.15.2 1 3

Fixes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 1.6 v0.18.1 (May 3, 2016) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 348 1.27.2 NumPy datetime64 dtype and 1.6 dependency . . . . . . . . . . . . . . . . . . . . . . . . . 348 1.27.3 Time series changes and improvements 1.5. v0.19.0 (October 2, 2016) 89 pandas: powerful Python data analysis toolkit, Release 0.20.2 1.6 v0.18.1 (May 3, 2016) This is a minor bug-fix release from 0.18.0 and includes a large number of bug

(December 12, 2014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 1.6 v0.15.1 (November 9, 2014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . the to nano-second conversion twice. (GH9011). • Bug in plotting of a period-like array (GH9012) 1.6 v0.15.1 (November 9, 2014) This is a minor bug-fix release from 0.15.0 and includes a small number We recommend that all users upgrade to this version. • Enhancements • API Changes • Bug Fixes 1.6. v0.15.1 (November 9, 2014) 63 pandas: powerful Python data analysis toolkit, Release 0.17.0 1.6

(October 24, 2011) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 1.6 v.0.4.3 through v0.4.1 (September 25 - October 9, 2011) . . . . . . . . . . . . . . . . . . . . . VBENCH Significantly speed up DataFrame __repr__ and count on large mixed-type DataFrame objects 1.6 v.0.4.3 through v0.4.1 (September 25 - October 9, 2011) 1.6.1 New Features • Added Python 3 support merging / joining methods in Cython. Will be integrated later into DataFrame.join and related functions 1.6. v.0.4.3 through v0.4.1 (September 25 - October 9, 2011) 13 pandas: powerful Python data analysis