(October 24, 2011) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 1.7 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 1.7 v.0.4.3 through v0.4.1 (September 25 - October 9, 2011) 1.7.1 New Features • Added Python 3 support merging / joining methods in Cython. Will be integrated later into DataFrame.join and related functions 1.7. v.0.4.3 through v0.4.1 (September 25 - October 9, 2011) 13 pandas: powerful Python data analysis

(November 25, 2011) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 1.7 v.0.5.0 (October 24, 2011) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . faster (GH327) • VBENCH Vastly improved performance of GroupBy on axes with a MultiIndex (GH299) 1.7 v.0.5.0 (October 24, 2011) 1.7.1 New Features • Added DataFrame.align method with standard join options take • Added set_eng_float_format for alternate DataFrame floating point string formatting (ENH61) 1.7. v.0.5.0 (October 24, 2011) 15 pandas: powerful Python data analysis toolkit, Release 0.7.3 • Added

print open(’data/mindex_ex.csv’).read() year,indiv,zit,xit 1977,"A",1.2,.6 1977,"B",1.5,.5 1977,"C",1.7,.8 1978,"A",.2,.06 1978,"B",.7,.2 1978,"C",.8,.3 1978,"D",.9,.5 1978,"E",1.4,.9 1979,"C",.2,.15 1979 print open(’tmp2.sv’).read() year:indiv:zit:xit 1977:A:1.2:0.59999999999999998 1977:B:1.5:0.5 1977:C:1.7:0.80000000000000004 1978:A:0.20000000000000001:0.059999999999999998 1978:B:0.69999999999999996:0.20000000000000001 read_csv(’tmp2.sv’) Out[600]: year:indiv:zit:xit 0 1977:A:1.2:0.59999999999999998 1 1977:B:1.5:0.5 2 1977:C:1.7:0.80000000000000004 3 1978:A:0.20000000000000001:0.059999999999999998 4 1978:B:0.69999999999999996:0

(February 3, 2014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 1.7 v0.13.0 (January 3, 2014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . non-unique but monotonic indexes (GH8680). • Bug when indexing a Float64Index with np.nan on numpy 1.7 (GH8980). • Fix shape attribute for MultiIndex (GH8609) • Bug in GroupBy where a name conflict between results (GH5175). • Bug in DataFrame.shift where empty columns would throw ZeroDivisionError on numpy 1.7 (GH8019) • Bug in installation where html_encoding/*.html wasn’t installed and therefore some tests

(January 22, 2013) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 1.7 v0.10.0 (December 17, 2012) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . columns] • timedelta64[ns] operations. See the docs. Warning: Most of these operations require numpy >= 1.7 1.3. v0.13.0 (January 3, 2014) 47 pandas: powerful Python data analysis toolkit, Release 0.14.0 (GH4488). • support for nanosecond times as an offset Warning: These operations require numpy >= 1.7 Period conversions in the range of seconds and below were reworked and extended up to nanoseconds

(December 17, 2012) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 1.7 v0.9.1 (November 14, 2012) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . columns] • timedelta64[ns] operations. See the docs. Warning: Most of these operations require numpy >= 1.7 Using the new top-level to_timedelta, you can convert a scalar or array from the standard timedelta Release 0.13.1 • support for nanosecond times as an offset Warning: These operations require numpy >= 1.7 Period conversions in the range of seconds and below were reworked and extended up to nanoseconds

(November 9, 2014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 1.7 v0.15.0 (October 18, 2014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . non-unique but monotonic indexes (GH8680). • Bug when indexing a Float64Index with np.nan on numpy 1.7 (GH8980). • Fix shape attribute for MultiIndex (GH8609) • Bug in GroupBy where a name conflict between invalid (GH8494) • Bug in get_quote_yahoo that wouldn’t allow non-float return values (GH5229). 1.7 v0.15.0 (October 18, 2014) This is a major release from 0.14.1 and includes a small number of API

(October 7, 2012) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 1.7 v0.8.1 (July 22, 2012) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . calendars and custom weekmasks. (GH2301) Note: This uses the numpy.busdaycalendar API introduced in Numpy 1.7 and therefore requires Numpy 1.7.0 or newer. In [41]: from pandas.tseries.offsets import CustomBusinessDay with Series (GH1915) See the full release notes or issue tracker on GitHub for a complete list. 1.7 v0.8.1 (July 22, 2012) This release includes a few new features, performance enhancements, and over

Fixes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 1.7 v0.18.0 (March 13, 2016) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . datetime-like may raise TypeError (GH12777) • Bug in pd.to_numeric() with scalar raises ValueError (GH12777) 1.7 v0.18.0 (March 13, 2016) This is a major release from 0.17.1 and includes a small number of API changes indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here. 1.7. v0.18.0 (March 13, 2016) 107 pandas: powerful Python data analysis toolkit, Release 0.20.2 • The

(January 3, 2014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 1.7 v0.12.0 (July 24, 2013) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . non-unique but monotonic indexes (GH8680). • Bug when indexing a Float64Index with np.nan on numpy 1.7 (GH8980). • Fix shape attribute for MultiIndex (GH8609) • Bug in GroupBy where a name conflict between results (GH5175). • Bug in DataFrame.shift where empty columns would throw ZeroDivisionError on numpy 1.7 (GH8019) • Bug in installation where html_encoding/*.html wasn’t installed and therefore some tests