Fixes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 1.9 v0.17.0 (October 9, 2015) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . DataFrame.round() with decimals being a non-unique indexed Series producing extra columns (GH11618) 1.9 v0.17.0 (October 9, 2015) This is a major release from 0.16.2 and includes a small number of API changes to_datetime and to_timedelta * Error handling * Consistent Parsing – Changes to Index Comparisons 1.9. v0.17.0 (October 9, 2015) 143 pandas: powerful Python data analysis toolkit, Release 0.20.2 – Changes

11, 2014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 1.9 v0.14.0 (May 31 , 2014) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . , periods=5)}) ....: In [58]: df.reindex([0.1, 1.9, 3.5], ....: method='nearest', ....: tolerance=0.2) ....: Out[58]: t x 0.1 2000-01-01 0 1.9 2000-01-03 2 3.5 NaT NaN When used on a DatetimeIndex 1.8. v0.14.1 (July 11, 2014) 101 pandas: powerful Python data analysis toolkit, Release 0.17.0 1.9 v0.14.0 (May 31 , 2014) This is a major release from 0.13.1 and includes a small number of API changes

Fixes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 1.9 v0.18.1 (May 3, 2016) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . (GH14302) 120 Chapter 1. What’s New pandas: powerful Python data analysis toolkit, Release 0.21.1 1.9 v0.18.1 (May 3, 2016) This is a minor bug-fix release from 0.18.0 and includes a large number of bug to_datetime error changes – Other API changes – Deprecations • Performance Improvements • Bug Fixes 1.9. v0.18.1 (May 3, 2016) 121 pandas: powerful Python data analysis toolkit, Release 0.21.1 1.9.1 New

What’s new in 1.0.0 (January 29, 2020) pandas: powerful Python data analysis toolkit, Release 1.0.0 1.9 Bug fixes 1.9.1 Categorical • Added test to assert the fillna() raises the correct ValueError message when subtracting a Timestamp from a np.datetime64 object incorrectly raising TypeError (GH28286) 1.9. Bug fixes 25 pandas: powerful Python data analysis toolkit, Release 1.0.0 • Addition and subtraction DataFrame.diff raising an IndexError when one of the columns was a nullable integer dtype (GH30967) 1.9. Bug fixes 27 pandas: powerful Python data analysis toolkit, Release 1.0.0 1.9.6 Conversion • •

Fixes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 1.9 v0.16.0 (March 22, 2015) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . toolkit, Release 0.19.1 In [58]: df.reindex([0.1, 1.9, 3.5], ....: method='nearest', ....: tolerance=0.2) ....: Out[58]: t x 0.1 2000-01-01 0.0 1.9 2000-01-03 2.0 3.5 NaT NaN When used on a DatetimeIndex that all users upgrade to this version. Highlights include: • DataFrame.assign method, see here 1.9. v0.16.0 (March 22, 2015) 137 pandas: powerful Python data analysis toolkit, Release 0.19.1 • Series

Fixes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136 1.9 v0.17.1 (November 21, 2015) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . (GH12344) 138 Chapter 1. What’s New pandas: powerful Python data analysis toolkit, Release 0.20.3 1.9 v0.17.1 (November 21, 2015) Note: We are proud to announce that pandas has become a sponsored project style.background_gradient(cmap='viridis', low=.5) We can render the HTML to get the following table. 1.9. v0.17.1 (November 21, 2015) 139 pandas: powerful Python data analysis toolkit, Release 0.20.3 Styler

29, 2012) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 1.9 v.0.7.3 (April 12, 2012) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . index.is_unique and raise an exception explicitly if it is False or go to a different code branch. 1.9 v.0.7.3 (April 12, 2012) This is a minor release from 0.7.2 and fixes many minor bugs and adds a number method for stacked bar plots. df.plot(kind=’bar’, stacked=True) df.plot(kind=’barh’, stacked=True) 1.9. v.0.7.3 (April 12, 2012) 51 pandas: powerful Python data analysis toolkit, Release 0.12.0 • Add

24, 2013) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 1.9 v0.11.0 (April 22, 2013) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . - boolean operations on numpy arrays in favor of inv ~, as this is going to be deprecated in numpy 1.9 (GH6960) 1.5.9 Deprecations • The pivot_table()/DataFrame.pivot_table() and crosstab() functions [4]: Series(1,np.arange(5.))[3] Out[4]: 1 In [5]: Series(1,np.arange(5.))[3.0] Out[6]: 1 • Numpy 1.9 compat w.r.t. deprecation warnings (GH6960) • Panel.shift() now has a function signature that matches

9,.5 1978,"E",1.4,.9 1979,"C",.2,.15 1979,"D",.14,.05 1979,"E",.5,.15 1979,"F",1.2,.5 1979,"G",3.4,1.9 1979,"H",5.4,2.7 1979,"I",6.4,1.2 The index_col argument to read_csv can take a list of column numbers Release 1.4.2 (continued from previous page) {\cellcolor[HTML]{FCA108}} \color[HTML]{000000} 0.79 & 1.9 & 3.5 & 14.1 & 19.8 & \color[HTML]{FFDD33} \bfseries HOLD \\ \cline{1-11} \multirow[c]{2}{*}{Consumer} 2, 2, 2, 3, 3, 3], ... 'birth': [1, 2, 3, 1, 2, 3, 1, 2, 3], ... 'ht1': [2.8, 2.9, 2.2, 2, 1.8, 1.9, 2.2, 2.3, 2.1], ... 'ht2': [3.4, 3.8, 2.9, 3.2, 2.8, 2.4, 3.3, 3.4, 2.9] ... }) >>> df famid birth

9,.5 1978,"E",1.4,.9 1979,"C",.2,.15 1979,"D",.14,.05 1979,"E",.5,.15 1979,"F",1.2,.5 1979,"G",3.4,1.9 1979,"H",5.4,2.7 1979,"I",6.4,1.2 The index_col argument to read_csv can take a list of column numbers 2, 2, 2, 3, 3, 3], ... 'birth': [1, 2, 3, 1, 2, 3, 1, 2, 3], ... 'ht1': [2.8, 2.9, 2.2, 2, 1.8, 1.9, 2.2, 2.3, 2.1], ... 'ht2': [3.4, 3.8, 2.9, 3.2, 2.8, 2.4, 3.3, 3.4, 2.9] ... }) >>> df famid birth birth ht1 ht2 0 1 1 2.8 3.4 1 1 2 2.9 3.8 2 1 3 2.2 2.9 3 2 1 2.0 3.2 4 2 2 1.8 2.8 5 2 3 1.9 2.4 6 3 1 2.2 3.3 7 3 2 2.3 3.4 8 3 3 2.1 2.9 >>> l = pd.wide_to_long(df, stubnames='ht', i=['famid'