implementation from pandas that depends on operators that are already defined on the underly- ing elements (scalars) of the ExtensionArray. See the ExtensionArray Operator Support documentation section Using DataFrame.itertuples() now creates itera- tors without internally allocating lists of all elements (GH20783) • Improved performance of Period constructor, additionally benefitting PeriodArray and • Bug in Series.hasnans() that could be incorrectly cached and return incorrect answers if null elements are introduced after an initial call (GH19700) • Series.isin() now treats all NaN-floats as equal

cases better (GH6531): – df.iloc[:-len(df)] is now empty – df.iloc[len(df)::-1] now enumerates all elements in reverse 4 Chapter 1. What’s New pandas: powerful Python data analysis toolkit, Release 0.14 prior to 0.14. (GH6760) • Added nunique and value_counts functions to Index for counting unique elements. (GH6734) • stack and unstack now raise a ValueError when the level keyword refers to a non-unique It contains both list and itera- tor versions of range, filter, map and zip, plus other necessary elements for Python 3 compatibility. lmap, lzip, lrange and lfilter all produce lists instead of iterators

uniquely valued Index objects when called with cache=True, with arg including at least two different elements from the set {None, numpy.nan, pandas.NaT} (GH22305) • Bug in DataFrame and Series where timezone in Project Governance documents. The documents clarify how decisions are made and how the various elements of our commu- nity interact, including the relationship between open source collaborative development sample of a Series or DataFrame object, use the head() and tail() methods. The default number of elements to display is five, but you may pass a custom number. In [4]: long_series = pd.Series(np.random

uniquely valued Index objects when called with cache=True, with arg including at least two different elements from the set {None, numpy.nan, pandas.NaT} (GH22305) • Bug in DataFrame and Series where timezone in Project Governance documents. The documents clarify how decisions are made and how the various elements of our commu- nity interact, including the relationship between open source collaborative development sample of a Series or DataFrame object, use the head() and tail() methods. The default number of elements to display is five, but you may pass a custom number. In [4]: long_series = pd.Series(np.random

in Project Governance documents. The documents clarify how decisions are made and how the various elements of our commu- nity interact, including the relationship between open source collaborative development values can be assigned to the selected data. For example, to assign the name anonymous to the first 3 elements of the third column: In [26]: titanic.iloc[0:3, 3] = "anonymous" In [27]: titanic.head() Out[27]: These methods have in general matching names with the equivalent built-in string methods for single elements, but are applied element-wise (remember element-wise calculations?) on each of the values of the

in Project Governance documents. The documents clarify how decisions are made and how the various elements of our commu- nity interact, including the relationship between open source collaborative development values can be assigned to the selected data. For example, to assign the name anonymous to the first 3 elements of the third column: In [26]: titanic.iloc[0:3, 3] = "anonymous" In [27]: titanic.head() Out[27]: These methods have in general matching names with the equivalent built-in string methods for single elements, but are applied element-wise (remember element-wise calculations?) on each of the values of the

in Project Governance documents. The documents clarify how decisions are made and how the various elements of our commu- nity interact, including the relationship between open source collaborative development values can be assigned to the selected data. For example, to assign the name anonymous to the first 3 elements of the third column: In [26]: titanic.iloc[0:3, 3] = "anonymous" In [27]: titanic.head() Out[27]: These methods have in general matching names with the equivalent built-in string methods for single elements, but are applied element-wise (remember element-wise calculations?) on each of the values of the

in Project Governance documents. The documents clarify how decisions are made and how the various elements of our commu- nity interact, including the relationship between open source collaborative development sample of a Series or DataFrame object, use the head() and tail() methods. The default number of elements to display is five, but you may pass a custom number. In [4]: long_series = pd.Series(np.random force a conversion, we can pass in an errors argument, which specifies how pandas should deal with elements that cannot be converted to desired dtype or object. By default, errors='raise', meaning that any

in Project Governance documents. The documents clarify how decisions are made and how the various elements of our commu- nity interact, including the relationship between open source collaborative development values can be assigned to the selected data. For example, to assign the name anonymous to the first 3 elements of the third column: In [26]: titanic.iloc[0:3, 3] = "anonymous" In [27]: titanic.head() Out[27]: These methods have in general matching names with the equivalent built-in string methods for single elements, but are applied element-wise (remember element-wise calculations?) on each of the values of the

in Project Governance documents. The documents clarify how decisions are made and how the various elements of our commu- nity interact, including the relationship between open source collaborative development values can be assigned to the selected data. For example, to assign the name anonymous to the first 3 elements of the third column: In [26]: titanic.iloc[0:3, 3] = "anonymous" In [27]: titanic.head() Out[27]: These methods have in general matching names with the equivalent built-in string methods for single elements, but are applied element-wise (remember element-wise calculations?) on each of the values of the