IntervalArray.from_tuples([(0, 1), (2, 3)]) Out[2]: IntervalArray([(0, 1], (2, 3]], closed='right', dtype='interval[int64]') pandas 1.0.0 1.5. Backwards incompatible API changes 9 pandas: powerful Python data from_tuples([(0, 1), (2, 3)]) Out[30]: [(0, 1], (2, 3]] Length: 2, closed: right, dtype: interval[int64] 1.5.3 DataFrame.rename now only accepts one positional argument DataFrame.rename() would “ismethods”) on an empty Series would return an object dtype instead of bool (GH29624) • 1.9.8 Interval • Bug in IntervalIndex.get_indexer() where a Categorical or CategoricalIndex target would incorrectly

the IO User Guide for more details (GH9070) • Interval, IntervalIndex, and IntervalArray have gained an is_empty attribute denoting if the given interval(s) are empty (GH27219) 8 Chapter 1. What’s new with Interval objects Indexing methods for IntervalIndex have been modified to require exact matches only for Interval queries. IntervalIndex methods previously matched on any overlapping Interval. Behavior (5, 8)]) In [43]: ii Out[43]: IntervalIndex([(0, 4], (1, 5], (5, 8]], closed='right', dtype='interval[int64]') 1.2. Backwards incompatible API changes 15 pandas: powerful Python data analysis toolkit

the IO User Guide for more details (GH9070) • Interval, IntervalIndex, and IntervalArray have gained an is_empty attribute denoting if the given interval(s) are empty (GH27219) 8 Chapter 1. What’s new with Interval objects Indexing methods for IntervalIndex have been modified to require exact matches only for Interval queries. IntervalIndex methods previously matched on any overlapping Interval. Behavior (5, 8)]) In [43]: ii Out[43]: IntervalIndex([(0, 4], (1, 5], (5, 8]], closed='right', dtype='interval[int64]') 1.2. Backwards incompatible API changes 15 pandas: powerful Python data analysis toolkit

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1840 3.5.6 Interval data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1855 powerful Python data analysis toolkit, Release 1.1.1 (continued from previous page) Categories (3, interval[float64]): [(0.995, 2.667] < (2.667, 4.333] < (4.333, 6.0]] In [42]: pd.Series([1, 2, 3, 2, 2, 2015); date1_year = year(date1); date2_month = month(date2); * shift date to beginning of next interval; date1_next = intnx('MONTH', date1, 1); * count intervals between dates; months_between = intck('MONTH'

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1840 3.5.6 Interval data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1855 powerful Python data analysis toolkit, Release 1.1.0 (continued from previous page) Categories (3, interval[float64]): [(0.995, 2.667] < (2.667, 4.333] < (4.333, 6.0]] In [42]: pd.Series([1, 2, 3, 2, 2, 2015); date1_year = year(date1); date2_month = month(date2); * shift date to beginning of next interval; date1_next = intnx('MONTH', date1, 1); * count intervals between dates; months_between = intck('MONTH'

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1765 3.5.6 Interval data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1780 968, -0.251], (-0.968, -0.251], (-0.968, -0.251], (-0. ˓→968, -0.251]] Length: 20 Categories (4, interval[float64]): [(-0.968, -0.251] < (-0.251, 0.464] < (0.464, 1. ˓→179] < (1.179, 1.893]] In [129]: (0, 1], (-1, 0], ..., (-1, 0], (-1, 0], (-1, 0], (-1, 0], (- ˓→1, 0]] Length: 20 Categories (4, interval[int64]): [(-5, -1] < (-1, 0] < (0, 1] < (1, 5]] qcut() computes sample quantiles. For example,

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1768 3.5.6 Interval data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1783 968, -0.251], (-0.968, -0.251], (-0.968, -0.251], (-0. ˓→968, -0.251]] Length: 20 Categories (4, interval[float64]): [(-0.968, -0.251] < (-0.251, 0.464] < (0.464, 1. ˓→179] < (1.179, 1.893]] In [129]: (0, 1], (-1, 0], ..., (-1, 0], (-1, 0], (-1, 0], (-1, 0], (- ˓→1, 0]] Length: 20 Categories (4, interval[int64]): [(-5, -1] < (-1, 0] < (0, 1] < (1, 5]] qcut() computes sample quantiles. For example,

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1766 4.5.6 Interval data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1781 timeseries no longer gives UserWarning (GH31205) Interval • Bug in Series.shift() with interval dtype raising a TypeError when shifting an interval array of integers or datetimes (GH34195) 1.4 Contributors 968, -0.251], (-0.968, -0.251], (-0.968, -0.251], (-0. ˓→968, -0.251]] Length: 20 Categories (4, interval[float64]): [(-0.968, -0.251] < (-0.251, 0.464] < (0.464, 1. ˓→179] < (1.179, 1.893]] In [129]:

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1872 3.5.6 Interval data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1888 (2.667, 4.333] 3 (2.667, 4.333] 4 (4.333, 6.0] 5 (4.333, 6.0] dtype: category Categories (3, interval[float64]): [(0.995, 2.667] < (2.667, 4.333] < (4.333, 6.0]] (continues on next page) 70 Chapter 2015); date1_year = year(date1); date2_month = month(date2); * shift date to beginning of next interval; date1_next = intnx('MONTH', date1, 1); * count intervals between dates; months_between = intck('MONTH'

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1960 3.5.6 Interval data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1976 (2.667, 4.333] 3 (2.667, 4.333] 4 (4.333, 6.0] 5 (4.333, 6.0] dtype: category Categories (3, interval[float64, right]): [(0.995, 2.667] < (2.667, 4.333] < (4.333, ˓→6.0]] (continues on next page) 2015); date1_year = year(date1); date2_month = month(date2); * shift date to beginning of next interval; date1_next = intnx('MONTH', date1, 1); * count intervals between dates; months_between = intck('MONTH'