From 3e0ee89e7ebbf98659ea18dbed5b1bb345c6880b Mon Sep 17 00:00:00 2001
From: Tom Augspurger <tom.w.augspurger@gmail.com>
Date: Fri, 25 Jan 2019 06:22:03 -0600
Subject: [PATCH 1/4] API: Remove IntervalArray from top-level
---
doc/source/api/arrays.rst | 4 ++--
doc/source/whatsnew/v0.24.0.rst | 4 ++--
pandas/core/api.py | 1 -
pandas/core/arrays/array_.py | 2 +-
pandas/tests/api/test_api.py | 1 -
5 files changed, 5 insertions(+), 7 deletions(-)
diff --git a/doc/source/api/arrays.rst b/doc/source/api/arrays.rst
index 5ecc5181af22c..ff1b9f3cecaac 100644
--- a/doc/source/api/arrays.rst
+++ b/doc/source/api/arrays.rst
@@ -288,12 +288,12 @@ Properties
Interval.overlaps
Interval.right
-A collection of intervals may be stored in an :class:`IntervalArray`.
+A collection of intervals may be stored in an :class:`arrays.IntervalArray`.
.. autosummary::
:toctree: generated/
- IntervalArray
+ arrays.IntervalArray
IntervalDtype
.. _api.arrays.integer_na:
diff --git a/doc/source/whatsnew/v0.24.0.rst b/doc/source/whatsnew/v0.24.0.rst
index f0f99d2def136..d3d8863df9fd5 100644
--- a/doc/source/whatsnew/v0.24.0.rst
+++ b/doc/source/whatsnew/v0.24.0.rst
@@ -225,7 +225,7 @@ from the ``Series``:
ser.array
pser.array
-These return an instance of :class:`IntervalArray` or :class:`arrays.PeriodArray`,
+These return an instance of :class:`arrays.IntervalArray` or :class:`arrays.PeriodArray`,
the new extension arrays that back interval and period data.
.. warning::
@@ -411,7 +411,7 @@ Other Enhancements
- :meth:`Categorical.from_codes` now can take a ``dtype`` parameter as an alternative to passing ``categories`` and ``ordered`` (:issue:`24398`).
- New attribute ``__git_version__`` will return git commit sha of current build (:issue:`21295`).
- Compatibility with Matplotlib 3.0 (:issue:`22790`).
-- Added :meth:`Interval.overlaps`, :meth:`IntervalArray.overlaps`, and :meth:`IntervalIndex.overlaps` for determining overlaps between interval-like objects (:issue:`21998`)
+- Added :meth:`Interval.overlaps`, :meth:`arrays.IntervalArray.overlaps`, and :meth:`IntervalIndex.overlaps` for determining overlaps between interval-like objects (:issue:`21998`)
- :func:`read_fwf` now accepts keyword ``infer_nrows`` (:issue:`15138`).
- :func:`~DataFrame.to_parquet` now supports writing a ``DataFrame`` as a directory of parquet files partitioned by a subset of the columns when ``engine = 'pyarrow'`` (:issue:`23283`)
- :meth:`Timestamp.tz_localize`, :meth:`DatetimeIndex.tz_localize`, and :meth:`Series.tz_localize` have gained the ``nonexistent`` argument for alternative handling of nonexistent times. See :ref:`timeseries.timezone_nonexistent` (:issue:`8917`, :issue:`24466`)
diff --git a/pandas/core/api.py b/pandas/core/api.py
index afc929c39086c..8c92287e212a6 100644
--- a/pandas/core/api.py
+++ b/pandas/core/api.py
@@ -4,7 +4,6 @@
import numpy as np
-from pandas.core.arrays import IntervalArray
from pandas.core.arrays.integer import (
Int8Dtype,
Int16Dtype,
diff --git a/pandas/core/arrays/array_.py b/pandas/core/arrays/array_.py
index c7be8e3f745c4..41d623c7efd9c 100644
--- a/pandas/core/arrays/array_.py
+++ b/pandas/core/arrays/array_.py
@@ -50,7 +50,7 @@ def array(data, # type: Sequence[object]
============================== =====================================
Scalar Type Array Type
============================== =====================================
- :class:`pandas.Interval` :class:`pandas.IntervalArray`
+ :class:`pandas.Interval` :class:`pandas.arrays.IntervalArray`
:class:`pandas.Period` :class:`pandas.arrays.PeriodArray`
:class:`datetime.datetime` :class:`pandas.arrays.DatetimeArray`
:class:`datetime.timedelta` :class:`pandas.arrays.TimedeltaArray`
diff --git a/pandas/tests/api/test_api.py b/pandas/tests/api/test_api.py
index 07cf358c765b3..599ab9a3c5f7c 100644
--- a/pandas/tests/api/test_api.py
+++ b/pandas/tests/api/test_api.py
@@ -46,7 +46,6 @@ class TestPDApi(Base):
'Series', 'SparseArray', 'SparseDataFrame', 'SparseDtype',
'SparseSeries', 'Timedelta',
'TimedeltaIndex', 'Timestamp', 'Interval', 'IntervalIndex',
- 'IntervalArray',
'CategoricalDtype', 'PeriodDtype', 'IntervalDtype',
'DatetimeTZDtype',
'Int8Dtype', 'Int16Dtype', 'Int32Dtype', 'Int64Dtype',
From ffaecf1b3c029bd4b21be49f591720bce58b306a Mon Sep 17 00:00:00 2001
From: Tom Augspurger <tom.w.augspurger@gmail.com>
Date: Fri, 25 Jan 2019 07:03:01 -0600
Subject: [PATCH 2/4] fixups
---
pandas/core/arrays/interval.py | 2 +-
pandas/tests/arrays/test_array.py | 4 ++--
2 files changed, 3 insertions(+), 3 deletions(-)
diff --git a/pandas/core/arrays/interval.py b/pandas/core/arrays/interval.py
index 45470e03c041a..82f985698bd1b 100644
--- a/pandas/core/arrays/interval.py
+++ b/pandas/core/arrays/interval.py
@@ -115,7 +115,7 @@
A new ``IntervalArray`` can be constructed directly from an array-like of
``Interval`` objects:
- >>> pd.IntervalArray([pd.Interval(0, 1), pd.Interval(1, 5)])
+ >>> pandas.IntervalArray([pd.Interval(0, 1), pd.Interval(1, 5)])
IntervalArray([(0, 1], (1, 5]],
closed='right',
dtype='interval[int64]')
diff --git a/pandas/tests/arrays/test_array.py b/pandas/tests/arrays/test_array.py
index 4a51fd63d963b..9fea1989e46df 100644
--- a/pandas/tests/arrays/test_array.py
+++ b/pandas/tests/arrays/test_array.py
@@ -74,7 +74,7 @@
# Interval
([pd.Interval(1, 2), pd.Interval(3, 4)], 'interval',
- pd.IntervalArray.from_tuples([(1, 2), (3, 4)])),
+ pd.arrays.IntervalArray.from_tuples([(1, 2), (3, 4)])),
# Sparse
([0, 1], 'Sparse[int64]', pd.SparseArray([0, 1], dtype='int64')),
@@ -129,7 +129,7 @@ def test_array_copy():
# interval
([pd.Interval(0, 1), pd.Interval(1, 2)],
- pd.IntervalArray.from_breaks([0, 1, 2])),
+ pd.arrays.IntervalArray.from_breaks([0, 1, 2])),
# datetime
([pd.Timestamp('2000',), pd.Timestamp('2001')],
From e79cdcf8fa44370ae5bcf7c02bba60136c63d08d Mon Sep 17 00:00:00 2001
From: Joris Van den Bossche <jorisvandenbossche@gmail.com>
Date: Fri, 25 Jan 2019 07:15:36 -0600
Subject: [PATCH 3/4] Update pandas/core/arrays/interval.py
Co-Authored-By: TomAugspurger <TomAugspurger@users.noreply.github.com>
---
pandas/core/arrays/interval.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/pandas/core/arrays/interval.py b/pandas/core/arrays/interval.py
index 82f985698bd1b..67d7281a91b4c 100644
--- a/pandas/core/arrays/interval.py
+++ b/pandas/core/arrays/interval.py
@@ -115,7 +115,7 @@
A new ``IntervalArray`` can be constructed directly from an array-like of
``Interval`` objects:
- >>> pandas.IntervalArray([pd.Interval(0, 1), pd.Interval(1, 5)])
+ >>> pd.arrays.IntervalArray([pd.Interval(0, 1), pd.Interval(1, 5)])
IntervalArray([(0, 1], (1, 5]],
closed='right',
dtype='interval[int64]')
From 86ec7b9951d5097a460e42931bce6ed9ee8f51ae Mon Sep 17 00:00:00 2001
From: Tom Augspurger <tom.w.augspurger@gmail.com>
Date: Fri, 25 Jan 2019 08:18:32 -0600
Subject: [PATCH 4/4] doctests
---
pandas/core/arrays/interval.py | 27 ++++++++++++++-------------
pandas/core/indexes/interval.py | 23 ++++++++++++-----------
2 files changed, 26 insertions(+), 24 deletions(-)
diff --git a/pandas/core/arrays/interval.py b/pandas/core/arrays/interval.py
index 67d7281a91b4c..1e671c7bd956a 100644
--- a/pandas/core/arrays/interval.py
+++ b/pandas/core/arrays/interval.py
@@ -32,6 +32,7 @@
_shared_docs_kwargs = dict(
klass='IntervalArray',
+ qualname='arrays.IntervalArray',
name=''
)
@@ -248,8 +249,8 @@ def _from_factorized(cls, values, original):
Examples
--------
- >>> pd.%(klass)s.from_breaks([0, 1, 2, 3])
- %(klass)s([(0, 1], (1, 2], (2, 3]]
+ >>> pd.%(qualname)s.from_breaks([0, 1, 2, 3])
+ %(klass)s([(0, 1], (1, 2], (2, 3]],
closed='right',
dtype='interval[int64]')
"""
@@ -311,7 +312,7 @@ def from_breaks(cls, breaks, closed='right', copy=False, dtype=None):
Examples
--------
>>> %(klass)s.from_arrays([0, 1, 2], [1, 2, 3])
- %(klass)s([(0, 1], (1, 2], (2, 3]]
+ %(klass)s([(0, 1], (1, 2], (2, 3]],
closed='right',
dtype='interval[int64]')
"""
@@ -354,16 +355,16 @@ def from_arrays(cls, left, right, closed='right', copy=False, dtype=None):
Examples
--------
- >>> pd.%(klass)s.from_intervals([pd.Interval(0, 1),
+ >>> pd.%(qualname)s.from_intervals([pd.Interval(0, 1),
... pd.Interval(1, 2)])
- %(klass)s([(0, 1], (1, 2]]
+ %(klass)s([(0, 1], (1, 2]],
closed='right', dtype='interval[int64]')
The generic Index constructor work identically when it infers an array
of all intervals:
>>> pd.Index([pd.Interval(0, 1), pd.Interval(1, 2)])
- %(klass)s([(0, 1], (1, 2]]
+ %(klass)s([(0, 1], (1, 2]],
closed='right', dtype='interval[int64]')
"""
@@ -394,7 +395,7 @@ def from_arrays(cls, left, right, closed='right', copy=False, dtype=None):
Examples
--------
- >>> pd.%(klass)s.from_tuples([(0, 1), (1, 2)])
+ >>> pd.%(qualname)s.from_tuples([(0, 1), (1, 2)])
%(klass)s([(0, 1], (1, 2]],
closed='right', dtype='interval[int64]')
"""
@@ -891,13 +892,13 @@ def closed(self):
Examples
--------
- >>> index = pd.interval_range(0, 3)
- >>> index
- %(klass)s([(0, 1], (1, 2], (2, 3]]
+ >>> index = pd.interval_range(0, 3)
+ >>> index
+ IntervalIndex([(0, 1], (1, 2], (2, 3]],
closed='right',
dtype='interval[int64]')
- >>> index.set_closed('both')
- %(klass)s([[0, 1], [1, 2], [2, 3]]
+ >>> index.set_closed('both')
+ IntervalIndex([[0, 1], [1, 2], [2, 3]],
closed='both',
dtype='interval[int64]')
"""
@@ -1039,7 +1040,7 @@ def repeat(self, repeats, axis=None):
Examples
--------
- >>> intervals = pd.%(klass)s.from_tuples([(0, 1), (1, 3), (2, 4)])
+ >>> intervals = pd.%(qualname)s.from_tuples([(0, 1), (1, 3), (2, 4)])
>>> intervals
%(klass)s([(0, 1], (1, 3], (2, 4]],
closed='right',
diff --git a/pandas/core/indexes/interval.py b/pandas/core/indexes/interval.py
index 2a6044fb0a08b..0210560aaa21f 100644
--- a/pandas/core/indexes/interval.py
+++ b/pandas/core/indexes/interval.py
@@ -38,6 +38,7 @@
_index_doc_kwargs.update(
dict(klass='IntervalIndex',
+ qualname="IntervalIndex",
target_klass='IntervalIndex or list of Intervals',
name=textwrap.dedent("""\
name : object, optional
@@ -282,10 +283,10 @@ def contains(self, key):
examples="""
Examples
--------
- >>> idx = pd.IntervalIndex.from_arrays([0, np.nan, 2], [1, np.nan, 3])
- >>> idx.to_tuples()
+ >>> idx = pd.IntervalIndex.from_arrays([0, np.nan, 2], [1, np.nan, 3])
+ >>> idx.to_tuples()
Index([(0.0, 1.0), (nan, nan), (2.0, 3.0)], dtype='object')
- >>> idx.to_tuples(na_tuple=False)
+ >>> idx.to_tuples(na_tuple=False)
Index([(0.0, 1.0), nan, (2.0, 3.0)], dtype='object')""",
))
def to_tuples(self, na_tuple=True):
@@ -1201,15 +1202,15 @@ def interval_range(start=None, end=None, periods=None, freq=None,
Numeric ``start`` and ``end`` is supported.
>>> pd.interval_range(start=0, end=5)
- IntervalIndex([(0, 1], (1, 2], (2, 3], (3, 4], (4, 5]]
+ IntervalIndex([(0, 1], (1, 2], (2, 3], (3, 4], (4, 5]],
closed='right', dtype='interval[int64]')
Additionally, datetime-like input is also supported.
>>> pd.interval_range(start=pd.Timestamp('2017-01-01'),
- end=pd.Timestamp('2017-01-04'))
+ ... end=pd.Timestamp('2017-01-04'))
IntervalIndex([(2017-01-01, 2017-01-02], (2017-01-02, 2017-01-03],
- (2017-01-03, 2017-01-04]]
+ (2017-01-03, 2017-01-04]],
closed='right', dtype='interval[datetime64[ns]]')
The ``freq`` parameter specifies the frequency between the left and right.
@@ -1217,23 +1218,23 @@ def interval_range(start=None, end=None, periods=None, freq=None,
numeric ``start`` and ``end``, the frequency must also be numeric.
>>> pd.interval_range(start=0, periods=4, freq=1.5)
- IntervalIndex([(0.0, 1.5], (1.5, 3.0], (3.0, 4.5], (4.5, 6.0]]
+ IntervalIndex([(0.0, 1.5], (1.5, 3.0], (3.0, 4.5], (4.5, 6.0]],
closed='right', dtype='interval[float64]')
Similarly, for datetime-like ``start`` and ``end``, the frequency must be
convertible to a DateOffset.
>>> pd.interval_range(start=pd.Timestamp('2017-01-01'),
- periods=3, freq='MS')
+ ... periods=3, freq='MS')
IntervalIndex([(2017-01-01, 2017-02-01], (2017-02-01, 2017-03-01],
- (2017-03-01, 2017-04-01]]
+ (2017-03-01, 2017-04-01]],
closed='right', dtype='interval[datetime64[ns]]')
Specify ``start``, ``end``, and ``periods``; the frequency is generated
automatically (linearly spaced).
>>> pd.interval_range(start=0, end=6, periods=4)
- IntervalIndex([(0.0, 1.5], (1.5, 3.0], (3.0, 4.5], (4.5, 6.0]]
+ IntervalIndex([(0.0, 1.5], (1.5, 3.0], (3.0, 4.5], (4.5, 6.0]],
closed='right',
dtype='interval[float64]')
@@ -1241,7 +1242,7 @@ def interval_range(start=None, end=None, periods=None, freq=None,
intervals within the ``IntervalIndex`` are closed.
>>> pd.interval_range(end=5, periods=4, closed='both')
- IntervalIndex([[1, 2], [2, 3], [3, 4], [4, 5]]
+ IntervalIndex([[1, 2], [2, 3], [3, 4], [4, 5]],
closed='both', dtype='interval[int64]')
"""
start = com.maybe_box_datetimelike(start)