From a2e58f90286043a81cf4d01e3456c80095bc7729 Mon Sep 17 00:00:00 2001
From: Santhosh18 <santhosh.balakrishnan@datakalp.com>
Date: Fri, 26 Jun 2020 17:11:01 +0530
Subject: [PATCH 1/8] Inferred dtype at the end of df.explode()

---
 pandas/core/frame.py                        | 1 +
 pandas/tests/series/methods/test_explode.py | 2 +-
 2 files changed, 2 insertions(+), 1 deletion(-)

diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index f52341ed782d8..372a989ce0ffd 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -7070,6 +7070,7 @@ def explode(
         else:
             result.index = self.index.take(result.index)
         result = result.reindex(columns=self.columns, copy=False)
+        result = result.infer_objects()
 
         return result
 
diff --git a/pandas/tests/series/methods/test_explode.py b/pandas/tests/series/methods/test_explode.py
index 4b65e042f7b02..ad2050ab2cc05 100644
--- a/pandas/tests/series/methods/test_explode.py
+++ b/pandas/tests/series/methods/test_explode.py
@@ -7,7 +7,7 @@
 
 def test_basic():
     s = pd.Series([[0, 1, 2], np.nan, [], (3, 4)], index=list("abcd"), name="foo")
-    result = s.explode()
+    result = s. explode()
     expected = pd.Series(
         [0, 1, 2, np.nan, np.nan, 3, 4], index=list("aaabcdd"), dtype=object, name="foo"
     )

From 1ead55f19ec3b16a997c1fb2d480f7dffef6b0ae Mon Sep 17 00:00:00 2001
From: Santhosh18 <santhosh.balakrishnan@datakalp.com>
Date: Fri, 26 Jun 2020 17:23:20 +0530
Subject: [PATCH 2/8] Fixed PEP issues

---
 pandas/tests/series/methods/test_explode.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/pandas/tests/series/methods/test_explode.py b/pandas/tests/series/methods/test_explode.py
index ad2050ab2cc05..5c8016f6d8b8b 100644
--- a/pandas/tests/series/methods/test_explode.py
+++ b/pandas/tests/series/methods/test_explode.py
@@ -126,3 +126,4 @@ def test_ignore_index():
     result = s.explode(ignore_index=True)
     expected = pd.Series([1, 2, 3, 4], index=[0, 1, 2, 3], dtype=object)
     tm.assert_series_equal(result, expected)
+

From 86f5f5f97d1d157d4d1386c3d23b3e6f4a2482fd Mon Sep 17 00:00:00 2001
From: Santhosh18 <santhosh.balakrishnan@datakalp.com>
Date: Fri, 26 Jun 2020 20:03:25 +0530
Subject: [PATCH 3/8] Modified test cases and added detailed explanation in
 v1.1.0.rst

---
 doc/source/whatsnew/v1.1.0.rst              | 70 +++++++++++++++++++++
 pandas/core/series.py                       |  2 +-
 pandas/tests/frame/methods/test_explode.py  | 25 ++++++--
 pandas/tests/series/methods/test_explode.py | 10 +--
 4 files changed, 96 insertions(+), 11 deletions(-)

diff --git a/doc/source/whatsnew/v1.1.0.rst b/doc/source/whatsnew/v1.1.0.rst
index 43d1244c15d8a..619419206c3b1 100644
--- a/doc/source/whatsnew/v1.1.0.rst
+++ b/doc/source/whatsnew/v1.1.0.rst
@@ -715,6 +715,76 @@ apply and applymap on ``DataFrame`` evaluates first row/column only once
 
     df.apply(func, axis=1)
 
+
+.. _whatsnew_110.api_breaking.explode_infer_dtype:
+
+Infer dtypes in explode method for Dataframe and Series
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Using :meth:`DataFrame.explode` and :meth:`Series.explode` would always return an object for the column being exploded. Now the dtype of the column would be inferred and returned accordingly. (:issue:`34923`)
+
+.. ipython:: python
+
+    s = pd.Series([1,2,3])
+    df = pd.DataFrame({'A': [s, s, s, s], 'B': 1})
+
+*Previous behavior*:
+
+.. code-block:: ipython
+
+    In [3]: df.explode("A").dtypes
+    Out[3]:
+    A    object
+    B     int64
+    dtype: object
+
+*New behavior*:
+
+.. ipython:: ipython
+
+    In [3]: df.explode("A").dtypes
+    Out[3]:
+    A    int64
+    B    int64
+    dtype: object
+
+.. _whatsnew_110.api.other:
+
+Other API changes
+^^^^^^^^^^^^^^^^^
+
+- :meth:`Series.describe` will now show distribution percentiles for ``datetime`` dtypes, statistics ``first`` and ``last``
+  will now be ``min`` and ``max`` to match with numeric dtypes in :meth:`DataFrame.describe` (:issue:`30164`)
+- Added :meth:`DataFrame.value_counts` (:issue:`5377`)
+- :meth:`Groupby.groups` now returns an abbreviated representation when called on large dataframes (:issue:`1135`)
+- ``loc`` lookups with an object-dtype :class:`Index` and an integer key will now raise ``KeyError`` instead of ``TypeError`` when key is missing (:issue:`31905`)
+- Using a :func:`pandas.api.indexers.BaseIndexer` with ``count``, ``min``, ``max``, ``median``, ``skew``,  ``cov``, ``corr`` will now return correct results for any monotonic :func:`pandas.api.indexers.BaseIndexer` descendant (:issue:`32865`)
+- Added a :func:`pandas.api.indexers.FixedForwardWindowIndexer` class to support forward-looking windows during ``rolling`` operations.
+- Added a :func:`pandas.api.indexers.NonFixedVariableWindowIndexer` class to support ``rolling`` operations with non-fixed offsets (:issue:`34994`)
+- Added :class:`pandas.errors.InvalidIndexError` (:issue:`34570`).
+- :meth:`DataFrame.swaplevels` now raises a  ``TypeError`` if the axis is not a :class:`MultiIndex`.
+  Previously an ``AttributeError`` was raised (:issue:`31126`)
+- :meth:`DataFrame.xs` now raises a  ``TypeError`` if a ``level`` keyword is supplied and the axis is not a :class:`MultiIndex`.
+  Previously an ``AttributeError`` was raised (:issue:`33610`)
+- :meth:`DataFrameGroupby.mean` and :meth:`SeriesGroupby.mean` (and similarly for :meth:`~DataFrameGroupby.median`, :meth:`~DataFrameGroupby.std` and :meth:`~DataFrameGroupby.var`)
+  now raise a  ``TypeError`` if a not-accepted keyword argument is passed into it.
+  Previously a ``UnsupportedFunctionCall`` was raised (``AssertionError`` if ``min_count`` passed into :meth:`~DataFrameGroupby.median`) (:issue:`31485`)
+- :meth:`DataFrame.at` and :meth:`Series.at` will raise a ``TypeError`` instead of a ``ValueError`` if an incompatible key is passed, and ``KeyError`` if a missing key is passed, matching the behavior of ``.loc[]`` (:issue:`31722`)
+- Passing an integer dtype other than ``int64`` to ``np.array(period_index, dtype=...)`` will now raise ``TypeError`` instead of incorrectly using ``int64`` (:issue:`32255`)
+- Passing an invalid ``fill_value`` to :meth:`Categorical.take` raises a ``ValueError`` instead of ``TypeError`` (:issue:`33660`)
+- Combining a ``Categorical`` with integer categories and which contains missing values
+  with a float dtype column in operations such as :func:`concat` or :meth:`~DataFrame.append`
+  will now result in a float column instead of an object dtyped column (:issue:`33607`)
+- :meth:`Series.to_timestamp` now raises a ``TypeError`` if the axis is not a :class:`PeriodIndex`. Previously an ``AttributeError`` was raised (:issue:`33327`)
+- :meth:`Series.to_period` now raises a ``TypeError`` if the axis is not a :class:`DatetimeIndex`. Previously an ``AttributeError`` was raised (:issue:`33327`)
+- :func: `pandas.api.dtypes.is_string_dtype` no longer incorrectly identifies categorical series as string.
+- :func:`read_excel` no longer takes ``**kwds`` arguments. This means that passing in keyword ``chunksize`` now raises a ``TypeError``
+  (previously raised a ``NotImplementedError``), while passing in keyword ``encoding`` now raises a ``TypeError`` (:issue:`34464`)
+- :func: `merge` now checks ``suffixes`` parameter type to be ``tuple`` and raises ``TypeError``, whereas before a ``list`` or ``set`` were accepted and that the ``set`` could produce unexpected results (:issue:`33740`)
+- :class:`Period` no longer accepts tuples for the ``freq`` argument (:issue:`34658`)
+- :meth:`Series.interpolate` and :meth:`DataFrame.interpolate` now raises ValueError if ``limit_direction`` is 'forward' or 'both' and ``method`` is 'backfill' or 'bfill' or ``limit_direction`` is 'backward' or 'both' and ``method`` is 'pad' or 'ffill' (:issue:`34746`)
+
+
 Increased minimum versions for dependencies
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
diff --git a/pandas/core/series.py b/pandas/core/series.py
index ef3be854bc3bb..b3e9be26038c8 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -3843,7 +3843,7 @@ def explode(self, ignore_index: bool = False) -> "Series":
         else:
             index = self.index.repeat(counts)
 
-        result = self._constructor(values, index=index, name=self.name)
+        result = self._constructor(values, index=index, name=self.name).infer_objects()
 
         return result
 
diff --git a/pandas/tests/frame/methods/test_explode.py b/pandas/tests/frame/methods/test_explode.py
index 2bbe8ac2d5b81..f34a2ef766ca6 100644
--- a/pandas/tests/frame/methods/test_explode.py
+++ b/pandas/tests/frame/methods/test_explode.py
@@ -25,7 +25,7 @@ def test_basic():
     expected = pd.DataFrame(
         {
             "A": pd.Series(
-                [0, 1, 2, np.nan, np.nan, 3, 4], index=list("aaabcdd"), dtype=object
+                [0, 1, 2, np.nan, np.nan, 3, 4], index=list("aaabcdd"), dtype=np.float64
             ),
             "B": 1,
         }
@@ -55,7 +55,7 @@ def test_multi_index_rows():
                         ("b", 2),
                     ]
                 ),
-                dtype=object,
+                dtype=np.float64,
             ),
             "B": 1,
         }
@@ -74,7 +74,7 @@ def test_multi_index_columns():
             ("A", 1): pd.Series(
                 [0, 1, 2, np.nan, np.nan, 3, 4],
                 index=pd.Index([0, 0, 0, 1, 2, 3, 3]),
-                dtype=object,
+                dtype=np.float64,
             ),
             ("A", 2): 1,
         }
@@ -93,7 +93,7 @@ def test_usecase():
     expected = pd.DataFrame(
         {
             "A": [11, 11, 11, 11, 11, 22, 22, 22],
-            "B": np.array([0, 1, 2, 3, 4, 0, 1, 2], dtype=object),
+            "B": np.array([0, 1, 2, 3, 4, 0, 1, 2], dtype=np.int64),
             "C": [10, 10, 10, 10, 10, 20, 20, 20],
         },
         columns=list("ABC"),
@@ -160,7 +160,22 @@ def test_duplicate_index(input_dict, input_index, expected_dict, expected_index)
     # GH 28005
     df = pd.DataFrame(input_dict, index=input_index)
     result = df.explode("col1")
-    expected = pd.DataFrame(expected_dict, index=expected_index, dtype=object)
+    expected = pd.DataFrame(expected_dict, index=expected_index, dtype=np.int64)
+    tm.assert_frame_equal(result, expected)
+
+
+def test_inferred_dtype():
+    # GH 34923
+    s = pd.Series([1, None, 3])
+    df = pd.DataFrame({'A': [s, s], "B": 1})
+    result = df.explode("A")
+    expected = pd.DataFrame(
+        {
+            "A": np.array([1, np.nan, 3, 1, np.nan, 3], dtype=np.float64),
+            "B": np.array([1, 1, 1, 1, 1, 1], dtype=np.int64)
+        },
+        index=[0, 0, 0, 1, 1, 1]
+    )
     tm.assert_frame_equal(result, expected)
 
 
diff --git a/pandas/tests/series/methods/test_explode.py b/pandas/tests/series/methods/test_explode.py
index 5c8016f6d8b8b..58aba1e52d722 100644
--- a/pandas/tests/series/methods/test_explode.py
+++ b/pandas/tests/series/methods/test_explode.py
@@ -7,9 +7,9 @@
 
 def test_basic():
     s = pd.Series([[0, 1, 2], np.nan, [], (3, 4)], index=list("abcd"), name="foo")
-    result = s. explode()
+    result = s.explode()
     expected = pd.Series(
-        [0, 1, 2, np.nan, np.nan, 3, 4], index=list("aaabcdd"), dtype=object, name="foo"
+        [0, 1, 2, np.nan, np.nan, 3, 4], index=list("aaabcdd"), dtype=np.float64, name="foo"
     )
     tm.assert_series_equal(result, expected)
 
@@ -54,7 +54,7 @@ def test_multi_index():
         names=["foo", "bar"],
     )
     expected = pd.Series(
-        [0, 1, 2, np.nan, np.nan, 3, 4], index=index, dtype=object, name="foo"
+        [0, 1, 2, np.nan, np.nan, 3, 4], index=index, dtype=np.float64, name="foo"
     )
     tm.assert_series_equal(result, expected)
 
@@ -116,7 +116,7 @@ def test_duplicate_index():
     # GH 28005
     s = pd.Series([[1, 2], [3, 4]], index=[0, 0])
     result = s.explode()
-    expected = pd.Series([1, 2, 3, 4], index=[0, 0, 0, 0], dtype=object)
+    expected = pd.Series([1, 2, 3, 4], index=[0, 0, 0, 0], dtype=np.int64)
     tm.assert_series_equal(result, expected)
 
 
@@ -124,6 +124,6 @@ def test_ignore_index():
     # GH 34932
     s = pd.Series([[1, 2], [3, 4]])
     result = s.explode(ignore_index=True)
-    expected = pd.Series([1, 2, 3, 4], index=[0, 1, 2, 3], dtype=object)
+    expected = pd.Series([1, 2, 3, 4], index=[0, 1, 2, 3], dtype=np.int64)
     tm.assert_series_equal(result, expected)
 

From 8b3e07b9d953392dd3fd5c01f18750463b4f3080 Mon Sep 17 00:00:00 2001
From: Santhosh18 <santhosh.balakrishnan@datakalp.com>
Date: Mon, 29 Jun 2020 18:28:09 +0530
Subject: [PATCH 4/8] Fixed Linting issues

---
 doc/source/whatsnew/v1.1.0.rst              | 2 +-
 pandas/tests/series/methods/test_explode.py | 3 ++-
 2 files changed, 3 insertions(+), 2 deletions(-)

diff --git a/doc/source/whatsnew/v1.1.0.rst b/doc/source/whatsnew/v1.1.0.rst
index 619419206c3b1..2d2cd386c9e60 100644
--- a/doc/source/whatsnew/v1.1.0.rst
+++ b/doc/source/whatsnew/v1.1.0.rst
@@ -725,7 +725,7 @@ Using :meth:`DataFrame.explode` and :meth:`Series.explode` would always return a
 
 .. ipython:: python
 
-    s = pd.Series([1,2,3])
+    s = pd.Series([1, 2, 3])
     df = pd.DataFrame({'A': [s, s, s, s], 'B': 1})
 
 *Previous behavior*:
diff --git a/pandas/tests/series/methods/test_explode.py b/pandas/tests/series/methods/test_explode.py
index 58aba1e52d722..3f6d31daa979e 100644
--- a/pandas/tests/series/methods/test_explode.py
+++ b/pandas/tests/series/methods/test_explode.py
@@ -9,7 +9,8 @@ def test_basic():
     s = pd.Series([[0, 1, 2], np.nan, [], (3, 4)], index=list("abcd"), name="foo")
     result = s.explode()
     expected = pd.Series(
-        [0, 1, 2, np.nan, np.nan, 3, 4], index=list("aaabcdd"), dtype=np.float64, name="foo"
+        [0, 1, 2, np.nan, np.nan, 3, 4], index=list("aaabcdd"),
+        dtype=np.float64, name="foo"
     )
     tm.assert_series_equal(result, expected)
 

From 2c1071c1ace6275962118e32bc0e232e7f8291f2 Mon Sep 17 00:00:00 2001
From: Santhosh18 <santhosh.balakrishnan@datakalp.com>
Date: Tue, 30 Jun 2020 12:37:51 +0530
Subject: [PATCH 5/8] Fixed PEP issues

---
 pandas/tests/series/methods/test_explode.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/pandas/tests/series/methods/test_explode.py b/pandas/tests/series/methods/test_explode.py
index 3f6d31daa979e..de2bf4c6379f8 100644
--- a/pandas/tests/series/methods/test_explode.py
+++ b/pandas/tests/series/methods/test_explode.py
@@ -127,4 +127,3 @@ def test_ignore_index():
     result = s.explode(ignore_index=True)
     expected = pd.Series([1, 2, 3, 4], index=[0, 1, 2, 3], dtype=np.int64)
     tm.assert_series_equal(result, expected)
-

From 7ba1472f1cc0ca0e6cd8392f5523ca9ccff309fb Mon Sep 17 00:00:00 2001
From: Santhosh18 <santhosh.balakrishnan@datakalp.com>
Date: Tue, 30 Jun 2020 14:11:43 +0530
Subject: [PATCH 6/8] Fixed linting issues

---
 pandas/tests/frame/methods/test_explode.py  | 6 +++---
 pandas/tests/series/methods/test_explode.py | 6 ++++--
 2 files changed, 7 insertions(+), 5 deletions(-)

diff --git a/pandas/tests/frame/methods/test_explode.py b/pandas/tests/frame/methods/test_explode.py
index f34a2ef766ca6..064f6936d6d0e 100644
--- a/pandas/tests/frame/methods/test_explode.py
+++ b/pandas/tests/frame/methods/test_explode.py
@@ -167,14 +167,14 @@ def test_duplicate_index(input_dict, input_index, expected_dict, expected_index)
 def test_inferred_dtype():
     # GH 34923
     s = pd.Series([1, None, 3])
-    df = pd.DataFrame({'A': [s, s], "B": 1})
+    df = pd.DataFrame({"A": [s, s], "B": 1})
     result = df.explode("A")
     expected = pd.DataFrame(
         {
             "A": np.array([1, np.nan, 3, 1, np.nan, 3], dtype=np.float64),
-            "B": np.array([1, 1, 1, 1, 1, 1], dtype=np.int64)
+            "B": np.array([1, 1, 1, 1, 1, 1], dtype=np.int64),
         },
-        index=[0, 0, 0, 1, 1, 1]
+        index=[0, 0, 0, 1, 1, 1],
     )
     tm.assert_frame_equal(result, expected)
 
diff --git a/pandas/tests/series/methods/test_explode.py b/pandas/tests/series/methods/test_explode.py
index de2bf4c6379f8..b720d7a23b375 100644
--- a/pandas/tests/series/methods/test_explode.py
+++ b/pandas/tests/series/methods/test_explode.py
@@ -9,8 +9,10 @@ def test_basic():
     s = pd.Series([[0, 1, 2], np.nan, [], (3, 4)], index=list("abcd"), name="foo")
     result = s.explode()
     expected = pd.Series(
-        [0, 1, 2, np.nan, np.nan, 3, 4], index=list("aaabcdd"),
-        dtype=np.float64, name="foo"
+        [0, 1, 2, np.nan, np.nan, 3, 4],
+        index=list("aaabcdd"),
+        dtype=np.float64,
+        name="foo",
     )
     tm.assert_series_equal(result, expected)
 

From 920f63bedfd482cc90e9a2ec6244651da9e525fb Mon Sep 17 00:00:00 2001
From: Santhosh18 <santhosh.balakrishnan@datakalp.com>
Date: Fri, 17 Jul 2020 17:13:35 +0530
Subject: [PATCH 7/8] Modified whasnew v1.1.0.rst

---
 doc/source/whatsnew/v1.1.0.rst | 37 ----------------------------------
 1 file changed, 37 deletions(-)

diff --git a/doc/source/whatsnew/v1.1.0.rst b/doc/source/whatsnew/v1.1.0.rst
index 2d2cd386c9e60..e56f8c9416235 100644
--- a/doc/source/whatsnew/v1.1.0.rst
+++ b/doc/source/whatsnew/v1.1.0.rst
@@ -748,43 +748,6 @@ Using :meth:`DataFrame.explode` and :meth:`Series.explode` would always return a
     B    int64
     dtype: object
 
-.. _whatsnew_110.api.other:
-
-Other API changes
-^^^^^^^^^^^^^^^^^
-
-- :meth:`Series.describe` will now show distribution percentiles for ``datetime`` dtypes, statistics ``first`` and ``last``
-  will now be ``min`` and ``max`` to match with numeric dtypes in :meth:`DataFrame.describe` (:issue:`30164`)
-- Added :meth:`DataFrame.value_counts` (:issue:`5377`)
-- :meth:`Groupby.groups` now returns an abbreviated representation when called on large dataframes (:issue:`1135`)
-- ``loc`` lookups with an object-dtype :class:`Index` and an integer key will now raise ``KeyError`` instead of ``TypeError`` when key is missing (:issue:`31905`)
-- Using a :func:`pandas.api.indexers.BaseIndexer` with ``count``, ``min``, ``max``, ``median``, ``skew``,  ``cov``, ``corr`` will now return correct results for any monotonic :func:`pandas.api.indexers.BaseIndexer` descendant (:issue:`32865`)
-- Added a :func:`pandas.api.indexers.FixedForwardWindowIndexer` class to support forward-looking windows during ``rolling`` operations.
-- Added a :func:`pandas.api.indexers.NonFixedVariableWindowIndexer` class to support ``rolling`` operations with non-fixed offsets (:issue:`34994`)
-- Added :class:`pandas.errors.InvalidIndexError` (:issue:`34570`).
-- :meth:`DataFrame.swaplevels` now raises a  ``TypeError`` if the axis is not a :class:`MultiIndex`.
-  Previously an ``AttributeError`` was raised (:issue:`31126`)
-- :meth:`DataFrame.xs` now raises a  ``TypeError`` if a ``level`` keyword is supplied and the axis is not a :class:`MultiIndex`.
-  Previously an ``AttributeError`` was raised (:issue:`33610`)
-- :meth:`DataFrameGroupby.mean` and :meth:`SeriesGroupby.mean` (and similarly for :meth:`~DataFrameGroupby.median`, :meth:`~DataFrameGroupby.std` and :meth:`~DataFrameGroupby.var`)
-  now raise a  ``TypeError`` if a not-accepted keyword argument is passed into it.
-  Previously a ``UnsupportedFunctionCall`` was raised (``AssertionError`` if ``min_count`` passed into :meth:`~DataFrameGroupby.median`) (:issue:`31485`)
-- :meth:`DataFrame.at` and :meth:`Series.at` will raise a ``TypeError`` instead of a ``ValueError`` if an incompatible key is passed, and ``KeyError`` if a missing key is passed, matching the behavior of ``.loc[]`` (:issue:`31722`)
-- Passing an integer dtype other than ``int64`` to ``np.array(period_index, dtype=...)`` will now raise ``TypeError`` instead of incorrectly using ``int64`` (:issue:`32255`)
-- Passing an invalid ``fill_value`` to :meth:`Categorical.take` raises a ``ValueError`` instead of ``TypeError`` (:issue:`33660`)
-- Combining a ``Categorical`` with integer categories and which contains missing values
-  with a float dtype column in operations such as :func:`concat` or :meth:`~DataFrame.append`
-  will now result in a float column instead of an object dtyped column (:issue:`33607`)
-- :meth:`Series.to_timestamp` now raises a ``TypeError`` if the axis is not a :class:`PeriodIndex`. Previously an ``AttributeError`` was raised (:issue:`33327`)
-- :meth:`Series.to_period` now raises a ``TypeError`` if the axis is not a :class:`DatetimeIndex`. Previously an ``AttributeError`` was raised (:issue:`33327`)
-- :func: `pandas.api.dtypes.is_string_dtype` no longer incorrectly identifies categorical series as string.
-- :func:`read_excel` no longer takes ``**kwds`` arguments. This means that passing in keyword ``chunksize`` now raises a ``TypeError``
-  (previously raised a ``NotImplementedError``), while passing in keyword ``encoding`` now raises a ``TypeError`` (:issue:`34464`)
-- :func: `merge` now checks ``suffixes`` parameter type to be ``tuple`` and raises ``TypeError``, whereas before a ``list`` or ``set`` were accepted and that the ``set`` could produce unexpected results (:issue:`33740`)
-- :class:`Period` no longer accepts tuples for the ``freq`` argument (:issue:`34658`)
-- :meth:`Series.interpolate` and :meth:`DataFrame.interpolate` now raises ValueError if ``limit_direction`` is 'forward' or 'both' and ``method`` is 'backfill' or 'bfill' or ``limit_direction`` is 'backward' or 'both' and ``method`` is 'pad' or 'ffill' (:issue:`34746`)
-
-
 Increased minimum versions for dependencies
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 

From f6144512d1385a29784e1f235132e1951268a31d Mon Sep 17 00:00:00 2001
From: Santhosh18 <santhosh.balakrishnan@datakalp.com>
Date: Fri, 17 Jul 2020 18:39:34 +0530
Subject: [PATCH 8/8] Modified whatsnew v1.1.0.rst

---
 doc/source/whatsnew/v1.1.0.rst | 9 +++------
 1 file changed, 3 insertions(+), 6 deletions(-)

diff --git a/doc/source/whatsnew/v1.1.0.rst b/doc/source/whatsnew/v1.1.0.rst
index e56f8c9416235..d5069c71d332b 100644
--- a/doc/source/whatsnew/v1.1.0.rst
+++ b/doc/source/whatsnew/v1.1.0.rst
@@ -740,13 +740,10 @@ Using :meth:`DataFrame.explode` and :meth:`Series.explode` would always return a
 
 *New behavior*:
 
-.. ipython:: ipython
+.. ipython:: python
+
+    df.explode("A").dtypes
 
-    In [3]: df.explode("A").dtypes
-    Out[3]:
-    A    int64
-    B    int64
-    dtype: object
 
 Increased minimum versions for dependencies
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^