From cb16c96cb0732327d8c36783ab2142661cd32cd4 Mon Sep 17 00:00:00 2001
From: Doug Branton <brantd@uw.edu>
Date: Wed, 10 Apr 2024 08:39:23 -0700
Subject: [PATCH 1/9] WIP: dropna

---
 src/nested_pandas/nestedframe/core.py | 134 ++++++++++++++++++++++++++
 1 file changed, 134 insertions(+)

diff --git a/src/nested_pandas/nestedframe/core.py b/src/nested_pandas/nestedframe/core.py
index 4970930..638552f 100644
--- a/src/nested_pandas/nestedframe/core.py
+++ b/src/nested_pandas/nestedframe/core.py
@@ -1,7 +1,10 @@
 # typing.Self and "|" union syntax don't exist in Python 3.9
 from __future__ import annotations
 
+import numpy as np
 import pandas as pd
+from pandas._libs import lib
+from pandas._typing import AnyAll, Axis, IndexLabel
 
 from nested_pandas.series import packer
 from nested_pandas.series.dtype import NestedDtype
@@ -154,3 +157,134 @@ def query(self, expr) -> Self:  # type: ignore[name-defined] # noqa: F821
                 # TODO: does not work with queries that empty the dataframe
                 result[expr] = result[expr].nest.query_flat(exprs_to_use[expr])
         return result
+
+    def dropna(
+        self,
+        *,
+        axis: Axis = 0,
+        how: AnyAll | lib.NoDefault = lib.no_default,
+        thresh: int | lib.NoDefault = lib.no_default,
+        on_nested: bool = False,
+        subset: IndexLabel | None = None,
+        inplace: bool = False,
+        ignore_index: bool = False,
+    ) -> NestedFrame | None:
+        """
+        Remove missing values.
+
+        Parameters
+        ----------
+        axis : {0 or 'index', 1 or 'columns'}, default 0
+            Determine if rows or columns which contain missing values are
+            removed.
+
+            * 0, or 'index' : Drop rows which contain missing values.
+            * 1, or 'columns' : Drop columns which contain missing value.
+
+            Only a single axis is allowed.
+
+        how : {'any', 'all'}, default 'any'
+            Determine if row or column is removed from DataFrame, when we have
+            at least one NA or all NA.
+
+            * 'any' : If any NA values are present, drop that row or column.
+            * 'all' : If all values are NA, drop that row or column.
+        thresh : int, optional
+            Require that many non-NA values. Cannot be combined with how.
+        on_nested : str or bool, optional
+            If not False, applies the call to the nested dataframe in the
+            column with label equal to the provided string. If specified,
+            the nested dataframe should align with any columns given in
+            `subset`.
+        subset : column label or sequence of labels, optional
+            Labels along other axis to consider, e.g. if you are dropping rows
+            these would be a list of columns to include.
+
+            Access nested columns using `nested_df.nested_col` (where
+            `nested_df` refers to a particular nested dataframe and
+            `nested_col` is a column of that nested dataframe).
+        inplace : bool, default False
+            Whether to modify the DataFrame rather than creating a new one.
+        ignore_index : bool, default ``False``
+            If ``True``, the resulting axis will be labeled 0, 1, …, n - 1.
+
+            .. versionadded:: 2.0.0
+
+        Returns
+        -------
+        DataFrame or None
+            DataFrame with NA entries dropped from it or None if ``inplace=True``.
+
+        Notes
+        -----
+        Operations that target a particular nested structure return a dataframe
+        with rows of that particular nested structure affected.
+        """
+
+        # determine target dataframe
+
+        # first check the subset kwarg input
+        subset_target = []
+        if subset:
+            if type(subset) is str:
+                subset = [subset]
+            for col in subset:
+                col = col.split(".")[0] if "." in col else col
+                if col in self.nested_columns:
+                    subset_target.append(col)
+                elif col in self.columns:
+                    subset_target.append("base")
+
+            # Check for 1 target
+            subset_target = np.unique(subset_target)
+            if len(subset_target) > 1:  # prohibit multi-target operations
+                raise ValueError(
+                    f"Targeted multiple nested structures ({target}), write one command per target dataframe"
+                )
+            elif len(subset_target) == 0:
+                raise ValueError(
+                    "Provided base columns or nested layer did not match any found in the nestedframe"
+                )
+            subset_target = subset_target[0]
+
+        # Next check the on_nested kwarg input
+        # import pdb;pdb.set_trace()
+        if on_nested:
+            if on_nested not in self.nested_columns:
+                raise ValueError("Provided nested layer not found in nested dataframes")
+
+        # Resolve target layer
+        target = "base"
+        if on_nested and subset_target:
+            if on_nested != subset_target:
+                raise ValueError(
+                    f"Provided on_nested={on_nested}, but subset columns are from {subset_target}. Make sure these are aligned or just use subset."
+                )
+            else:
+                target = subset_target
+        elif on_nested:
+            target = on_nested
+        elif subset_target:
+            target = subset_target
+
+        if target == "base":
+            return super().dropna(
+                axis=axis, how=how, thresh=thresh, subset=subset, inplace=inplace, ignore_index=ignore_index
+            )
+        else:
+            if subset is not None:
+                subset = [col.split(".")[-1] for col in subset]
+            # import pdb;pdb.set_trace()
+            self[target] = packer.pack_flat(
+                self[target]
+                .nest.to_flat()
+                .dropna(
+                    axis=axis,
+                    how=how,
+                    thresh=thresh,
+                    subset=subset,
+                    inplace=inplace,
+                    ignore_index=ignore_index,
+                )
+            )
+            return self

From 8d902f1696116439cad61edc44945a94dadc2698 Mon Sep 17 00:00:00 2001
From: Doug Branton <brantd@uw.edu>
Date: Wed, 10 Apr 2024 13:29:39 -0700
Subject: [PATCH 2/9] add initial tests; formatting

---
 src/nested_pandas/nestedframe/core.py         | 17 +++++------
 .../nestedframe/test_nestedframe.py           | 29 +++++++++++++++++++
 2 files changed, 36 insertions(+), 10 deletions(-)

diff --git a/src/nested_pandas/nestedframe/core.py b/src/nested_pandas/nestedframe/core.py
index 638552f..4667be0 100644
--- a/src/nested_pandas/nestedframe/core.py
+++ b/src/nested_pandas/nestedframe/core.py
@@ -226,7 +226,7 @@ def dropna(
         # first check the subset kwarg input
         subset_target = []
         if subset:
-            if type(subset) is str:
+            if isinstance(subset, str):
                 subset = [subset]
             for col in subset:
                 col = col.split(".")[0] if "." in col else col
@@ -239,7 +239,7 @@ def dropna(
             subset_target = np.unique(subset_target)
             if len(subset_target) > 1:  # prohibit multi-target operations
                 raise ValueError(
-                    f"Targeted multiple nested structures ({target}), write one command per target dataframe"
+                    f"Targeted multiple nested structures ({subset_target}), write one command per target dataframe"  # noqa
                 )
             elif len(subset_target) == 0:
                 raise ValueError(
@@ -248,24 +248,22 @@ def dropna(
             subset_target = subset_target[0]
 
         # Next check the on_nested kwarg input
-        # import pdb;pdb.set_trace()
-        if on_nested:
-            if on_nested not in self.nested_columns:
-                raise ValueError("Provided nested layer not found in nested dataframes")
+        if on_nested not in self.nested_columns:
+            raise ValueError("Provided nested layer not found in nested dataframes")
 
         # Resolve target layer
         target = "base"
         if on_nested and subset_target:
             if on_nested != subset_target:
                 raise ValueError(
-                    f"Provided on_nested={on_nested}, but subset columns are from {subset_target}. Make sure these are aligned or just use subset."
+                    f"Provided on_nested={on_nested}, but subset columns are from {subset_target}. Make sure these are aligned or just use subset."  # noqa
                 )
             else:
                 target = subset_target
         elif on_nested:
-            target = on_nested
+            target = str(on_nested)
         elif subset_target:
-            target = subset_target
+            target = str(subset_target)
 
         if target == "base":
             return super().dropna(
@@ -274,7 +272,6 @@ def dropna(
         else:
             if subset is not None:
                 subset = [col.split(".")[-1] for col in subset]
-            # import pdb;pdb.set_trace()
             self[target] = packer.pack_flat(
                 self[target]
                 .nest.to_flat()
diff --git a/tests/nested_pandas/nestedframe/test_nestedframe.py b/tests/nested_pandas/nestedframe/test_nestedframe.py
index 15f9d9f..8e3f1d7 100644
--- a/tests/nested_pandas/nestedframe/test_nestedframe.py
+++ b/tests/nested_pandas/nestedframe/test_nestedframe.py
@@ -1,3 +1,4 @@
+import numpy as np
 import pandas as pd
 import pytest
 from nested_pandas import NestedFrame
@@ -101,3 +102,31 @@ def test_query():
 
     nest_queried = base.query("(nested.c > 1) and (nested.d>2)")
     assert len(nest_queried.nested.nest.to_flat()) == 4
+
+
+def test_dropna():
+    """Test that dropna works on all layers"""
+
+    base = NestedFrame(data={"a": [1, 2, 3], "b": [2, np.NaN, 6]}, index=[0, 1, 2])
+
+    nested = pd.DataFrame(
+        data={"c": [0, 2, 4, 1, np.NaN, 3, 1, 4, 1], "d": [5, 4, 7, 5, 3, 1, 9, 3, 4]},
+        index=[0, 0, 0, 1, 1, 1, 2, 2, 2],
+    )
+
+    base = base.add_nested(nested, "nested")
+
+    # Test basic functionality
+    dn_base = base.dropna(subset=["b"])
+    assert len(dn_base) == 2
+    assert len(dn_base["nested"].nest.to_flat() == 6)
+
+    # Test on_nested kwarg
+    dn_on_nested = base.dropna(on_nested="nested")
+    assert len(dn_on_nested) == 3
+    assert len(dn_on_nested["nested"].nest.to_flat() == 8)
+
+    # Test hierarchical column subset
+    dn_hierarchical = base.dropna(subset="nested.c")
+    assert len(dn_hierarchical) == 3
+    assert len(dn_hierarchical["nested"].nest.to_flat() == 8)

From 26575386248b5e36eeae066e874c294778cc0dd3 Mon Sep 17 00:00:00 2001
From: Doug Branton <brantd@uw.edu>
Date: Wed, 10 Apr 2024 13:57:15 -0700
Subject: [PATCH 3/9] full test suite

---
 src/nested_pandas/nestedframe/core.py         |  5 +++-
 .../nestedframe/test_nestedframe.py           | 29 +++++++++++++++++++
 2 files changed, 33 insertions(+), 1 deletion(-)

diff --git a/src/nested_pandas/nestedframe/core.py b/src/nested_pandas/nestedframe/core.py
index 4667be0..7371114 100644
--- a/src/nested_pandas/nestedframe/core.py
+++ b/src/nested_pandas/nestedframe/core.py
@@ -228,6 +228,7 @@ def dropna(
         if subset:
             if isinstance(subset, str):
                 subset = [subset]
+
             for col in subset:
                 col = col.split(".")[0] if "." in col else col
                 if col in self.nested_columns:
@@ -235,6 +236,8 @@ def dropna(
                 elif col in self.columns:
                     subset_target.append("base")
 
+            # import pdb;pdb.set_trace()
+
             # Check for 1 target
             subset_target = np.unique(subset_target)
             if len(subset_target) > 1:  # prohibit multi-target operations
@@ -248,7 +251,7 @@ def dropna(
             subset_target = subset_target[0]
 
         # Next check the on_nested kwarg input
-        if on_nested not in self.nested_columns:
+        if on_nested and on_nested not in self.nested_columns:
             raise ValueError("Provided nested layer not found in nested dataframes")
 
         # Resolve target layer
diff --git a/tests/nested_pandas/nestedframe/test_nestedframe.py b/tests/nested_pandas/nestedframe/test_nestedframe.py
index 8e3f1d7..d8f34c9 100644
--- a/tests/nested_pandas/nestedframe/test_nestedframe.py
+++ b/tests/nested_pandas/nestedframe/test_nestedframe.py
@@ -130,3 +130,32 @@ def test_dropna():
     dn_hierarchical = base.dropna(subset="nested.c")
     assert len(dn_hierarchical) == 3
     assert len(dn_hierarchical["nested"].nest.to_flat() == 8)
+
+
+def test_dropna_errors():
+    """Test that the various dropna exceptions trigger"""
+
+    base = NestedFrame(data={"a": [1, 2, 3], "b": [2, np.NaN, 6]}, index=[0, 1, 2])
+
+    nested = pd.DataFrame(
+        data={"c": [0, 2, 4, 1, np.NaN, 3, 1, 4, 1], "d": [5, 4, 7, 5, 3, 1, 9, 3, 4]},
+        index=[0, 0, 0, 1, 1, 1, 2, 2, 2],
+    )
+
+    base = base.add_nested(nested, "nested")
+
+    # Test multi-target
+    with pytest.raises(ValueError):
+        base.dropna(subset=["b", "nested.c"])
+
+    # Test no-target
+    with pytest.raises(ValueError):
+        base.dropna(subset=["not_nested.c"])
+
+    # Test bad on-nested value
+    with pytest.raises(ValueError):
+        base.dropna(on_nested="not_nested")
+
+    # Test on-nested + subset disagreement
+    with pytest.raises(ValueError):
+        base.dropna(on_nested="nested", subset=["b"])

From e5458b17fcafc7614bc2103bb663587aaa3b06d3 Mon Sep 17 00:00:00 2001
From: Doug Branton <brantd@uw.edu>
Date: Wed, 10 Apr 2024 14:07:43 -0700
Subject: [PATCH 4/9] cover on_nested+subset case

---
 tests/nested_pandas/nestedframe/test_nestedframe.py | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/tests/nested_pandas/nestedframe/test_nestedframe.py b/tests/nested_pandas/nestedframe/test_nestedframe.py
index d8f34c9..b30015a 100644
--- a/tests/nested_pandas/nestedframe/test_nestedframe.py
+++ b/tests/nested_pandas/nestedframe/test_nestedframe.py
@@ -131,6 +131,11 @@ def test_dropna():
     assert len(dn_hierarchical) == 3
     assert len(dn_hierarchical["nested"].nest.to_flat() == 8)
 
+    # Test hierarchical column subset and on_nested
+    dn_hierarchical = base.dropna(on_nested="nested", subset="nested.c")
+    assert len(dn_hierarchical) == 3
+    assert len(dn_hierarchical["nested"].nest.to_flat() == 8)
+
 
 def test_dropna_errors():
     """Test that the various dropna exceptions trigger"""

From cc25440f28249ce932ff00f68aeadc65a24de6f7 Mon Sep 17 00:00:00 2001
From: Doug Branton <brantd@uw.edu>
Date: Thu, 11 Apr 2024 09:11:32 -0700
Subject: [PATCH 5/9] Update src/nested_pandas/nestedframe/core.py

Co-authored-by: Konstantin Malanchev <hombit@gmail.com>
---
 src/nested_pandas/nestedframe/core.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/nested_pandas/nestedframe/core.py b/src/nested_pandas/nestedframe/core.py
index 7371114..5e16427 100644
--- a/src/nested_pandas/nestedframe/core.py
+++ b/src/nested_pandas/nestedframe/core.py
@@ -230,7 +230,7 @@ def dropna(
                 subset = [subset]
 
             for col in subset:
-                col = col.split(".")[0] if "." in col else col
+                col = col.split(".")[0]
                 if col in self.nested_columns:
                     subset_target.append(col)
                 elif col in self.columns:

From 879d6caf173a17de65e73aece71b05dde545e11b Mon Sep 17 00:00:00 2001
From: Doug Branton <brantd@uw.edu>
Date: Thu, 11 Apr 2024 09:11:39 -0700
Subject: [PATCH 6/9] Update src/nested_pandas/nestedframe/core.py

Co-authored-by: Konstantin Malanchev <hombit@gmail.com>
---
 src/nested_pandas/nestedframe/core.py | 2 --
 1 file changed, 2 deletions(-)

diff --git a/src/nested_pandas/nestedframe/core.py b/src/nested_pandas/nestedframe/core.py
index 5e16427..731e569 100644
--- a/src/nested_pandas/nestedframe/core.py
+++ b/src/nested_pandas/nestedframe/core.py
@@ -236,8 +236,6 @@ def dropna(
                 elif col in self.columns:
                     subset_target.append("base")
 
-            # import pdb;pdb.set_trace()
-
             # Check for 1 target
             subset_target = np.unique(subset_target)
             if len(subset_target) > 1:  # prohibit multi-target operations

From a014a01bd7b827f9589f1f7f60e979b45acccb9e Mon Sep 17 00:00:00 2001
From: Doug Branton <brantd@uw.edu>
Date: Thu, 11 Apr 2024 10:37:01 -0700
Subject: [PATCH 7/9] address review comments; add with failing inplace test

---
 src/nested_pandas/nestedframe/core.py         | 115 +++++++++++-------
 .../nestedframe/test_nestedframe.py           |  29 +++++
 2 files changed, 97 insertions(+), 47 deletions(-)

diff --git a/src/nested_pandas/nestedframe/core.py b/src/nested_pandas/nestedframe/core.py
index 731e569..eeebd9c 100644
--- a/src/nested_pandas/nestedframe/core.py
+++ b/src/nested_pandas/nestedframe/core.py
@@ -158,6 +158,50 @@ def query(self, expr) -> Self:  # type: ignore[name-defined] # noqa: F821
                 result[expr] = result[expr].nest.query_flat(exprs_to_use[expr])
         return result
 
+    def _resolve_dropna_target(self, on_nested, subset):
+        """resolves the target layer for a given set of dropna kwargs"""
+        # first check the subset kwarg input
+        subset_target = []
+        if subset:
+            if isinstance(subset, str):
+                subset = [subset]
+
+            for col in subset:
+                col = col.split(".")[0]
+                if col in self.nested_columns:
+                    subset_target.append(col)
+                elif col in self.columns:
+                    subset_target.append("base")
+                else:
+                    raise ValueError(f"Column name {col} not found in any base or nested columns")
+
+            # Check for 1 target
+            subset_target = np.unique(subset_target)
+            if len(subset_target) > 1:  # prohibit multi-target operations
+                raise ValueError(
+                    f"Targeted multiple nested structures ({subset_target}), write one command per target dataframe"  # noqa
+                )
+            subset_target = str(subset_target[0])
+
+        # Next check the on_nested kwarg input
+        if on_nested and on_nested not in self.nested_columns:
+            raise ValueError("Provided nested layer not found in nested dataframes")
+
+        # Resolve target layer
+        target = "base"
+        if on_nested and subset_target:
+            if on_nested != subset_target:
+                raise ValueError(
+                    f"Provided on_nested={on_nested}, but subset columns are from {subset_target}. Make sure these are aligned or just use subset."  # noqa
+                )
+            else:
+                target = subset_target
+        elif on_nested:
+            target = str(on_nested)
+        elif subset_target:
+            target = str(subset_target)
+        return target, subset
+
     def dropna(
         self,
         *,
@@ -170,7 +214,7 @@ def dropna(
         ignore_index: bool = False,
     ) -> NestedFrame | None:
         """
-        Remove missing values.
+        Remove missing values for one layer of the NestedFrame.
 
         Parameters
         ----------
@@ -219,60 +263,22 @@ def dropna(
         -----
         Operations that target a particular nested structure return a dataframe
         with rows of that particular nested structure affected.
+
+        Values for `on_nested` and `subset` should be consistent in pointing
+        to a single layer, multi-layer operations are not supported at this
+        time.
         """
 
         # determine target dataframe
-
-        # first check the subset kwarg input
-        subset_target = []
-        if subset:
-            if isinstance(subset, str):
-                subset = [subset]
-
-            for col in subset:
-                col = col.split(".")[0]
-                if col in self.nested_columns:
-                    subset_target.append(col)
-                elif col in self.columns:
-                    subset_target.append("base")
-
-            # Check for 1 target
-            subset_target = np.unique(subset_target)
-            if len(subset_target) > 1:  # prohibit multi-target operations
-                raise ValueError(
-                    f"Targeted multiple nested structures ({subset_target}), write one command per target dataframe"  # noqa
-                )
-            elif len(subset_target) == 0:
-                raise ValueError(
-                    "Provided base columns or nested layer did not match any found in the nestedframe"
-                )
-            subset_target = subset_target[0]
-
-        # Next check the on_nested kwarg input
-        if on_nested and on_nested not in self.nested_columns:
-            raise ValueError("Provided nested layer not found in nested dataframes")
-
-        # Resolve target layer
-        target = "base"
-        if on_nested and subset_target:
-            if on_nested != subset_target:
-                raise ValueError(
-                    f"Provided on_nested={on_nested}, but subset columns are from {subset_target}. Make sure these are aligned or just use subset."  # noqa
-                )
-            else:
-                target = subset_target
-        elif on_nested:
-            target = str(on_nested)
-        elif subset_target:
-            target = str(subset_target)
+        target, subset = self._resolve_dropna_target(on_nested, subset)
 
         if target == "base":
             return super().dropna(
                 axis=axis, how=how, thresh=thresh, subset=subset, inplace=inplace, ignore_index=ignore_index
             )
-        else:
-            if subset is not None:
-                subset = [col.split(".")[-1] for col in subset]
+        if subset is not None:
+            subset = [col.split(".")[-1] for col in subset]
+        if inplace:
             self[target] = packer.pack_flat(
                 self[target]
                 .nest.to_flat()
@@ -286,3 +292,18 @@ def dropna(
                 )
             )
             return self
+        new_df = self.copy()
+        new_df[target] = packer.pack_flat(
+            new_df[target]
+            .nest.to_flat()
+            .copy()
+            .dropna(
+                axis=axis,
+                how=how,
+                thresh=thresh,
+                subset=subset,
+                inplace=inplace,
+                ignore_index=ignore_index,
+            )
+        )
+        return new_df
diff --git a/tests/nested_pandas/nestedframe/test_nestedframe.py b/tests/nested_pandas/nestedframe/test_nestedframe.py
index b30015a..544282a 100644
--- a/tests/nested_pandas/nestedframe/test_nestedframe.py
+++ b/tests/nested_pandas/nestedframe/test_nestedframe.py
@@ -137,6 +137,35 @@ def test_dropna():
     assert len(dn_hierarchical["nested"].nest.to_flat() == 8)
 
 
+def test_dropna_inplace():
+    """Test in-place behavior of dropna"""
+
+    base = NestedFrame(data={"a": [1, 2, 3], "b": [2, np.NaN, 6]}, index=[0, 1, 2])
+
+    nested = pd.DataFrame(
+        data={"c": [0, 2, 4, 1, np.NaN, 3, 1, 4, 1], "d": [5, 4, 7, 5, 3, 1, 9, 3, 4]},
+        index=[0, 0, 0, 1, 1, 1, 2, 2, 2],
+    )
+
+    base = base.add_nested(nested, "nested")
+
+    # Test inplace=False with base layer
+    dn_base = base.dropna(subset=["b"], inplace=False)
+    assert not dn_base.equals(base)
+
+    # Test inplace=True with base layer
+    base.dropna(subset=["b"], inplace=True)
+    assert dn_base.equals(base)
+
+    # Test inplace=False with nested layer
+    dn_base = base.dropna(on_nested="nested", inplace=False)
+    assert not dn_base.nested.nest.to_flat().equals(base.nested.nest.to_flat())
+
+    # Test inplace=True with nested layer
+    base.dropna(on_nested="nested", inplace=True)
+    assert dn_base.equals(base)
+
+
 def test_dropna_errors():
     """Test that the various dropna exceptions trigger"""
 

From 2bda706accd624af9f4f3e13ff3b2d32834be830 Mon Sep 17 00:00:00 2001
From: Doug Branton <brantd@uw.edu>
Date: Thu, 11 Apr 2024 12:52:20 -0700
Subject: [PATCH 8/9] fix inplace behavior

---
 src/nested_pandas/nestedframe/core.py         | 27 +++++++++----------
 .../nestedframe/test_nestedframe.py           | 17 ++++++++++--
 2 files changed, 28 insertions(+), 16 deletions(-)

diff --git a/src/nested_pandas/nestedframe/core.py b/src/nested_pandas/nestedframe/core.py
index eeebd9c..604a350 100644
--- a/src/nested_pandas/nestedframe/core.py
+++ b/src/nested_pandas/nestedframe/core.py
@@ -5,6 +5,7 @@
 import pandas as pd
 from pandas._libs import lib
 from pandas._typing import AnyAll, Axis, IndexLabel
+from pandas.api.extensions import no_default
 
 from nested_pandas.series import packer
 from nested_pandas.series.dtype import NestedDtype
@@ -206,8 +207,8 @@ def dropna(
         self,
         *,
         axis: Axis = 0,
-        how: AnyAll | lib.NoDefault = lib.no_default,
-        thresh: int | lib.NoDefault = lib.no_default,
+        how: AnyAll | lib.NoDefault = no_default,
+        thresh: int | lib.NoDefault = no_default,
         on_nested: bool = False,
         subset: IndexLabel | None = None,
         inplace: bool = False,
@@ -279,24 +280,22 @@ def dropna(
         if subset is not None:
             subset = [col.split(".")[-1] for col in subset]
         if inplace:
-            self[target] = packer.pack_flat(
-                self[target]
-                .nest.to_flat()
-                .dropna(
-                    axis=axis,
-                    how=how,
-                    thresh=thresh,
-                    subset=subset,
-                    inplace=inplace,
-                    ignore_index=ignore_index,
-                )
+            target_flat = self[target].nest.to_flat()
+            target_flat.dropna(
+                axis=axis,
+                how=how,
+                thresh=thresh,
+                subset=subset,
+                inplace=inplace,
+                ignore_index=ignore_index,
             )
+            self[target] = packer.pack_flat(target_flat)
             return self
+        # Or if not inplace
         new_df = self.copy()
         new_df[target] = packer.pack_flat(
             new_df[target]
             .nest.to_flat()
-            .copy()
             .dropna(
                 axis=axis,
                 how=how,
diff --git a/tests/nested_pandas/nestedframe/test_nestedframe.py b/tests/nested_pandas/nestedframe/test_nestedframe.py
index 544282a..36afdad 100644
--- a/tests/nested_pandas/nestedframe/test_nestedframe.py
+++ b/tests/nested_pandas/nestedframe/test_nestedframe.py
@@ -137,10 +137,10 @@ def test_dropna():
     assert len(dn_hierarchical["nested"].nest.to_flat() == 8)
 
 
-def test_dropna_inplace():
+def test_dropna_inplace_base():
     """Test in-place behavior of dropna"""
 
-    base = NestedFrame(data={"a": [1, 2, 3], "b": [2, np.NaN, 6]}, index=[0, 1, 2])
+    base = NestedFrame(data={"a": [1, 2, 3], "b": [np.NaN, 4, 6]}, index=[0, 1, 2])
 
     nested = pd.DataFrame(
         data={"c": [0, 2, 4, 1, np.NaN, 3, 1, 4, 1], "d": [5, 4, 7, 5, 3, 1, 9, 3, 4]},
@@ -157,6 +157,19 @@ def test_dropna_inplace():
     base.dropna(subset=["b"], inplace=True)
     assert dn_base.equals(base)
 
+
+def test_dropna_inplace_nested():
+    """Test in-place behavior of dropna"""
+
+    base = NestedFrame(data={"a": [1, 2, 3], "b": [np.NaN, 4, 6]}, index=[0, 1, 2])
+
+    nested = pd.DataFrame(
+        data={"c": [0, 2, 4, 1, np.NaN, 3, 1, 4, 1], "d": [5, 4, 7, 5, 3, 1, 9, 3, 4]},
+        index=[0, 0, 0, 1, 1, 1, 2, 2, 2],
+    )
+
+    base = base.add_nested(nested, "nested")
+
     # Test inplace=False with nested layer
     dn_base = base.dropna(on_nested="nested", inplace=False)
     assert not dn_base.nested.nest.to_flat().equals(base.nested.nest.to_flat())

From b63a49ca406b240b6f616c41838ce5a4f0df5264 Mon Sep 17 00:00:00 2001
From: Doug Branton <brantd@uw.edu>
Date: Thu, 11 Apr 2024 12:56:26 -0700
Subject: [PATCH 9/9] use properties once

---
 src/nested_pandas/nestedframe/core.py | 10 +++++++---
 1 file changed, 7 insertions(+), 3 deletions(-)

diff --git a/src/nested_pandas/nestedframe/core.py b/src/nested_pandas/nestedframe/core.py
index 604a350..6ebef11 100644
--- a/src/nested_pandas/nestedframe/core.py
+++ b/src/nested_pandas/nestedframe/core.py
@@ -161,6 +161,10 @@ def query(self, expr) -> Self:  # type: ignore[name-defined] # noqa: F821
 
     def _resolve_dropna_target(self, on_nested, subset):
         """resolves the target layer for a given set of dropna kwargs"""
+
+        nested_cols = self.nested_columns
+        columns = self.columns
+
         # first check the subset kwarg input
         subset_target = []
         if subset:
@@ -169,9 +173,9 @@ def _resolve_dropna_target(self, on_nested, subset):
 
             for col in subset:
                 col = col.split(".")[0]
-                if col in self.nested_columns:
+                if col in nested_cols:
                     subset_target.append(col)
-                elif col in self.columns:
+                elif col in columns:
                     subset_target.append("base")
                 else:
                     raise ValueError(f"Column name {col} not found in any base or nested columns")
@@ -185,7 +189,7 @@ def _resolve_dropna_target(self, on_nested, subset):
             subset_target = str(subset_target[0])
 
         # Next check the on_nested kwarg input
-        if on_nested and on_nested not in self.nested_columns:
+        if on_nested and on_nested not in nested_cols:
             raise ValueError("Provided nested layer not found in nested dataframes")
 
         # Resolve target layer