From 4596247a06d0c3615c6b5ba64442a84dbfa33f7f Mon Sep 17 00:00:00 2001
From: Aaron Tacke <tacke@in.tum.de>
Date: Sat, 7 Jun 2025 15:03:20 +0200
Subject: [PATCH 1/4] remove pandas from tabulardelta_dataclasses

---
 tabulardelta/comparators/pandas_comparator.py |  2 +-
 .../comparators/sqlcompyre_comparator.py      | 19 +++--
 .../comparators/tabulardelta_dataclasses.py   | 70 +++++++++----------
 tests/test_comparators.py                     | 46 ++++++------
 tests/test_formatters.py                      | 16 +++--
 5 files changed, 81 insertions(+), 72 deletions(-)

diff --git a/tabulardelta/comparators/pandas_comparator.py b/tabulardelta/comparators/pandas_comparator.py
index 72ee973..c26f0cd 100644
--- a/tabulardelta/comparators/pandas_comparator.py
+++ b/tabulardelta/comparators/pandas_comparator.py
@@ -154,7 +154,7 @@ def _value_change(
     diff.rename(columns={col + suffixes[1]: col}, inplace=True)
     diff["_count"] = 1
     combined = col, old_dt[col], col, new_dt[col], False
-    return ColumnPair.from_str(*combined, incomparable, diff)
+    return ColumnPair.from_str(*combined, incomparable, diff.to_dict("records"))
 
 
 def compare_pandas(
diff --git a/tabulardelta/comparators/sqlcompyre_comparator.py b/tabulardelta/comparators/sqlcompyre_comparator.py
index d53e7ab..48dfc7b 100644
--- a/tabulardelta/comparators/sqlcompyre_comparator.py
+++ b/tabulardelta/comparators/sqlcompyre_comparator.py
@@ -96,12 +96,16 @@ def table_comparison(ignore_columns=None, renaming=None) -> TableComparison:
         removed_rows = _get_sample(self.engine, rows.unjoined_left, self.row_samples)
 
         return TabularDelta(
-            new
-            if isinstance(new, str)
-            else getattr(getattr(right, "original"), "name", ""),
-            old
-            if isinstance(old, str)
-            else getattr(getattr(left, "original"), "name", ""),
+            (
+                new
+                if isinstance(new, str)
+                else getattr(getattr(right, "original"), "name", "")
+            ),
+            (
+                old
+                if isinstance(old, str)
+                else getattr(getattr(left, "original"), "name", "")
+            ),
             _columns=incomparable + comparable + uncompared,
             _old_rows=comp.row_counts.left,
             _new_rows=comp.row_counts.right,
@@ -208,8 +212,9 @@ def _get_value_change(
     except (sa.exc.ProgrammingError, sa.exc.DataError):
         warn(f"Couldn't get value change for {name}.")
         result = pd.DataFrame({old_name: None, new_name: None, "_count": [total]})
+    result.columns = result.columns.astype(str)
     return ColumnPair.from_sqlalchemy(
-        original_old, original_new, False, not comparable, result
+        original_old, original_new, False, not comparable, result.to_dict("records")
     )
 
 
diff --git a/tabulardelta/comparators/tabulardelta_dataclasses.py b/tabulardelta/comparators/tabulardelta_dataclasses.py
index d0db0c0..edea341 100644
--- a/tabulardelta/comparators/tabulardelta_dataclasses.py
+++ b/tabulardelta/comparators/tabulardelta_dataclasses.py
@@ -9,8 +9,6 @@
 from functools import cached_property
 from typing import Any
 
-import pandas as pd
-
 try:
     import sqlalchemy as sa
 except ImportError as e:
@@ -88,7 +86,7 @@ class ColumnPair:
     incomparable: bool = False
     """Whether data types of column in old and new table are incomparable."""
 
-    _values: pd.DataFrame | None = None
+    _values: list[dict[Any, Any]] | None = None
 
     @property
     def old(self) -> Column:
@@ -112,13 +110,13 @@ def new(self) -> Column:
 
     def __iter__(self) -> Iterator[ChangedValue]:
         """Examples of value changes."""
-        for idx, row in self._values.iterrows() if self._values is not None else []:
-            index = {k: v for k, v in row.to_dict().items() if k not in self._required}
+        for row in self._values or []:
+            index = {k: v for k, v in row.items() if k not in self._required}
             yield ChangedValue(index, *[row[key] for key in self._required])
 
     def __len__(self) -> int:
         """Total number of changes."""
-        return self._values["_count"].sum() if self._values is not None else 0
+        return sum(r["_count"] for r in self._values or [])
 
     @staticmethod
     def from_sqlalchemy(
@@ -126,7 +124,7 @@ def from_sqlalchemy(
         new: sa.sql.ColumnElement[Any] | None = None,
         join: bool = False,
         incomparable: bool = False,
-        _values: pd.DataFrame | None = None,
+        _values: list[dict[Any, Any]] | None = None,
     ) -> ColumnPair:
         """Creates TabularDelta.ColumnPair using SQLAlchemy columns.
 
@@ -139,8 +137,8 @@ def from_sqlalchemy(
                 Whether column was used as join column for comparison.
             incomparable :class:`bool`:
                 Whether data types of column in old and new table are incomparable.
-            _values :class:`pd.DataFrame`:
-                DataFrame with examples of value changes.
+            _values :class:`list[dict[Any, Any]]`:
+                List of rows with examples of value changes.
                 Contains old column, new column, :code:`_count` column,
                 and optionally other columns for identifying example rows.
 
@@ -163,7 +161,7 @@ def from_str(
         new_type: str | None = None,
         join: bool = False,
         incomparable: bool = False,
-        _values: pd.DataFrame | None = None,
+        _values: list[dict[Any, Any]] | None = None,
     ) -> ColumnPair:
         """Creates TabularDelta.ColumnPair using column names and types.
 
@@ -180,11 +178,11 @@ def from_str(
                 Whether column was used as join column for comparison.
             incomparable :class:`bool`:
                 Whether data types of column in old and new table are incomparable.
-            _values :class:`pd.DataFrame`:
-                DataFrame with examples of value changes.
+            _values :class:`list[dict[Any, Any]]`:
+                List of rows with examples of value changes.
                 Contains old column, new column, :code:`_count` column,
                 and optionally other columns for identifying example rows.
-                If the column wasn't renamed, the name of the old column in the DataFrame should
+                If the column wasn't renamed, the name of the old column should
                 be suffixed by :code:`_old`.
 
         Returns :class:`ColumnPair`:
@@ -200,7 +198,7 @@ def from_str(
 
     @cached_property
     def _df_old_name(self) -> str:
-        """Name of the old column in the DataFrame.
+        """Name of the old column in the row list.
 
         Suffixed with :code:`_old` if column wasn't renamed.
         """
@@ -208,32 +206,28 @@ def _df_old_name(self) -> str:
 
     @cached_property
     def _required(self) -> tuple[str, str, str]:
-        """Required columns in the DataFrame."""
+        """Required columns in the row list."""
         return self._df_old_name, self.new.name, "_count"
 
     def __post_init__(self):
-        """Check if DataFrame contains required columns and compactifies it."""
-        if self._values is None:
+        """Check if row list contains required columns and compactifies it."""
+        if not self._values:
             return
 
-        if missing := set(self._required) - set(self._values.columns):
+        if missing := set(self._required) - self._values[0].keys():
             raise ValueError(f"Missing columns in comparison: {missing}")
 
-        group_by_cols = [self._df_old_name, self.new.name]
-
-        # DIRTY FIX FOR PANDAS BUG: Categorical in GroupBy leads to
-        # ValueError: Length of values (5) does not match length of index (25)
-        for col in group_by_cols:
-            if self._values[col].dtype.name == "category":
-                self._values[col] = self._values[col].astype("object")
-
-        # Compactify dataframe by grouping equal changes together
-        groupby = self._values.groupby(group_by_cols, as_index=False, dropna=False)
-        join_cols = {c: (c, "first") for c in set(self._values) - set(self._required)}
-        agg = groupby.agg(_count=("_count", "sum"), **join_cols)  # type: ignore
-        sort = agg.sort_values(by="_count", ascending=False)
-        actual_changes = ~sort[self._df_old_name].isna() | ~sort[self.new.name].isna()
-        self._values = sort[actual_changes]
+        known_changes: dict[tuple[Any, Any], dict[str, Any]] = {}
+        for row in self._values:
+            chg = (row[self._df_old_name], row[self.new.name])
+            if chg[0] != chg[0] and chg[1] != chg[1]:
+                # Skip placeholder row
+                continue
+            if chg in known_changes:
+                known_changes[chg]["_count"] += row["_count"]
+            else:
+                known_changes[chg] = row
+        self._values = sorted(known_changes.values(), key=lambda x: -x["_count"])
 
 
 @dataclass(frozen=True)
@@ -308,7 +302,7 @@ class Rows:
 
     count: int
     """Number of represented rows."""
-    examples: list[dict[str, Any]] | None
+    examples: list[dict[Any, Any]] | None
     """Optional examples of represented rows."""
 
     def __len__(self) -> int:
@@ -378,13 +372,13 @@ class TabularDelta:
     """Number of equal rows (joined and all columns unchanged)."""
     _unequal_rows: int = 0
     """Number of unequal rows (joined but at least one column changed)."""
-    _example_added_rows: list[dict[str, Any]] = field(default_factory=list)
+    _example_added_rows: list[dict[Any, Any]] = field(default_factory=list)
     """Optional examples of added rows (only in new table)."""
-    _example_removed_rows: list[dict[str, Any]] = field(default_factory=list)
+    _example_removed_rows: list[dict[Any, Any]] = field(default_factory=list)
     """Optional examples of removed rows (only in old table)."""
-    _example_equal_rows: list[dict[str, Any]] = field(default_factory=list)
+    _example_equal_rows: list[dict[Any, Any]] = field(default_factory=list)
     """Optional examples of equal rows (joined and all columns unchanged)."""
-    _example_unequal_rows: list[dict[str, Any]] = field(default_factory=list)
+    _example_unequal_rows: list[dict[Any, Any]] = field(default_factory=list)
     """Optional examples of unequal rows (joined but at least one column changed)."""
 
     @cached_property
diff --git a/tests/test_comparators.py b/tests/test_comparators.py
index 9e3722f..898c2ab 100644
--- a/tests/test_comparators.py
+++ b/tests/test_comparators.py
@@ -140,8 +140,9 @@ def test_pandas_comparator():
     assert "paid" in incomparable_dtype_dict
     assert incomparable_dtype_dict["paid"][2] == "object"
     assert incomparable_dtype_dict["paid"][3] == "bool"
-    assert isinstance(incomparable_dtype_dict["paid"][4], pd.DataFrame)
-    cols = incomparable_dtype_dict["paid"][4].columns
+    assert incomparable_dtype_dict["paid"][4] is not None
+    assert len(incomparable_dtype_dict["paid"][4]) > 0
+    cols = incomparable_dtype_dict["paid"][4][0].keys()
     assert "name" in cols
     assert "_count" in cols
     assert incomparable_dtype_dict["paid"][0] in cols
@@ -150,12 +151,13 @@ def test_pandas_comparator():
     assert "id" in incomparable_dtype_dict
     assert incomparable_dtype_dict["id"][2] == "int64"
     assert incomparable_dtype_dict["id"][3] == "float64"
-    assert isinstance(incomparable_dtype_dict["id"][4], pd.DataFrame)
-    cols = incomparable_dtype_dict["id"][4].columns
+    assert incomparable_dtype_dict["id"][4] is not None
+    assert len(incomparable_dtype_dict["id"][4]) > 0
+    cols = incomparable_dtype_dict["id"][4][0].keys()
     assert "name" in cols
     assert "_count" in cols
-    assert incomparable_dtype_dict["id"][0] in incomparable_dtype_dict["id"][4].columns
-    assert incomparable_dtype_dict["id"][1] in incomparable_dtype_dict["id"][4].columns
+    assert incomparable_dtype_dict["id"][0] in cols
+    assert incomparable_dtype_dict["id"][1] in cols
 
     assert len(delta.rows.old) == 10
     assert len(delta.rows.new) == 11
@@ -209,19 +211,21 @@ def test_pandas_comparator():
     actual_differences = [diff for diff in delta.cols.differences if len(diff) > 0]
     assert len(actual_differences) == 1
     assert actual_differences[0].new and actual_differences[0].new.name == "expectation"
-    df = actual_differences[0]._values
-    assert df is not None
-    assert actual_differences[0].old and actual_differences[0].old.name in df.columns
-    assert actual_differences[0].new and actual_differences[0].new.name in df.columns
+    changes = actual_differences[0]._values
+    assert changes is not None
+    assert len(changes) > 0
+    cols = changes[0].keys()
+    assert actual_differences[0].old and actual_differences[0].old.name in cols
+    assert actual_differences[0].new and actual_differences[0].new.name in cols
     expected_df = pd.DataFrame(
         {
+            "name": ["E"],
             "expectation_old": [0.5],
             "expectation": [0.55],
             "_count": [1],
-            "name": ["E"],
         }
     )
-    assert_frame_equal(df.reset_index(drop=True), expected_df.reset_index(drop=True))
+    assert_frame_equal(pd.DataFrame(changes), expected_df.reset_index(drop=True))
 
 
 def test_pandas_comparator_row_col_orders():
@@ -323,8 +327,9 @@ def test_sqlcompyre_comparator(mssql_engine: sa.Engine, input_type: str):
         == 'VARCHAR COLLATE "SQL_Latin1_General_CP1_CI_AS"'
     )
     assert incomparable_dtype_dict["paid"][3] == "BIT"
-    assert isinstance(incomparable_dtype_dict["paid"][4], pd.DataFrame)
-    cols = incomparable_dtype_dict["paid"][4].columns
+    assert incomparable_dtype_dict["paid"][4] is not None
+    assert len(incomparable_dtype_dict["paid"][4]) > 0
+    cols = incomparable_dtype_dict["paid"][4][0].keys()
     assert "name" in cols
     assert "_count" in cols
     assert incomparable_dtype_dict["paid"][0] in cols
@@ -377,20 +382,21 @@ def test_sqlcompyre_comparator(mssql_engine: sa.Engine, input_type: str):
     assert actual_differences[0].new
     assert actual_differences[0].old
     assert actual_differences[0].new.name == "expectation"
-    df = actual_differences[0]._values
-    assert df is not None
-    assert actual_differences[0].old.name in df.columns
-    assert actual_differences[0].new.name in df.columns
+    diff_values = actual_differences[0]._values
+    assert diff_values is not None
+    assert len(diff_values) > 0
+    assert actual_differences[0].old.name in diff_values[0].keys()
+    assert actual_differences[0].new.name in diff_values[0].keys()
     expected = pd.DataFrame(
         {
-            "expectation_old": [0.5],
             "expectation": [0.55],
+            "expectation_old": [0.5],
             "_count": [1],
             "name": ["E"],
         }
     )
     assert_frame_equal(
-        df.reset_index(drop=True), expected.reset_index(drop=True), check_dtype=False
+        pd.DataFrame(diff_values), expected.reset_index(drop=True), check_dtype=False
     )
 
 
diff --git a/tests/test_formatters.py b/tests/test_formatters.py
index e57196f..8b587f8 100644
--- a/tests/test_formatters.py
+++ b/tests/test_formatters.py
@@ -60,25 +60,29 @@ def gen_chg_values(
     ) -> ColumnPair:
         if chg.old is None or chg.new is None:
             raise ValueError("Can't generate values for non-matched columns.")
-        size = cast(int, gen.integers(0, 2 ** gen.integers(0, 10)))
+        size = gen.integers(0, 2 ** gen.integers(0, 10))
         old_renamed = Column(
             chg.old.name + ("_old" if chg.old.name == chg.new.name else ""),
             chg.old.type,
         )
-        indexes = {col.name: gen_col_values(col.type, size) for col in join_columns}
+        indexes = {
+            col.name: gen_col_values(col.type, cast(int, size)) for col in join_columns
+        }
         df = pd.DataFrame(
             {
-                old_renamed.name: gen_col_values(chg.old.type, size),
-                chg.new.name: gen_col_values(chg.new.type, size),
+                old_renamed.name: gen_col_values(chg.old.type, cast(int, size)),
+                chg.new.name: gen_col_values(chg.new.type, cast(int, size)),
                 **indexes,
-                "_count": gen_col_values("uint64", size).astype("int"),
+                "_count": gen_col_values("uint64", cast(int, size)).astype("int"),
             }
         )
         if gen.random() < 0.5:
             additional = gen.integers(0, 10 ** gen.integers(0, 8))
             df.loc[len(df)] = [None] * (2 + len(join_columns)) + [additional]
             df["_count"] = df["_count"].astype("int")
-        return ColumnPair(chg.old, chg.new, incomparable=incomparable, _values=df)
+        return ColumnPair(
+            chg.old, chg.new, incomparable=incomparable, _values=df.to_dict("records")
+        )
 
     def gen_change() -> ColumnPair:
         old = gen_col_meta()

From 641d33a5465a35c149007e3cf1d94f6ad3180eac Mon Sep 17 00:00:00 2001
From: Aaron Tacke <tacke@in.tum.de>
Date: Sun, 8 Jun 2025 10:11:43 +0200
Subject: [PATCH 2/4] Remove Pandas from sqlcompyre_comparator

---
 .../comparators/sqlcompyre_comparator.py         | 16 +++++++++-------
 1 file changed, 9 insertions(+), 7 deletions(-)

diff --git a/tabulardelta/comparators/sqlcompyre_comparator.py b/tabulardelta/comparators/sqlcompyre_comparator.py
index 48dfc7b..d830a98 100644
--- a/tabulardelta/comparators/sqlcompyre_comparator.py
+++ b/tabulardelta/comparators/sqlcompyre_comparator.py
@@ -7,7 +7,6 @@
 from typing import Any, TypeVar
 from warnings import warn
 
-import pandas as pd
 import sqlalchemy as sa
 import sqlcompyre as sc
 from sqlcompyre.analysis import TableComparison
@@ -207,14 +206,17 @@ def _get_value_change(
     try:
         with tab_comp.engine.connect() as conn:
             total = conn.execute(sa.select(count).select_from(diffs)).scalar() or total
-        result = pd.read_sql(query, tab_comp.engine).astype("object")
-        result.loc[result.shape[0], "_count"] = total - result["_count"].sum()
-    except (sa.exc.ProgrammingError, sa.exc.DataError):
+            result_proxy = conn.execute(query)
+            columns = result_proxy.keys()
+            rows = result_proxy.fetchall()
+            result = [dict(zip(columns, row)) for row in rows]
+        result.append({k: float("nan") for k in result[0].keys()})
+        result[-1]["_count"] = total - sum(row["_count"] for row in result[:-1])
+    except (sa.exc.ProgrammingError, sa.exc.DataError, IndexError):
         warn(f"Couldn't get value change for {name}.")
-        result = pd.DataFrame({old_name: None, new_name: None, "_count": [total]})
-    result.columns = result.columns.astype(str)
+        result = [{old_name: float("nan"), new_name: float("nan"), "_count": [total]}]
     return ColumnPair.from_sqlalchemy(
-        original_old, original_new, False, not comparable, result.to_dict("records")
+        original_old, original_new, False, not comparable, result
     )
 
 

From 191b36c2d7e7672f274a1fe62007b01b67b7d3ec Mon Sep 17 00:00:00 2001
From: Aaron Tacke <tacke@in.tum.de>
Date: Mon, 9 Jun 2025 15:16:07 +0200
Subject: [PATCH 3/4] Adapt tests to work without pandas

---
 .github/workflows/ci.yml    |    3 +-
 pixi.lock                   | 3124 +++++++++++++++++++----------------
 pixi.toml                   |   11 +-
 tests/test_comparators.py   |  396 ++++-
 tests/test_docs_examples.py |   13 +-
 tests/test_formatters.py    |   20 +-
 6 files changed, 2128 insertions(+), 1439 deletions(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 101b75f..58ba214 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -31,6 +31,7 @@ jobs:
           - py311
           - py312
           - no-sql
+          - no-pandas
         os:
           - ubuntu-22.04
           - windows-latest
@@ -55,4 +56,4 @@ jobs:
       - name: Install repository
         run: pixi run -e ${{ matrix.environment }} postinstall
       - name: Run pytest
-        run: pixi run -e ${{ matrix.environment }} test-coverage --color=yes ${{ matrix.environment=='no-sql' && '-m "not sql"' || ''}}
+        run: pixi run -e ${{ matrix.environment }} test-coverage --color=yes -m ${{ matrix.environment=='no-sql' && '"not sql"' || (matrix.environment=='no-pandas' && '"not pandas"' || '""')}}
diff --git a/pixi.lock b/pixi.lock
index c2beec6..5e106b0 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -10,7 +10,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/noarch/_python_abi3_support-1.0-hd8ed1ab_2.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/backports-1.0-pyhd8ed1ab_5.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/backports.tarfile-1.2.0-pyhd8ed1ab_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/brotli-python-1.1.0-py313h46c70d0_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/brotli-python-1.1.0-py313h46c70d0_3.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-h4bc722e_7.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2025.4.26-hbd8a1cb_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/certifi-2025.4.26-pyhd8ed1ab_0.conda
@@ -35,22 +35,16 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/noarch/jeepney-0.9.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/keyring-25.6.0-pyha804496_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.43-h712a8e2_4.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libblas-3.9.0-31_h59b9bed_openblas.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcblas-3.9.0-31_he106b2a_openblas.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.7.0-h5888daf_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.4.6-h2dba641_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-15.1.0-h767d61c_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-15.1.0-h69a702a_2.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgfortran-15.1.0-h69a702a_2.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-15.1.0-hcea5267_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libglib-2.84.2-h3618099_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-15.1.0-h767d61c_2.conda
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   - vc >=14.2,<15
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+  - aws-c-http >=0.10.1,<0.10.2.0a0
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   license: Apache-2.0
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   license: Apache-2.0
   license_family: Apache
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-  md5: 8ee52f649777534cd21fc6905b83316d
+- conda: https://conda.anaconda.org/conda-forge/linux-64/aws-c-http-0.10.1-hcfde5e4_4.conda
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+  - libgcc >=13
   - aws-c-io >=0.19.1,<0.19.2.0a0
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+  - aws-c-common >=0.12.3,<0.12.4.0a0
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   license: Apache-2.0
   license_family: APACHE
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-  - aws-c-cal >=0.9.1,<0.9.2.0a0
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+  - aws-c-io >=0.19.1,<0.19.2.0a0
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   license: Apache-2.0
   license_family: APACHE
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   - aws-c-compression >=0.3.1,<0.3.2.0a0
-  - aws-c-cal >=0.9.1,<0.9.2.0a0
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   license: Apache-2.0
   license_family: APACHE
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-  - aws-c-cal >=0.9.1,<0.9.2.0a0
   - aws-c-compression >=0.3.1,<0.3.2.0a0
+  - aws-c-cal >=0.9.2,<0.9.3.0a0
   - aws-c-common >=0.12.3,<0.12.4.0a0
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   license: Apache-2.0
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+  md5: 012df4026887e82115796d4e664abe2d
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   - libgcc >=13
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   license: Apache-2.0
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   license: Apache-2.0
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+  - aws-c-cal >=0.9.2,<0.9.3.0a0
   - aws-c-common >=0.12.3,<0.12.4.0a0
   license: Apache-2.0
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   - ucrt >=10.0.20348.0
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-  - aws-c-cal >=0.9.1,<0.9.2.0a0
   license: Apache-2.0
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 - conda: https://conda.anaconda.org/conda-forge/linux-64/aws-c-mqtt-0.13.1-h7b3935a_0.conda
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-  md5: eff3d619b784eb000e62a6fd7797d6a5
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-  - aws-c-http >=0.10.1,<0.10.2.0a0
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+  - openssl >=3.5.0,<4.0a0
   license: Apache-2.0
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-  - aws-c-cal >=0.9.1,<0.9.2.0a0
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   - aws-checksums >=0.2.7,<0.2.8.0a0
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   license: Apache-2.0
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-  - aws-c-cal >=0.9.1,<0.9.2.0a0
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   - aws-checksums >=0.2.7,<0.2.8.0a0
   - aws-c-io >=0.19.1,<0.19.2.0a0
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   license: Apache-2.0
   license_family: APACHE
-  size: 116445
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-  md5: 8a3879d0655a704292a7d965053d0989
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   - vc14_runtime >=14.29.30139
   - ucrt >=10.0.20348.0
-  - aws-c-auth >=0.9.0,<0.9.1.0a0
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   - aws-checksums >=0.2.7,<0.2.8.0a0
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   license: Apache-2.0
   license_family: APACHE
-  size: 125858
-  timestamp: 1748316681469
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-  md5: 656bd42917a2ad14a7ff09ad57c758a0
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   license: Apache-2.0
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   license: Apache-2.0
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-  - aws-c-common >=0.12.3,<0.12.4.0a0
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   license: Apache-2.0
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-  size: 290843
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 - conda: https://conda.anaconda.org/conda-forge/linux-64/aws-sdk-cpp-1.11.510-h4607db7_10.conda
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/brotli-python-1.1.0-py312h2ec8cdc_2.conda
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   constrains:
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+  - libbrotlicommon 1.1.0 hb9d3cd8_3
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+  - libbrotlicommon 1.1.0 h2466b09_3
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-  sha256: 7aa8c8e6c08e3376e9231a03505923cd1f8a4b4870e65a2be798d1f281820a72
-  md5: 27e54d645fac93f95052610af45161ee
+  size: 267736
+  timestamp: 1749298294844
+- conda: https://conda.anaconda.org/conda-forge/osx-64/ruamel.yaml-0.18.13-py311h4d7f069_0.conda
+  sha256: 8bc421c1ee2c7b1e1f4006099099ac2f504df10a69d0582912988b0c8856d30e
+  md5: 4e5d89eb5231c8da27ddef64a94e292f
   depends:
   - __osx >=10.13
   - python >=3.11,<3.12.0a0
@@ -14601,11 +14977,11 @@ packages:
   - ruamel.yaml.clib >=0.1.2
   license: MIT
   license_family: MIT
-  size: 275237
-  timestamp: 1748630208007
-- conda: https://conda.anaconda.org/conda-forge/osx-64/ruamel.yaml-0.18.12-py312h01d7ebd_0.conda
-  sha256: 2b81c8e935b01e9030cac59ca79acd5dcc7e781fe8562f5edcb2d8cf32cfdeb2
-  md5: 8b2741eb5a2239d0d3709934519ee8c4
+  size: 274400
+  timestamp: 1749298337228
+- conda: https://conda.anaconda.org/conda-forge/osx-64/ruamel.yaml-0.18.13-py312h01d7ebd_0.conda
+  sha256: 4800a0880d96fbc00170ba32b7dfac2d2c430bf6f0eca94867a7e5098510606f
+  md5: bde74d2a57403b701af62c4370153869
   depends:
   - __osx >=10.13
   - python >=3.12,<3.13.0a0
@@ -14613,23 +14989,11 @@ packages:
   - ruamel.yaml.clib >=0.1.2
   license: MIT
   license_family: MIT
-  size: 269088
-  timestamp: 1748630324465
-- conda: https://conda.anaconda.org/conda-forge/osx-64/ruamel.yaml-0.18.12-py313h63b0ddb_0.conda
-  sha256: 16df93a20a89268fb465cdd653bbd618231412a6748650f6292ad3d067d9264a
-  md5: 5e4f1fd6fb52144a0e079f3b263ac896
-  depends:
-  - __osx >=10.13
-  - python >=3.13,<3.14.0a0
-  - python_abi 3.13.* *_cp313
-  - ruamel.yaml.clib >=0.1.2
-  license: MIT
-  license_family: MIT
-  size: 272036
-  timestamp: 1748630266373
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/ruamel.yaml-0.18.12-py311h917b07b_0.conda
-  sha256: 6bb72d61c573707e92940e3ee5b1e913cf36722f4f7af97799dd4b10b1997179
-  md5: 2e27f476a74ae2a543b6ecc6dbe482e6
+  size: 267572
+  timestamp: 1749298321435
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/ruamel.yaml-0.18.13-py311h917b07b_0.conda
+  sha256: c64177c51887031344d2613fda6b6e4b102db476bcf97e67dfe579cd10b6d168
+  md5: 2db52dbddb4c0129c35aa93fbe5c0762
   depends:
   - __osx >=11.0
   - python >=3.11,<3.12.0a0
@@ -14638,11 +15002,11 @@ packages:
   - ruamel.yaml.clib >=0.1.2
   license: MIT
   license_family: MIT
-  size: 275746
-  timestamp: 1748630248897
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/ruamel.yaml-0.18.12-py312hea69d52_0.conda
-  sha256: bb746f5bbb7ae3c37b7a85af690bb9380bdcaa743fe87568953cf9714d246c0f
-  md5: b80d543145b6fea31855178500d05a34
+  size: 275564
+  timestamp: 1749298548541
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/ruamel.yaml-0.18.13-py312hea69d52_0.conda
+  sha256: ecc30edea3a4d8f7d4c875101d911602d80c61bffe47991d2822890493b1bf6d
+  md5: 877c08d6812c47b228c956119641cf1b
   depends:
   - __osx >=11.0
   - python >=3.12,<3.13.0a0
@@ -14651,11 +15015,11 @@ packages:
   - ruamel.yaml.clib >=0.1.2
   license: MIT
   license_family: MIT
-  size: 268991
-  timestamp: 1748630316232
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/ruamel.yaml-0.18.12-py313h90d716c_0.conda
-  sha256: a698568d53bf3a1b1d914a422ee2849c0630b89ebdaf2ca465e2ef4f46765f39
-  md5: 3df63e960f79c9ea8ba7de55876938b2
+  size: 267757
+  timestamp: 1749298394660
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/ruamel.yaml-0.18.13-py313h90d716c_0.conda
+  sha256: e766762e7d10986772dbd986e8236c5a6868dc7124b699a702ef0344a8795f7a
+  md5: cdb428c446fee2f78a883ec4b45a4412
   depends:
   - __osx >=11.0
   - python >=3.13,<3.14.0a0
@@ -14664,11 +15028,11 @@ packages:
   - ruamel.yaml.clib >=0.1.2
   license: MIT
   license_family: MIT
-  size: 271235
-  timestamp: 1748630210978
-- conda: https://conda.anaconda.org/conda-forge/win-64/ruamel.yaml-0.18.12-py311he736701_0.conda
-  sha256: 50099b7c248b53fbd6e01c441fd6fdde2789e69b4d763c2f35732fb34485b43a
-  md5: c42c8b8632376b9f000bd3ef4ced1b44
+  size: 271455
+  timestamp: 1749298411542
+- conda: https://conda.anaconda.org/conda-forge/win-64/ruamel.yaml-0.18.13-py311he736701_0.conda
+  sha256: 782bfc40be4df4e74f76fb8e6f8cf6a15923af1f54e8fffe73b688910ea2f540
+  md5: 29e83b10932ea5dcb1f69b9df7637e04
   depends:
   - python >=3.11,<3.12.0a0
   - python_abi 3.11.* *_cp311
@@ -14678,11 +15042,11 @@ packages:
   - vc14_runtime >=14.29.30139
   license: MIT
   license_family: MIT
-  size: 274308
-  timestamp: 1748630204698
-- conda: https://conda.anaconda.org/conda-forge/win-64/ruamel.yaml-0.18.12-py312h4389bb4_0.conda
-  sha256: 24a0d68804427069b1e883d146e5a08086a11b5c1d586a44cad1ab257fbcd5ec
-  md5: f182c13ef8f6a9cd50d13fe37605183e
+  size: 274774
+  timestamp: 1749298364031
+- conda: https://conda.anaconda.org/conda-forge/win-64/ruamel.yaml-0.18.13-py312h4389bb4_0.conda
+  sha256: dea6da7f1bd9e8f8bb70175c8fb499cc4b416c8a05ab0dab68ab4998f6d4c73f
+  md5: f5ca380f56544d98f5c0866cbebe1163
   depends:
   - python >=3.12,<3.13.0a0
   - python_abi 3.12.* *_cp312
@@ -14692,11 +15056,11 @@ packages:
   - vc14_runtime >=14.29.30139
   license: MIT
   license_family: MIT
-  size: 269197
-  timestamp: 1748630194428
-- conda: https://conda.anaconda.org/conda-forge/win-64/ruamel.yaml-0.18.12-py313ha7868ed_0.conda
-  sha256: 15d83ac014bd31d45e09771547c0cd7e373d2cd052ccc96b3165f7616b158a05
-  md5: e81a5ea01bcfbae6cd79ad29a6ccf0ba
+  size: 268507
+  timestamp: 1749298366428
+- conda: https://conda.anaconda.org/conda-forge/win-64/ruamel.yaml-0.18.13-py313ha7868ed_0.conda
+  sha256: f3506b093e72e0797cf6e456331702bd07e4daeeb05fe36839fe2ba326622669
+  md5: 2581a9b1a248ffc1ab9226f7f74b5cb5
   depends:
   - python >=3.13,<3.14.0a0
   - python_abi 3.13.* *_cp313
@@ -14706,8 +15070,8 @@ packages:
   - vc14_runtime >=14.29.30139
   license: MIT
   license_family: MIT
-  size: 271532
-  timestamp: 1748630263167
+  size: 269677
+  timestamp: 1749298464344
 - conda: https://conda.anaconda.org/conda-forge/linux-64/ruamel.yaml.clib-0.2.8-py311h9ecbd09_1.conda
   sha256: e38364ad63e29ea0134b2d6661c71d78a384a6f0f0c6248a270c97a73a970de8
   md5: e56869fca385961323e43783b89bef66
@@ -14754,17 +15118,6 @@ packages:
   license_family: MIT
   size: 122331
   timestamp: 1728724619287
-- conda: https://conda.anaconda.org/conda-forge/osx-64/ruamel.yaml.clib-0.2.8-py313hb558fbc_1.conda
-  sha256: 02ce4f34ca0e8acdcc67591142675657c9f4951f9cf65a5274dcb4f310227e88
-  md5: d9f11ed93c18a0d4fce36373a43caadb
-  depends:
-  - __osx >=10.13
-  - python >=3.13,<3.14.0a0
-  - python_abi 3.13.* *_cp313
-  license: MIT
-  license_family: MIT
-  size: 121594
-  timestamp: 1728724629571
 - conda: https://conda.anaconda.org/conda-forge/osx-arm64/ruamel.yaml.clib-0.2.8-py311hae2e1ce_1.conda
   sha256: 4a61547188dff0aa1cbab2cc6a6ce3ca354fe7b48c5bbf765d676df8c29e5d80
   md5: 11dccbe06e61a3d95223ce75013a7c80
@@ -14840,9 +15193,9 @@ packages:
   license_family: MIT
   size: 108488
   timestamp: 1728724833760
-- conda: https://conda.anaconda.org/conda-forge/linux-64/ruff-0.11.12-py312h1d08497_0.conda
-  sha256: e6a3e0fc264e4cddccd2a096dc13b61bf7f737fac5e42689a4272718acfe9c1c
-  md5: 0731d0ce2209c306e61ba3617728686d
+- conda: https://conda.anaconda.org/conda-forge/linux-64/ruff-0.11.13-py312h1d08497_0.conda
+  sha256: 25e99382bbe8431e25f086960ba34de8d975c903a4810fbf2009e95285e4d719
+  md5: 8e7c909d4f48865c8c5241d83649fc66
   depends:
   - __glibc >=2.17,<3.0.a0
   - libgcc >=13
@@ -14853,25 +15206,25 @@ packages:
   - __glibc >=2.17
   license: MIT
   license_family: MIT
-  size: 8209280
-  timestamp: 1748541900869
-- conda: https://conda.anaconda.org/conda-forge/osx-64/ruff-0.11.12-py313h1aad41e_0.conda
-  sha256: 55abc4ea52d887ef3097b9fae66bd0dc976cd4491c0fc992e52c415e596ce6e1
-  md5: ea82c2786814a9e189d6f154e2e57935
+  size: 8254968
+  timestamp: 1749215957598
+- conda: https://conda.anaconda.org/conda-forge/osx-64/ruff-0.11.13-py312heade784_0.conda
+  sha256: 9fbe59d5339e8c1d102591725a0d13c53c06c06c6788bc82b06782eca3e47119
+  md5: 78236a42e7a04fba6484250ae90c5a85
   depends:
   - __osx >=10.13
   - libcxx >=18
-  - python >=3.13,<3.14.0a0
-  - python_abi 3.13.* *_cp313
+  - python >=3.12,<3.13.0a0
+  - python_abi 3.12.* *_cp312
   constrains:
   - __osx >=10.13
   license: MIT
   license_family: MIT
-  size: 7840944
-  timestamp: 1748542910589
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/ruff-0.11.12-py313h19b3928_0.conda
-  sha256: 6a433bf4908aaa0cdf26676a1e190893e2db042708e110d77d9eff93990df1ae
-  md5: f0f3acf676fbd9eb9e87bc8f13b39875
+  size: 7893708
+  timestamp: 1749216415517
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/ruff-0.11.13-py313h19b3928_0.conda
+  sha256: cc86ed15d30fe6039bf5c83d9157b44a2ad0133ce55209aff02330855455684b
+  md5: 8800290270f1d0d9d8482a153c92dc5e
   depends:
   - __osx >=11.0
   - libcxx >=18
@@ -14882,11 +15235,11 @@ packages:
   - __osx >=11.0
   license: MIT
   license_family: MIT
-  size: 7389768
-  timestamp: 1748542655722
-- conda: https://conda.anaconda.org/conda-forge/win-64/ruff-0.11.12-py313h784dc11_0.conda
-  sha256: c7eeab8c3e827553643af3ccd6bf26d812436af593f56f42aaf6762a5edf2553
-  md5: b24d86dc71ddc9fd5b39d0378b52b9e2
+  size: 7444761
+  timestamp: 1749216159571
+- conda: https://conda.anaconda.org/conda-forge/win-64/ruff-0.11.13-py313h784dc11_0.conda
+  sha256: f1855143169ce7217158829d64f46fc5a36806875b83068655a9c02e8b3084c4
+  md5: 747a0705331d45934a8c853b4beb5111
   depends:
   - python >=3.13,<3.14.0a0
   - python_abi 3.13.* *_cp313
@@ -14895,8 +15248,8 @@ packages:
   - vc14_runtime >=14.29.30139
   license: MIT
   license_family: MIT
-  size: 8215905
-  timestamp: 1748542651315
+  size: 8262379
+  timestamp: 1749216842505
 - conda: https://conda.anaconda.org/conda-forge/linux-64/s2n-1.5.21-h7ab7c64_0.conda
   sha256: c8b252398b502a5cc6ea506fd2fafe7e102e7c9e2ef48b7813566e8a72ce2205
   md5: 28b5a7895024a754249b2ad7de372faa
@@ -15201,19 +15554,6 @@ packages:
   license_family: MIT
   size: 3541719
   timestamp: 1747299113055
-- conda: https://conda.anaconda.org/conda-forge/osx-64/sqlalchemy-2.0.41-py313h63b0ddb_0.conda
-  sha256: 4405cc737a3dc4d6953745610e1ade247cfb015a369b406e0e037e12631b8ddc
-  md5: 85e82a7cc9f30d3848fbf62537c0296b
-  depends:
-  - __osx >=10.13
-  - greenlet !=0.4.17
-  - python >=3.13,<3.14.0a0
-  - python_abi 3.13.* *_cp313
-  - typing-extensions >=4.6.0
-  license: MIT
-  license_family: MIT
-  size: 3595916
-  timestamp: 1747299086608
 - conda: https://conda.anaconda.org/conda-forge/osx-arm64/sqlalchemy-2.0.41-py311h917b07b_0.conda
   sha256: 8d9098ab8282166e900458e33ee7bc35c8e3187f0d5545ae53deb4172d0a6673
   md5: d9893da3d6686adde083f0ca2f8d75b6
@@ -15618,19 +15958,19 @@ packages:
   license_family: MIT
   size: 13904
   timestamp: 1725784191021
-- conda: https://conda.anaconda.org/conda-forge/osx-64/ukkonen-1.0.1-py313h0c4e38b_5.conda
-  sha256: 6abf14f984a1fc3641908cb7e96ba8f2ce56e6f81069852b384e1755f8f5225e
-  md5: 6185cafe9e489071688304666923c2ad
+- conda: https://conda.anaconda.org/conda-forge/osx-64/ukkonen-1.0.1-py312hc5c4d5f_5.conda
+  sha256: f6433143294c1ca52410bf8bbca6029a04f2061588d32e6d2b67c7fd886bc4e0
+  md5: f270aa502d8817e9cb3eb33541f78418
   depends:
   - __osx >=10.13
   - cffi
   - libcxx >=17
-  - python >=3.13.0rc1,<3.14.0a0
-  - python_abi 3.13.* *_cp313
+  - python >=3.12,<3.13.0a0
+  - python_abi 3.12.* *_cp312
   license: MIT
   license_family: MIT
-  size: 13126
-  timestamp: 1725784265187
+  size: 13031
+  timestamp: 1725784199719
 - conda: https://conda.anaconda.org/conda-forge/osx-arm64/ukkonen-1.0.1-py313hf9c7212_5.conda
   sha256: 482eac475928c031948790647ae10c2cb1d4a779c2e8f35f5fd1925561b13203
   md5: 8ddba23e26957f0afe5fc9236c73124a
@@ -15786,17 +16126,17 @@ packages:
   license: LicenseRef-Public-Domain
   size: 9555
   timestamp: 1733130678956
-- conda: https://conda.anaconda.org/conda-forge/linux-64/xkeyboard-config-2.44-hb9d3cd8_0.conda
-  sha256: 83ad2be5eb1d359b4cd7d7a93a6b25cdbfdce9d27b37508e2a4efe90d3a4ed80
-  md5: 7c91bfc90672888259675ad2ad28af9c
+- conda: https://conda.anaconda.org/conda-forge/linux-64/xkeyboard-config-2.45-hb9d3cd8_0.conda
+  sha256: a5d4af601f71805ec67403406e147c48d6bad7aaeae92b0622b7e2396842d3fe
+  md5: 397a013c2dc5145a70737871aaa87e98
   depends:
   - __glibc >=2.17,<3.0.a0
   - libgcc >=13
   - xorg-libx11 >=1.8.12,<2.0a0
   license: MIT
   license_family: MIT
-  size: 392870
-  timestamp: 1745806998840
+  size: 392406
+  timestamp: 1749375847832
 - conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libice-1.1.2-hb9d3cd8_0.conda
   sha256: c12396aabb21244c212e488bbdc4abcdef0b7404b15761d9329f5a4a39113c4b
   md5: fb901ff28063514abb6046c9ec2c4a45
@@ -16104,15 +16444,15 @@ packages:
   license_family: MIT
   size: 63274
   timestamp: 1641347623319
-- conda: https://conda.anaconda.org/conda-forge/noarch/zipp-3.22.0-pyhd8ed1ab_0.conda
-  sha256: 3f7a58ff4ff1d337d56af0641a7eba34e7eea0bf32e49934c96ee171640f620b
-  md5: 234be740b00b8e41567e5b0ed95aaba9
+- conda: https://conda.anaconda.org/conda-forge/noarch/zipp-3.23.0-pyhd8ed1ab_0.conda
+  sha256: 7560d21e1b021fd40b65bfb72f67945a3fcb83d78ad7ccf37b8b3165ec3b68ad
+  md5: df5e78d904988eb55042c0c97446079f
   depends:
   - python >=3.9
   license: MIT
   license_family: MIT
-  size: 22691
-  timestamp: 1748277499928
+  size: 22963
+  timestamp: 1749421737203
 - conda: https://conda.anaconda.org/conda-forge/linux-64/zlib-1.3.1-hb9d3cd8_2.conda
   sha256: 5d7c0e5f0005f74112a34a7425179f4eb6e73c92f5d109e6af4ddeca407c92ab
   md5: c9f075ab2f33b3bbee9e62d4ad0a6cd8
@@ -16170,6 +16510,18 @@ packages:
   license_family: BSD
   size: 736909
   timestamp: 1745869790689
+- conda: https://conda.anaconda.org/conda-forge/osx-64/zstandard-0.23.0-py312h01d7ebd_2.conda
+  sha256: 970db6b96b9ac7c1418b8743cf63c3ee6285ec7f56ffc94ac7850b4c2ebc3095
+  md5: 64aea64b791ab756ef98c79f0e48fee5
+  depends:
+  - __osx >=10.13
+  - cffi >=1.11
+  - python >=3.12,<3.13.0a0
+  - python_abi 3.12.* *_cp312
+  license: BSD-3-Clause
+  license_family: BSD
+  size: 690063
+  timestamp: 1745869852235
 - conda: https://conda.anaconda.org/conda-forge/osx-64/zstandard-0.23.0-py313h63b0ddb_2.conda
   sha256: ab53cc54d0af1a8d85a50510209595d09c584101668f35c0fd3c4fbd59c4ece2
   md5: 3babd14037340de278106b258fdb28d9
diff --git a/pixi.toml b/pixi.toml
index 578f1da..3a0a9c8 100644
--- a/pixi.toml
+++ b/pixi.toml
@@ -9,8 +9,6 @@ postinstall = "pip install --no-build-isolation --no-deps --disable-pip-version-
 
 [dependencies]
 python = ">=3.11"
-numpy = ">=1.24.4,<3"
-pandas = ">=2.0.3,<3"
 
 [host-dependencies]
 pip = "*"
@@ -71,9 +69,14 @@ sqlalchemy = "*"
 sqlcompyre = "*"
 pyodbc = "*"
 
+[feature.pandas.dependencies]
+numpy = ">=1.24.4,<3"
+pandas = ">=2.0.3,<3"
+
 [environments]
-no-sql = ["test"]
-default = ["test", "sql"]
+default = ["test", "pandas", "sql"]
+no-sql = ["test", "pandas"]
+no-pandas = ["test", "sql"]
 py311 = ["py311", "test", "sql"]
 py312 = ["py312", "test", "sql"]
 docs = ["docs", "sql"]
diff --git a/tests/test_comparators.py b/tests/test_comparators.py
index 898c2ab..fed5a54 100644
--- a/tests/test_comparators.py
+++ b/tests/test_comparators.py
@@ -2,10 +2,7 @@
 # SPDX-License-Identifier: LicenseRef-QuantCo
 from typing import Any, NamedTuple
 
-import numpy as np
-import pandas as pd
 import pytest
-from pandas.testing import assert_frame_equal
 
 from tabulardelta import (
     DetailedTextFormatter,
@@ -18,6 +15,12 @@
     ColumnPair,
 )
 
+try:
+    import numpy as np
+    import pandas as pd
+except ImportError:
+    pass
+
 try:
     from tests.mssql_container.cached_mssql_container import mssql_engine
 except ImportError:
@@ -99,6 +102,217 @@ def new_df():
     return df
 
 
+def old_df_rows():
+    return [
+        {
+            "id": 0,
+            "equal": 0,
+            "paid": "yes",
+            "unnecessary": 0,
+            "name": "A",
+            "measurement": "[0.1, 0.1, 0.1]",
+            "expectation": 0.12,
+        },
+        {
+            "id": 1,
+            "equal": 0,
+            "paid": "no",
+            "unnecessary": 0,
+            "name": "B",
+            "measurement": "[0.2, 0.2, 0.2]",
+            "expectation": 0.24,
+        },
+        {
+            "id": 2,
+            "equal": 0,
+            "paid": "yes",
+            "unnecessary": 0,
+            "name": "C",
+            "measurement": "[0.3, 0.3, 0.3]",
+            "expectation": 0.36,
+        },
+        {
+            "id": 3,
+            "equal": 0,
+            "paid": "maybe",
+            "unnecessary": 0,
+            "name": "D",
+            "measurement": "[0.4, 0.4, 0.4]",
+            "expectation": 0.48,
+        },
+        {
+            "id": 4,
+            "equal": 0,
+            "paid": "yes",
+            "unnecessary": 0,
+            "name": "E",
+            "measurement": "[0.5, 0.5, 0.5]",
+            "expectation": 0.5,
+        },
+        {
+            "id": 5,
+            "equal": 0,
+            "paid": "no",
+            "unnecessary": 0,
+            "name": "F",
+            "measurement": "[0.6, 0.6, 0.6]",
+            "expectation": 0.68,
+        },
+        {
+            "id": 6,
+            "equal": 0,
+            "paid": "yes",
+            "unnecessary": 0,
+            "name": "G",
+            "measurement": "[0.7, 0.7, 0.7]",
+            "expectation": 0.76,
+        },
+        {
+            "id": 7,
+            "equal": 0,
+            "paid": "no",
+            "unnecessary": 0,
+            "name": "H",
+            "measurement": "[0.8, 0.8, 0.8]",
+            "expectation": 0.84,
+        },
+        {
+            "id": 8,
+            "equal": 0,
+            "paid": "yes",
+            "unnecessary": 0,
+            "name": "I",
+            "measurement": "[0.9, 0.9, 0.9]",
+            "expectation": 0.92,
+        },
+        {
+            "id": 9,
+            "equal": 0,
+            "paid": "no",
+            "unnecessary": 0,
+            "name": "J",
+            "measurement": "[1.0, 1.0, 1.0]",
+            "expectation": 1.0,
+        },
+    ]
+
+
+def new_df_rows():
+    return [
+        {
+            "id": 1.0,
+            "equal": 0,
+            "paid": False,
+            "name": "B",
+            "renamedmeasurement": "[0.2, 0.2, 0.2]",
+            "expectation": 0.24,
+            "results": 0.2,
+            "second_result": 0.2,
+        },
+        {
+            "id": 0.0,
+            "equal": 0,
+            "paid": True,
+            "name": "A",
+            "renamedmeasurement": "[0.1, 0.1, 0.1]",
+            "expectation": 0.12,
+            "results": 0.1,
+            "second_result": 0.1,
+        },
+        {
+            "id": 2.0,
+            "equal": 0,
+            "paid": True,
+            "name": "C",
+            "renamedmeasurement": "[0.3, 0.3, 0.3]",
+            "expectation": 0.36,
+            "results": 0.3,
+            "second_result": 0.3,
+        },
+        {
+            "id": 3.0,
+            "equal": 0,
+            "paid": False,
+            "name": "D",
+            "renamedmeasurement": "[0.4, 0.4, 0.4]",
+            "expectation": 0.48,
+            "results": 0.4,
+            "second_result": 0.4,
+        },
+        {
+            "id": 4.0,
+            "equal": 0,
+            "paid": True,
+            "name": "E",
+            "renamedmeasurement": "[0.5, 0.5, 0.5]",
+            "expectation": 0.55,
+            "results": 0.5,
+            "second_result": 0.5,
+        },
+        {
+            "id": 5.0,
+            "equal": 0,
+            "paid": False,
+            "name": "F",
+            "renamedmeasurement": "[0.6, 0.6, 0.6]",
+            "expectation": 0.68,
+            "results": 0.6,
+            "second_result": 0.6,
+        },
+        {
+            "id": 6.0,
+            "equal": 0,
+            "paid": True,
+            "name": "G",
+            "renamedmeasurement": "[0.7, 0.7, 0.7]",
+            "expectation": 0.76,
+            "results": 0.7,
+            "second_result": 0.7,
+        },
+        {
+            "id": 7.0,
+            "equal": 0,
+            "paid": False,
+            "name": "H",
+            "renamedmeasurement": "[0.8, 0.8, 0.8]",
+            "expectation": 0.84,
+            "results": 0.8,
+            "second_result": 0.8,
+        },
+        {
+            "id": 8.0,
+            "equal": 0,
+            "paid": True,
+            "name": "I",
+            "renamedmeasurement": "[0.9, 0.9, 0.9]",
+            "expectation": 0.92,
+            "results": 0.9,
+            "second_result": 0.9,
+        },
+        {
+            "id": 9.0,
+            "equal": 0,
+            "paid": False,
+            "name": "Jess",
+            "renamedmeasurement": "[1.0, 1.0, 1.0]",
+            "expectation": 1.0,
+            "results": 1.0,
+            "second_result": 1.0,
+        },
+        {
+            "id": 10.0,
+            "equal": 0,
+            "paid": True,
+            "name": "Karl",
+            "renamedmeasurement": "[1.0, 1.1, 1.2]",
+            "expectation": 0.9,
+            "results": 1.1,
+            "second_result": 1.1,
+        },
+    ]
+
+
+@pytest.mark.pandas
 def test_pandas_comparator():
     delta = PandasComparator(["name"]).compare(old_df(), new_df())
 
@@ -217,17 +431,18 @@ def test_pandas_comparator():
     cols = changes[0].keys()
     assert actual_differences[0].old and actual_differences[0].old.name in cols
     assert actual_differences[0].new and actual_differences[0].new.name in cols
-    expected_df = pd.DataFrame(
+    expected_changes = [
         {
-            "name": ["E"],
-            "expectation_old": [0.5],
-            "expectation": [0.55],
-            "_count": [1],
+            "name": "E",
+            "expectation_old": 0.5,
+            "expectation": 0.55,
+            "_count": 1,
         }
-    )
-    assert_frame_equal(pd.DataFrame(changes), expected_df.reset_index(drop=True))
+    ]
+    rec_approx(changes, expected_changes)
 
 
+@pytest.mark.pandas
 def test_pandas_comparator_row_col_orders():
     test_dfs = [  # (DataFrame, Order <1=RowChanged, 2=ColChanged>)
         (pd.DataFrame({"id": [1, 2], "col": ["a", "b"]}), 0),
@@ -250,12 +465,36 @@ def test_pandas_comparator_row_col_orders():
     "input_type", ["table_str", "schema_table_str", "bracket_table_str", "sa_table"]
 )
 def test_sqlcompyre_comparator(mssql_engine: sa.Engine, input_type: str):
-    first = old_df()
-    first["measurement"] = first["measurement"].apply(str)
-    second = new_df()
-    second["renamedmeasurement"] = second["renamedmeasurement"].apply(str)
-    first.to_sql("first", mssql_engine, index=False, index_label="name", schema="dbo")
-    second.to_sql("second", mssql_engine, index=False, index_label="name", schema="dbo")
+    metadata = sa.MetaData()
+    first_table = sa.Table(
+        "first",
+        metadata,
+        sa.Column("id", sa.BigInteger()),
+        sa.Column("equal", sa.Integer()),
+        sa.Column("paid", sa.String()),
+        sa.Column("unnecessary", sa.BigInteger()),
+        sa.Column("name", sa.String()),
+        sa.Column("measurement", sa.String()),
+        sa.Column("expectation", sa.Float()),
+        schema="dbo",
+    )
+    second_table = sa.Table(
+        "second",
+        metadata,
+        sa.Column("id", sa.Float()),
+        sa.Column("equal", sa.Integer()),
+        sa.Column("paid", sa.Boolean()),
+        sa.Column("name", sa.String()),
+        sa.Column("renamedmeasurement", sa.String()),
+        sa.Column("expectation", sa.Float(24)),
+        sa.Column("results", sa.Float()),
+        sa.Column("second_result", sa.Float(24)),
+        schema="dbo",
+    )
+    metadata.create_all(mssql_engine)
+    with mssql_engine.begin() as conn:
+        conn.execute(sa.insert(first_table), old_df_rows())
+        conn.execute(sa.insert(second_table), new_df_rows())
 
     old: str | sa.Table
     new: str | sa.Table
@@ -350,7 +589,7 @@ def test_sqlcompyre_comparator(mssql_engine: sa.Engine, input_type: str):
             "id": 9.0,
             "equal": 0.0,
             "name": "Jess",
-            "renamedmeasurement": "[np.float64(1.0), np.float64(1.0), np.float64(1.0)]",
+            "renamedmeasurement": "[1.0, 1.0, 1.0]",
             "expectation": 1.0,
         },
     )
@@ -371,7 +610,7 @@ def test_sqlcompyre_comparator(mssql_engine: sa.Engine, input_type: str):
                 "id": 9.0,
                 "equal": 0.0,
                 "name": "J",
-                "measurement": "[np.float64(1.0), np.float64(1.0), np.float64(1.0)]",
+                "measurement": "[1.0, 1.0, 1.0]",
                 "expectation": 1.0,
             }
         ],
@@ -387,17 +626,15 @@ def test_sqlcompyre_comparator(mssql_engine: sa.Engine, input_type: str):
     assert len(diff_values) > 0
     assert actual_differences[0].old.name in diff_values[0].keys()
     assert actual_differences[0].new.name in diff_values[0].keys()
-    expected = pd.DataFrame(
+    expected_diff = [
         {
-            "expectation": [0.55],
-            "expectation_old": [0.5],
-            "_count": [1],
-            "name": ["E"],
+            "expectation": 0.55,
+            "expectation_old": 0.5,
+            "_count": 1,
+            "name": "E",
         }
-    )
-    assert_frame_equal(
-        pd.DataFrame(diff_values), expected.reset_index(drop=True), check_dtype=False
-    )
+    ]
+    rec_approx(diff_values, expected_diff)
 
 
 @pytest.mark.sql
@@ -405,12 +642,36 @@ def test_sqlcompyre_comparator(mssql_engine: sa.Engine, input_type: str):
     "input_type", ["table_str", "schema_table_str", "bracket_table_str", "sa_table"]
 )
 def test_sqlmetadata_comparator(mssql_engine: sa.Engine, input_type: str):
-    first = old_df()
-    first["measurement"] = first["measurement"].apply(str)
-    second = new_df()
-    second["renamedmeasurement"] = second["renamedmeasurement"].apply(str)
-    first.to_sql("first", mssql_engine, index=False, index_label="name")
-    second.to_sql("second", mssql_engine, index=False, index_label="name")
+    metadata = sa.MetaData()
+    first_table = sa.Table(
+        "first",
+        metadata,
+        sa.Column("id", sa.BigInteger()),
+        sa.Column("equal", sa.Integer()),
+        sa.Column("paid", sa.String()),
+        sa.Column("unnecessary", sa.BigInteger()),
+        sa.Column("name", sa.String()),
+        sa.Column("measurement", sa.String()),
+        sa.Column("expectation", sa.Float()),
+        schema="dbo",
+    )
+    second_table = sa.Table(
+        "second",
+        metadata,
+        sa.Column("id", sa.Float()),
+        sa.Column("equal", sa.Integer()),
+        sa.Column("paid", sa.Boolean()),
+        sa.Column("name", sa.String()),
+        sa.Column("renamedmeasurement", sa.String()),
+        sa.Column("expectation", sa.Float(24)),
+        sa.Column("results", sa.Float()),
+        sa.Column("second_result", sa.Float(24)),
+        schema="dbo",
+    )
+    metadata.create_all(mssql_engine)
+    with mssql_engine.begin() as conn:
+        conn.execute(sa.insert(first_table), old_df_rows())
+        conn.execute(sa.insert(second_table), new_df_rows())
 
     old: str | sa.Table
     new: str | sa.Table
@@ -468,22 +729,75 @@ def test_sqlmetadata_comparator(mssql_engine: sa.Engine, input_type: str):
 
 @pytest.mark.sql
 def test_sqlmetadata_comparator_cache(mssql_engine: sa.Engine):
-    first = old_df()
-    second = new_df()
-    first.to_sql("first", mssql_engine, index=False, index_label="name")
-    second.to_sql("second", mssql_engine, index=False, index_label="name")
+    metadata = sa.MetaData()
+    first_table = sa.Table(
+        "first",
+        metadata,
+        sa.Column("id", sa.BigInteger()),
+        sa.Column("equal", sa.Integer()),
+        sa.Column("paid", sa.String()),
+        sa.Column("unnecessary", sa.BigInteger()),
+        sa.Column("name", sa.String()),
+        sa.Column("measurement", sa.String()),
+        sa.Column("expectation", sa.Float()),
+        schema="dbo",
+    )
+    second_table = sa.Table(
+        "second",
+        metadata,
+        sa.Column("id", sa.Float()),
+        sa.Column("equal", sa.Integer()),
+        sa.Column("paid", sa.Boolean()),
+        sa.Column("name", sa.String()),
+        sa.Column("renamedmeasurement", sa.String()),
+        sa.Column("expectation", sa.Float(24)),
+        sa.Column("results", sa.Float()),
+        sa.Column("second_result", sa.Float(24)),
+        schema="dbo",
+    )
+    metadata.create_all(mssql_engine)
+    with mssql_engine.begin() as conn:
+        conn.execute(sa.insert(first_table), old_df_rows())
+        conn.execute(sa.insert(second_table), new_df_rows())
 
     # Create a comparison with activated caching
     cache_comp = SqlMetadataComparator(mssql_engine, cache_db_metadata=True)
     original_delta = cache_comp.compare("first", "second")
 
     # Change (switch) the tables in the database
-    second.to_sql(
-        "first", mssql_engine, index=False, index_label="id", if_exists="replace"
+    first_table.drop(bind=mssql_engine, checkfirst=True)
+    second_table.drop(bind=mssql_engine, checkfirst=True)
+    first_renamed_table = sa.Table(
+        "second",
+        metadata,
+        sa.Column("id", sa.BigInteger()),
+        sa.Column("equal", sa.Integer()),
+        sa.Column("paid", sa.String()),
+        sa.Column("unnecessary", sa.BigInteger()),
+        sa.Column("name", sa.String()),
+        sa.Column("measurement", sa.String()),
+        sa.Column("expectation", sa.Float()),
+        schema="dbo",
+        extend_existing=True,
     )
-    first.to_sql(
-        "second", mssql_engine, index=False, index_label="id", if_exists="replace"
+    second_renamed_table = sa.Table(
+        "first",
+        metadata,
+        sa.Column("id", sa.Float()),
+        sa.Column("equal", sa.Integer()),
+        sa.Column("paid", sa.Boolean()),
+        sa.Column("name", sa.String()),
+        sa.Column("renamedmeasurement", sa.String()),
+        sa.Column("expectation", sa.Float(24)),
+        sa.Column("results", sa.Float()),
+        sa.Column("second_result", sa.Float(24)),
+        schema="dbo",
+        extend_existing=True,
     )
+    metadata.create_all(mssql_engine)
+    with mssql_engine.begin() as conn:
+        conn.execute(sa.insert(first_renamed_table), old_df_rows())
+        conn.execute(sa.insert(second_renamed_table), new_df_rows())
 
     # New comparison should be different
     changed_delta = SqlMetadataComparator(mssql_engine).compare("first", "second")
diff --git a/tests/test_docs_examples.py b/tests/test_docs_examples.py
index 81a7ce8..767b4de 100644
--- a/tests/test_docs_examples.py
+++ b/tests/test_docs_examples.py
@@ -6,7 +6,6 @@
 from typing import Any
 
 import click
-import pandas as pd
 import polars as pl
 import pytest
 import sqlalchemy
@@ -21,6 +20,12 @@
 from pydiverse.pipedag.core.config import create_basic_pipedag_config  # type: ignore
 from pydiverse.pipedag.util.structlog import setup_logging  # type: ignore
 
+try:
+    import pandas as pd
+except ImportError:
+    pass
+
+
 from tabulardelta import (
     DetailedTextFormatter,
     OverviewRowFormatter,
@@ -48,6 +53,7 @@ def mssql_engine() -> Any:
         return "SqlAlchemy or pyodbc not installed."
 
 
+@pytest.mark.pandas
 def test_df_example():
     df_old = df_new = pd.DataFrame()
     # df_old, df_new = ...
@@ -56,6 +62,7 @@ def test_df_example():
     print(DetailedTextFormatter().format(delta))
 
 
+@pytest.mark.pandas
 def test_csv_example():
     assets_path = Path(__file__).parent / "test_assets"
 
@@ -67,6 +74,7 @@ def test_csv_example():
 
 
 @pytest.mark.sql
+@pytest.mark.pandas
 def test_sql_cli_example(mssql_engine: sqlalchemy.Engine):
     @click.command()
     @click.argument("old_table")
@@ -228,6 +236,7 @@ def validate_stage(
 
 
 @pytest.mark.sql
+@pytest.mark.pandas
 def test_pipedag_example():
     url = cached_clean_mssql_container().sqlalchemy_url()
     cfg = create_basic_pipedag_config(url).get("default")
@@ -260,6 +269,7 @@ def compare(self, left: pl.DataFrame, right: pl.DataFrame) -> TabularDelta:
         return comparator.compare(left.to_pandas(), right.to_pandas())
 
 
+@pytest.mark.pandas
 def test_polars_comparator():
     expected = pl.DataFrame({"id": [1, 2, 3]})
     observed = pl.DataFrame({"id": [1, 2, 3, 4], "data_column": [1, 2, 3, 4]})
@@ -316,6 +326,7 @@ def format(delta: TabularDelta) -> None:
             raise AssertionError("\n - ".join(flat_changes))
 
 
+@pytest.mark.pandas
 def test_example():
     expected = pd.DataFrame({"id": [1, 2, 3]})
     # observed = ...
diff --git a/tests/test_formatters.py b/tests/test_formatters.py
index 8b587f8..f3efe21 100644
--- a/tests/test_formatters.py
+++ b/tests/test_formatters.py
@@ -5,12 +5,17 @@
 
 from typing import Any, cast
 
-import numpy as np
-import pandas as pd
-from numpy import (
-    dtype,
-    ndarray,
-)
+import pytest
+
+try:
+    import numpy as np
+    import pandas as pd
+    from numpy import (
+        dtype,
+        ndarray,
+    )
+except ImportError:
+    pass
 
 from tabulardelta import (
     DetailedTextFormatter,
@@ -164,10 +169,12 @@ def gen_change() -> ColumnPair:
     )
 
 
+@pytest.mark.pandas
 def test_random_tabulardelta_smoke():
     print(len(get_random_tabulardelta(np.random.default_rng(42)).rows.unequal))
 
 
+@pytest.mark.pandas
 def test_detailed_text_formatter_smoke(sample_size: int = 100):
     for idx in range(sample_size):
         delta = get_random_tabulardelta(np.random.default_rng(idx))
@@ -181,6 +188,7 @@ def test_detailed_text_formatter_smoke(sample_size: int = 100):
             print(f"Completed {idx}/{sample_size}")
 
 
+@pytest.mark.pandas
 def test_row_formatter_smoke(sample_size: int = 10):
     for idx in range(sample_size):
         gen = np.random.default_rng(idx)

From e143063c63112c57924c9fa5b4dbbcb2d1a7afd6 Mon Sep 17 00:00:00 2001
From: Aaron Tacke <tacke@in.tum.de>
Date: Sat, 14 Jun 2025 08:50:52 +0200
Subject: [PATCH 4/4] introduce dataclasses with and without pandas

---
 docs/index.rst                                |   9 +-
 ...a_dataclasses.py => native_dataclasses.py} |   0
 tabulardelta/comparators/pandas_comparator.py |   4 +-
 .../comparators/pandas_dataclasses.py         | 420 ++++++++++++++++++
 .../comparators/sqlcompyre_comparator.py      |   2 +-
 .../comparators/sqlmetadata_comparator.py     |   2 +-
 tests/test_comparators.py                     |  62 +--
 tests/test_formatters.py                      |   2 +-
 8 files changed, 461 insertions(+), 40 deletions(-)
 rename tabulardelta/comparators/{tabulardelta_dataclasses.py => native_dataclasses.py} (100%)
 create mode 100644 tabulardelta/comparators/pandas_dataclasses.py

diff --git a/docs/index.rst b/docs/index.rst
index b2c8236..84f424a 100644
--- a/docs/index.rst
+++ b/docs/index.rst
@@ -354,7 +354,7 @@ For more details, please have a look at the API reference:
 
    TabularDelta Protocol <api/tabulardelta.tabulardelta>
 
-Comparators using TabularDelta_Dataclasses
+Comparators
 ----------------------------------------------
 
 Comparators can compare two (tabular) data sources and return an object which adheres to the TabularDelta protocol:
@@ -367,9 +367,10 @@ Comparators can compare two (tabular) data sources and return an object which ad
         def compare(self, old: T, new: T) -> TabularDelta: ...
 
 
-All current comparators rely on
-:doc:`tabulardelta_dataclasses.py<api/tabulardelta.comparators.tabulardelta_dataclasses>`
-which implements the TabularDelta protocol using dataclasses.
+SQL-based comparators rely on
+:doc:`tabulardelta_dataclasses.py<api/tabulardelta.comparators.native_dataclasses>`
+while the PandasComparator uses a pandas-specific :doc:`tabulardelta_dataclasses.py<api/tabulardelta.comparators.pandas_dataclasses>`,
+both of which implement the TabularDelta protocol.
 
 These currently implemented Comparators are:
 
diff --git a/tabulardelta/comparators/tabulardelta_dataclasses.py b/tabulardelta/comparators/native_dataclasses.py
similarity index 100%
rename from tabulardelta/comparators/tabulardelta_dataclasses.py
rename to tabulardelta/comparators/native_dataclasses.py
diff --git a/tabulardelta/comparators/pandas_comparator.py b/tabulardelta/comparators/pandas_comparator.py
index c26f0cd..6fcbcc6 100644
--- a/tabulardelta/comparators/pandas_comparator.py
+++ b/tabulardelta/comparators/pandas_comparator.py
@@ -10,7 +10,7 @@
 import numpy as np
 import pandas as pd
 
-from tabulardelta.comparators.tabulardelta_dataclasses import (
+from tabulardelta.comparators.pandas_dataclasses import (
     ColumnPair,
     TabularDelta,
 )
@@ -154,7 +154,7 @@ def _value_change(
     diff.rename(columns={col + suffixes[1]: col}, inplace=True)
     diff["_count"] = 1
     combined = col, old_dt[col], col, new_dt[col], False
-    return ColumnPair.from_str(*combined, incomparable, diff.to_dict("records"))
+    return ColumnPair.from_str(*combined, incomparable, diff)
 
 
 def compare_pandas(
diff --git a/tabulardelta/comparators/pandas_dataclasses.py b/tabulardelta/comparators/pandas_dataclasses.py
new file mode 100644
index 0000000..d0db0c0
--- /dev/null
+++ b/tabulardelta/comparators/pandas_dataclasses.py
@@ -0,0 +1,420 @@
+# Copyright (c) QuantCo 2022-2024
+# SPDX-License-Identifier: LicenseRef-QuantCo
+
+
+from __future__ import annotations
+
+from collections.abc import Iterator
+from dataclasses import dataclass, field
+from functools import cached_property
+from typing import Any
+
+import pandas as pd
+
+try:
+    import sqlalchemy as sa
+except ImportError as e:
+    sa = f"SQLAlchemy not installed: {e}"  # type: ignore
+
+
+@dataclass(frozen=True)
+class Column:
+    """Implements the :class:`Column` protocol for TabularDelta.
+
+    Methods
+    -------
+
+    from_sqlalchemy(column: sa.sql.ColumnElement[Any]) -> Column:
+        Turns SQLAlchemy.Column into TabularDelta.Column
+    """
+
+    name: str
+    """Name of the column."""
+    type: str
+    """Data type of the column."""
+
+    @staticmethod
+    def from_sqlalchemy(column: sa.sql.ColumnElement[Any]) -> Column:
+        """Turns SQLAlchemy.Column into TabularDelta.Column.
+
+        Arguments:
+            column :class:`sa.sql.ColumnElement[Any]`:
+                SQLAlchemy column to be converted.
+
+        Results :class:`Column`:
+            TabularDelta column with according name and type.
+        """
+        return Column(column.name, str(column.type))
+
+
+@dataclass(frozen=True)
+class ChangedValue:
+    """Implements the :class:`ChangedValue` protocol for TabularDelta."""
+
+    example_join_columns: dict[str, Any]
+    """Mapping from column names to values represents an example row where this change
+    occurred."""
+    old: Any
+    """Previous value before the change."""
+    new: Any
+    """New value after the change."""
+    count: int
+    """(Positive) number of rows containing this change."""
+
+
+@dataclass
+class ColumnPair:
+    """Implements the :class:`MatchedColumn` and :class:`ChangedColumn` protocol for
+    TabularDelta.
+
+    Methods
+    -------
+    from_sqlalchemy(...) -> ColumnPair:
+        Creates TabularDelta.ColumnPair using SQLAlchemy columns
+    from_str(...) -> ColumnPair:
+        Creates TabularDelta.ColumnPair using column names and types
+    __len__() -> int
+        Total number of changes
+    __iter__() -> Iterator[ChangedValue]
+        Examples of value changes
+    """
+
+    _old: Column | None = None
+    """Metadata of column in the old table or None if column was added."""
+    _new: Column | None = None
+    """Metadata of column in the new table or None if column was removed."""
+    join: bool = False
+    """Whether column was used as join column for comparison."""
+    incomparable: bool = False
+    """Whether data types of column in old and new table are incomparable."""
+
+    _values: pd.DataFrame | None = None
+
+    @property
+    def old(self) -> Column:
+        """The column in the old table.
+
+        Fails if column was added.
+        """
+        if self._old is None:
+            raise ValueError("Old column does not exist.")
+        return self._old
+
+    @property
+    def new(self) -> Column:
+        """The column in the new table.
+
+        Fails if column was removed.
+        """
+        if self._new is None:
+            raise ValueError("New column does not exist.")
+        return self._new
+
+    def __iter__(self) -> Iterator[ChangedValue]:
+        """Examples of value changes."""
+        for idx, row in self._values.iterrows() if self._values is not None else []:
+            index = {k: v for k, v in row.to_dict().items() if k not in self._required}
+            yield ChangedValue(index, *[row[key] for key in self._required])
+
+    def __len__(self) -> int:
+        """Total number of changes."""
+        return self._values["_count"].sum() if self._values is not None else 0
+
+    @staticmethod
+    def from_sqlalchemy(
+        old: sa.sql.ColumnElement[Any] | None = None,
+        new: sa.sql.ColumnElement[Any] | None = None,
+        join: bool = False,
+        incomparable: bool = False,
+        _values: pd.DataFrame | None = None,
+    ) -> ColumnPair:
+        """Creates TabularDelta.ColumnPair using SQLAlchemy columns.
+
+        Arguments:
+            old :class:`sa.sql.ColumnElement[Any]` | :code:`None`:
+                Column in the old table or None if column was added.
+            new :class:`sa.sql.ColumnElement[Any]` | :code:`None`:
+                Column in the new table or None if column was removed.
+            join :class:`bool`:
+                Whether column was used as join column for comparison.
+            incomparable :class:`bool`:
+                Whether data types of column in old and new table are incomparable.
+            _values :class:`pd.DataFrame`:
+                DataFrame with examples of value changes.
+                Contains old column, new column, :code:`_count` column,
+                and optionally other columns for identifying example rows.
+
+        Returns :class:`ColumnPair`:
+            TabularDelta.ColumnPair with according metadata and values.
+        """
+        return ColumnPair(
+            Column.from_sqlalchemy(old) if old is not None else None,
+            Column.from_sqlalchemy(new) if new is not None else None,
+            join,
+            incomparable,
+            _values,
+        )
+
+    @staticmethod
+    def from_str(
+        old: str | None = None,
+        old_type: str | None = None,
+        new: str | None = None,
+        new_type: str | None = None,
+        join: bool = False,
+        incomparable: bool = False,
+        _values: pd.DataFrame | None = None,
+    ) -> ColumnPair:
+        """Creates TabularDelta.ColumnPair using column names and types.
+
+        Arguments:
+            old :class:`str` | :code:`None`:
+                Column name in the old table or None if column was added.
+            old_type :class:`str` | :code:`None`:
+                Column type in the old table or None if column was added.
+            new :class:`str` | :code:`None`:
+                Column name in the new table or None if column was removed.
+            new_type :class:`str` | :code:`None`:
+                Column type in the new table or None if column was removed.
+            join :class:`bool`:
+                Whether column was used as join column for comparison.
+            incomparable :class:`bool`:
+                Whether data types of column in old and new table are incomparable.
+            _values :class:`pd.DataFrame`:
+                DataFrame with examples of value changes.
+                Contains old column, new column, :code:`_count` column,
+                and optionally other columns for identifying example rows.
+                If the column wasn't renamed, the name of the old column in the DataFrame should
+                be suffixed by :code:`_old`.
+
+        Returns :class:`ColumnPair`:
+            TabularDelta.ColumnPair with according metadata and values.
+        """
+        return ColumnPair(
+            Column(old, old_type) if old and old_type else None,
+            Column(new, new_type) if new and new_type else None,
+            join,
+            incomparable,
+            _values,
+        )
+
+    @cached_property
+    def _df_old_name(self) -> str:
+        """Name of the old column in the DataFrame.
+
+        Suffixed with :code:`_old` if column wasn't renamed.
+        """
+        return self.old.name + ("_old" if self.old.name == self.new.name else "")
+
+    @cached_property
+    def _required(self) -> tuple[str, str, str]:
+        """Required columns in the DataFrame."""
+        return self._df_old_name, self.new.name, "_count"
+
+    def __post_init__(self):
+        """Check if DataFrame contains required columns and compactifies it."""
+        if self._values is None:
+            return
+
+        if missing := set(self._required) - set(self._values.columns):
+            raise ValueError(f"Missing columns in comparison: {missing}")
+
+        group_by_cols = [self._df_old_name, self.new.name]
+
+        # DIRTY FIX FOR PANDAS BUG: Categorical in GroupBy leads to
+        # ValueError: Length of values (5) does not match length of index (25)
+        for col in group_by_cols:
+            if self._values[col].dtype.name == "category":
+                self._values[col] = self._values[col].astype("object")
+
+        # Compactify dataframe by grouping equal changes together
+        groupby = self._values.groupby(group_by_cols, as_index=False, dropna=False)
+        join_cols = {c: (c, "first") for c in set(self._values) - set(self._required)}
+        agg = groupby.agg(_count=("_count", "sum"), **join_cols)  # type: ignore
+        sort = agg.sort_values(by="_count", ascending=False)
+        actual_changes = ~sort[self._df_old_name].isna() | ~sort[self.new.name].isna()
+        self._values = sort[actual_changes]
+
+
+@dataclass(frozen=True)
+class ColumnDelta:
+    """Implements the :class:`ColumnDelta` protocol."""
+
+    cols: list[ColumnPair]
+    """All (potentially matched) columns of both tables.
+
+    Unmatched columns have None on other side.
+    """
+
+    @cached_property
+    def old(self) -> list[Column]:
+        """Metadata of columns in the old table."""
+        return [col.old for col in self.cols if col._old]
+
+    @cached_property
+    def new(self) -> list[Column]:
+        """Metadata of columns in the new table."""
+        return [col.new for col in self.cols if col._new]
+
+    @cached_property
+    def added(self) -> list[Column]:
+        """Metadata of added columns (only in new table)."""
+        return [col.new for col in self.cols if col._new and not col._old]
+
+    @cached_property
+    def removed(self) -> list[Column]:
+        """Metadata of removed columns (only in old table)."""
+        return [col.old for col in self.cols if col._old and not col._new]
+
+    @cached_property
+    def joined(self) -> list[ColumnPair]:
+        """Columns used to join the old and new table."""
+        return [col for col in self.cols if col.join]
+
+    @cached_property
+    def matched(self) -> list[ColumnPair]:
+        """Matched columns (exist in both tables)."""
+        return [col for col in self.cols if col._old and col._new]
+
+    @cached_property
+    def renamed(self) -> list[ColumnPair]:
+        """Renamed columns (matched using values and types)."""
+        return [col for col in self.matched if col.old.name != col.new.name]
+
+    @cached_property
+    def _type_changed(self) -> list[ColumnPair]:
+        """Columns with changed data types."""
+        return [col for col in self.matched if col.old.type != col.new.type]
+
+    @cached_property
+    def comparable_type_changed(self) -> list[ColumnPair]:
+        """Columns with changed but comparable data types."""
+        return [col for col in self._type_changed if not col.incomparable]
+
+    @cached_property
+    def incomparable_type_changed(self) -> list[ColumnPair]:
+        """Columns with changed and incomparable data types."""
+        return [col for col in self._type_changed if col.incomparable]
+
+    @cached_property
+    def differences(self) -> list[ColumnPair]:
+        """Comparable column with changed values."""
+        return [col for col in self.cols if not col.incomparable and len(col) > 0]
+
+
+@dataclass
+class Rows:
+    """Implements the :class:`Rows` protocol."""
+
+    count: int
+    """Number of represented rows."""
+    examples: list[dict[str, Any]] | None
+    """Optional examples of represented rows."""
+
+    def __len__(self) -> int:
+        """Number of represented rows."""
+        return self.count
+
+    def __iter__(self) -> Iterator[dict[str, Any]]:
+        """Examples of represented rows."""
+        return iter(self.examples or [])
+
+
+@dataclass(frozen=True)
+class RowDelta:
+    """Implements the :class:`RowDelta` protocol."""
+
+    old: Rows
+    """Rows in the old table."""
+    new: Rows
+    """Rows in the new table."""
+    added: Rows
+    """Added rows (only in new table)."""
+    removed: Rows
+    """Removed rows (only in old table)."""
+    equal: Rows
+    """Equal rows (joined and all columns unchanged)."""
+    unequal: Rows
+    """Unequal rows (joined but at least one column changed)."""
+
+
+@dataclass(frozen=True)
+class TabularDelta:
+    """Implements the :class:`TabularDelta` protocol.
+
+    Methods
+    -------
+
+    from_errors(errors: list[str], name: str = "") -> TabularDelta:
+        Default TabularDelta containing errors
+    """
+
+    name: str = ""
+    """Name of the new table and therefore the comparison."""
+    old_name: str | None = None
+    """Optional name of the old table."""
+    info: list[str] = field(default_factory=list)
+    """Additional information collected during the comparison."""
+    warnings: list[str] = field(default_factory=list)
+    """Warnings collected during the comparison."""
+    errors: list[str] = field(default_factory=list)
+    """Errors collected during the comparison."""
+
+    _columns: list[ColumnPair] = field(default_factory=list)
+    """All (potentially matched) columns of both tables.
+
+    Unmatched columns have None on other side.
+    """
+
+    _old_rows: int = 0
+    """Number of rows in the old table."""
+    _new_rows: int = 0
+    """Number of rows in the new table."""
+    _added_rows: int = 0
+    """Number of added rows (only in new table)."""
+    _removed_rows: int = 0
+    """Number of removed rows (only in old table)."""
+    _equal_rows: int = 0
+    """Number of equal rows (joined and all columns unchanged)."""
+    _unequal_rows: int = 0
+    """Number of unequal rows (joined but at least one column changed)."""
+    _example_added_rows: list[dict[str, Any]] = field(default_factory=list)
+    """Optional examples of added rows (only in new table)."""
+    _example_removed_rows: list[dict[str, Any]] = field(default_factory=list)
+    """Optional examples of removed rows (only in old table)."""
+    _example_equal_rows: list[dict[str, Any]] = field(default_factory=list)
+    """Optional examples of equal rows (joined and all columns unchanged)."""
+    _example_unequal_rows: list[dict[str, Any]] = field(default_factory=list)
+    """Optional examples of unequal rows (joined but at least one column changed)."""
+
+    @cached_property
+    def cols(self) -> ColumnDelta:
+        """Returns :class:`ColumnDelta` implementation."""
+        return ColumnDelta(self._columns)
+
+    @cached_property
+    def rows(self) -> RowDelta:
+        """Returns :class:`RowDelta` implementation."""
+        return RowDelta(
+            Rows(self._old_rows, None),
+            Rows(self._new_rows, None),
+            Rows(self._added_rows, self._example_added_rows),
+            Rows(self._removed_rows, self._example_removed_rows),
+            Rows(self._equal_rows, self._example_equal_rows),
+            Rows(self._unequal_rows, self._example_unequal_rows),
+        )
+
+    @staticmethod
+    def from_errors(errors: list[str], name: str = "") -> TabularDelta:
+        """Creates default TabularDelta object with errors.
+
+        Arguments:
+            errors :class:`list[str]`:
+                List of error messages.
+            name :class:`str`:
+                Name of the table.
+
+        Returns :class:`TabularDelta`:
+            TabularDelta object containing errors.
+        """
+        return TabularDelta(name=name, errors=errors)
diff --git a/tabulardelta/comparators/sqlcompyre_comparator.py b/tabulardelta/comparators/sqlcompyre_comparator.py
index d830a98..761d11c 100644
--- a/tabulardelta/comparators/sqlcompyre_comparator.py
+++ b/tabulardelta/comparators/sqlcompyre_comparator.py
@@ -11,7 +11,7 @@
 import sqlcompyre as sc
 from sqlcompyre.analysis import TableComparison
 
-from tabulardelta.comparators.tabulardelta_dataclasses import (
+from tabulardelta.comparators.native_dataclasses import (
     ColumnPair,
     TabularDelta,
 )
diff --git a/tabulardelta/comparators/sqlmetadata_comparator.py b/tabulardelta/comparators/sqlmetadata_comparator.py
index 96fc5a6..5031cdf 100644
--- a/tabulardelta/comparators/sqlmetadata_comparator.py
+++ b/tabulardelta/comparators/sqlmetadata_comparator.py
@@ -9,7 +9,7 @@
 
 import sqlalchemy as sa
 
-from tabulardelta.comparators.tabulardelta_dataclasses import (
+from tabulardelta.comparators.native_dataclasses import (
     Column,
     ColumnPair,
     TabularDelta,
diff --git a/tests/test_comparators.py b/tests/test_comparators.py
index fed5a54..db71456 100644
--- a/tests/test_comparators.py
+++ b/tests/test_comparators.py
@@ -3,14 +3,16 @@
 from typing import Any, NamedTuple
 
 import pytest
+from pandas.testing import assert_frame_equal
 
+import tabulardelta.comparators.pandas_dataclasses as pd_dc
 from tabulardelta import (
     DetailedTextFormatter,
     PandasComparator,
     SqlCompyreComparator,
     SqlMetadataComparator,
 )
-from tabulardelta.comparators.tabulardelta_dataclasses import (
+from tabulardelta.comparators.native_dataclasses import (
     Column,
     ColumnPair,
 )
@@ -321,23 +323,25 @@ def test_pandas_comparator():
     assert delta.warnings == []
     assert delta.errors == []
     assert delta.cols.joined == [
-        ColumnPair(Column("name", "object"), Column("name", "object"), join=True)
+        pd_dc.ColumnPair(
+            pd_dc.Column("name", "object"), pd_dc.Column("name", "object"), join=True
+        )
     ]
-    assert delta.cols.removed == [Column("unnecessary", "int64")]
+    assert delta.cols.removed == [pd_dc.Column("unnecessary", "int64")]
     assert set(delta.cols.added) == {
-        Column("results", "float64"),
-        Column("second_result", "float32"),
+        pd_dc.Column("results", "float64"),
+        pd_dc.Column("second_result", "float32"),
     }
     assert delta.cols.renamed == [
-        ColumnPair(
-            Column("measurement", "object"),
-            Column("renamedmeasurement", "object"),
+        pd_dc.ColumnPair(
+            pd_dc.Column("measurement", "object"),
+            pd_dc.Column("renamedmeasurement", "object"),
         )
     ]
     comparable = [chg for chg in delta.cols.comparable_type_changed]
     assert len(comparable) == 1
-    assert comparable[0].old == Column("expectation", "float64")
-    assert comparable[0].new == Column("expectation", "float32")
+    assert comparable[0].old == pd_dc.Column("expectation", "float64")
+    assert comparable[0].new == pd_dc.Column("expectation", "float32")
     assert all(chg.old and chg.new for chg in delta.cols.incomparable_type_changed)
     incomparable_dtype_dict = {
         chg.new.name: (
@@ -354,9 +358,8 @@ def test_pandas_comparator():
     assert "paid" in incomparable_dtype_dict
     assert incomparable_dtype_dict["paid"][2] == "object"
     assert incomparable_dtype_dict["paid"][3] == "bool"
-    assert incomparable_dtype_dict["paid"][4] is not None
-    assert len(incomparable_dtype_dict["paid"][4]) > 0
-    cols = incomparable_dtype_dict["paid"][4][0].keys()
+    assert isinstance(incomparable_dtype_dict["paid"][4], pd.DataFrame)
+    cols = incomparable_dtype_dict["paid"][4].columns
     assert "name" in cols
     assert "_count" in cols
     assert incomparable_dtype_dict["paid"][0] in cols
@@ -365,13 +368,12 @@ def test_pandas_comparator():
     assert "id" in incomparable_dtype_dict
     assert incomparable_dtype_dict["id"][2] == "int64"
     assert incomparable_dtype_dict["id"][3] == "float64"
-    assert incomparable_dtype_dict["id"][4] is not None
-    assert len(incomparable_dtype_dict["id"][4]) > 0
-    cols = incomparable_dtype_dict["id"][4][0].keys()
+    assert isinstance(incomparable_dtype_dict["id"][4], pd.DataFrame)
+    cols = incomparable_dtype_dict["id"][4].columns
     assert "name" in cols
     assert "_count" in cols
-    assert incomparable_dtype_dict["id"][0] in cols
-    assert incomparable_dtype_dict["id"][1] in cols
+    assert incomparable_dtype_dict["id"][0] in incomparable_dtype_dict["id"][4].columns
+    assert incomparable_dtype_dict["id"][1] in incomparable_dtype_dict["id"][4].columns
 
     assert len(delta.rows.old) == 10
     assert len(delta.rows.new) == 11
@@ -425,21 +427,19 @@ def test_pandas_comparator():
     actual_differences = [diff for diff in delta.cols.differences if len(diff) > 0]
     assert len(actual_differences) == 1
     assert actual_differences[0].new and actual_differences[0].new.name == "expectation"
-    changes = actual_differences[0]._values
-    assert changes is not None
-    assert len(changes) > 0
-    cols = changes[0].keys()
-    assert actual_differences[0].old and actual_differences[0].old.name in cols
-    assert actual_differences[0].new and actual_differences[0].new.name in cols
-    expected_changes = [
+    df = actual_differences[0]._values
+    assert df is not None
+    assert actual_differences[0].old and actual_differences[0].old.name in df.columns
+    assert actual_differences[0].new and actual_differences[0].new.name in df.columns
+    expected_df = pd.DataFrame(
         {
-            "name": "E",
-            "expectation_old": 0.5,
-            "expectation": 0.55,
-            "_count": 1,
+            "expectation_old": [0.5],
+            "expectation": [0.55],
+            "_count": [1],
+            "name": ["E"],
         }
-    ]
-    rec_approx(changes, expected_changes)
+    )
+    assert_frame_equal(df.reset_index(drop=True), expected_df.reset_index(drop=True))
 
 
 @pytest.mark.pandas
diff --git a/tests/test_formatters.py b/tests/test_formatters.py
index f3efe21..809e567 100644
--- a/tests/test_formatters.py
+++ b/tests/test_formatters.py
@@ -21,7 +21,7 @@
     DetailedTextFormatter,
     OverviewRowFormatter,
 )
-from tabulardelta.comparators.tabulardelta_dataclasses import (
+from tabulardelta.comparators.native_dataclasses import (
     Column,
     ColumnPair,
     TabularDelta,