Backport PR pandas-dev#40850: REGR: object column repr not respecting float format

Author: mzeitlin11

doc/source/whatsnew/v1.2.4.rst

@@ -20,7 +20,7 @@ Fixed regressions
 - Fixed regression in (in)equality comparison of ``pd.NaT`` with a non-datetimelike numpy array returning a scalar instead of an array (:issue:`40722`)
 - Fixed regression in :meth:`DataFrame.where` not returning a copy in the case of an all True condition (:issue:`39595`)
 - Fixed regression in :meth:`DataFrame.replace` raising ``IndexError`` when ``regex`` was a multi-key dictionary (:issue:`39338`)
--
+- Fixed regression in repr of floats in an ``object`` column not respecting ``float_format`` when printed in the console or outputted through :meth:`DataFrame.to_string`, :meth:`DataFrame.to_html`, and :meth:`DataFrame.to_latex` (:issue:`40024`)
 
 .. ---------------------------------------------------------------------------
 

pandas/io/formats/format.py

@@ -1254,7 +1254,9 @@ def _format_strings(self) -> List[str]:
             float_format = get_option("display.float_format")
             if float_format is None:
                 precision = get_option("display.precision")
-                float_format = lambda x: f"{x: .{precision:d}f}"
+                float_format = lambda x: _trim_zeros_single_float(
+                    f"{x: .{precision:d}f}"
+                )
         else:
             float_format = self.float_format
 
@@ -1305,7 +1307,7 @@ def _format(x):
             if not is_float_type[i] and leading_space:
                 fmt_values.append(f" {_format(v)}")
             elif is_float_type[i]:
-                fmt_values.append(_trim_zeros_single_float(float_format(v)))
+                fmt_values.append(float_format(v))
             else:
                 if leading_space is False:
                     # False specifically, so that the default is

pandas/tests/io/formats/test_format.py

@@ -2021,6 +2021,21 @@ def test_repr_str_float_truncation(self, data, expected):
         result = repr(series)
         assert result == expected
 
+    @pytest.mark.parametrize(
+        "float_format,expected",
+        [
+            ("{:,.0f}".format, "0   1,000\n1    test\ndtype: object"),
+            ("{:.4f}".format, "0   1000.0000\n1        test\ndtype: object"),
+        ],
+    )
+    def test_repr_float_format_in_object_col(self, float_format, expected):
+        # GH#40024
+        df = Series([1000.0, "test"])
+        with option_context("display.float_format", float_format):
+            result = repr(df)
+
+        assert result == expected
+
     def test_dict_entries(self):
         df = DataFrame({"A": [{"a": 1, "b": 2}]})
 

pandas/tests/io/formats/test_to_html.py

@@ -878,3 +878,29 @@ def test_to_html_na_rep_and_float_format(na_rep):
   </tbody>
 </table>"""
     assert result == expected
+
+
+def test_to_html_float_format_object_col():
+    # GH#40024
+    df = DataFrame(data={"x": [1000.0, "test"]})
+    result = df.to_html(float_format=lambda x: f"{x:,.0f}")
+    expected = """<table border="1" class="dataframe">
+  <thead>
+    <tr style="text-align: right;">
+      <th></th>
+      <th>x</th>
+    </tr>
+  </thead>
+  <tbody>
+    <tr>
+      <th>0</th>
+      <td>1,000</td>
+    </tr>
+    <tr>
+      <th>1</th>
+      <td>test</td>
+    </tr>
+  </tbody>
+</table>"""
+
+    assert result == expected

pandas/tests/io/formats/test_to_latex.py

@@ -121,6 +121,24 @@ def test_to_latex_column_format(self):
         )
         assert result == expected
 
+    def test_to_latex_float_format_object_col(self):
+        # GH#40024
+        ser = Series([1000.0, "test"])
+        result = ser.to_latex(float_format="{:,.0f}".format)
+        expected = _dedent(
+            r"""
+            \begin{tabular}{ll}
+            \toprule
+            {} &     0 \\
+            \midrule
+            0 & 1,000 \\
+            1 &  test \\
+            \bottomrule
+            \end{tabular}
+            """
+        )
+        assert result == expected
+
     def test_to_latex_empty_tabular(self):
         df = DataFrame()
         result = df.to_latex()