BUG: float-like string, trailing 0 truncation

doc/source/whatsnew/v1.2.1.rst

@@ -15,6 +15,7 @@ including other versions of pandas.
 Fixed regressions
 ~~~~~~~~~~~~~~~~~
 - The deprecated attributes ``_AXIS_NAMES`` and ``_AXIS_NUMBERS`` of :class:`DataFrame` and :class:`Series` will no longer show up in ``dir`` or ``inspect.getmembers`` calls (:issue:`38740`)
+- Bug in float-like strings having trailing 0's truncated (:issue:`38708`)
 -
 
 .. ---------------------------------------------------------------------------

pandas/io/formats/format.py

@@ -1310,7 +1310,9 @@ def _format(x):
                     tpl = " {v}"
                 fmt_values.append(tpl.format(v=_format(v)))
 
-        fmt_values = _trim_zeros_float(str_floats=fmt_values, decimal=".")
+        fmt_values = _trim_zeros_float(
+            str_floats=fmt_values, decimal=".", is_float_type=is_float_type
+        )
 
         return fmt_values
 
@@ -1828,35 +1830,44 @@ def _trim_zeros_complex(str_complexes: np.ndarray, decimal: str = ".") -> List[s
 
 
 def _trim_zeros_float(
-    str_floats: Union[np.ndarray, List[str]], decimal: str = "."
+    str_floats: Union[np.ndarray, List[str]],
+    decimal: str = ".",
+    is_float_type: Optional[np.ndarray] = None,
 ) -> List[str]:
     """
     Trims zeros, leaving just one before the decimal points if need be.
     """
     trimmed = str_floats
     number_regex = re.compile(fr"^\s*[\+-]?[0-9]+\{decimal}[0-9]*$")
+    float_locs = (
+        is_float_type
+        if is_float_type is not None
+        else np.ones(len(trimmed), dtype=bool)
+    )
 
-    def is_number_with_decimal(x):
-        return re.match(number_regex, x) is not None
+    def is_number_with_decimal(x, i):
+        return re.match(number_regex, x) is not None and float_locs[i]
 
     def should_trim(values: Union[np.ndarray, List[str]]) -> bool:
         """
         Determine if an array of strings should be trimmed.
 
         Returns True if all numbers containing decimals (defined by the
-        above regular expression) within the array end in a zero, otherwise
-        returns False.
+        above regular expression and the specification of float locations
+        `float_locs`) within the array end in a zero, otherwise returns False.
         """
-        numbers = [x for x in values if is_number_with_decimal(x)]
+        numbers = [x for i, x in enumerate(values) if is_number_with_decimal(x, i)]
         return len(numbers) > 0 and all(x.endswith("0") for x in numbers)
 
     while should_trim(trimmed):
-        trimmed = [x[:-1] if is_number_with_decimal(x) else x for x in trimmed]
+        trimmed = [
+            x[:-1] if is_number_with_decimal(x, i) else x for i, x in enumerate(trimmed)
+        ]
 
     # leave one 0 after the decimal points if need be.
     result = [
-        x + "0" if is_number_with_decimal(x) and x.endswith(decimal) else x
-        for x in trimmed
+        x + "0" if is_number_with_decimal(x, i) and x.endswith(decimal) else x
+        for i, x in enumerate(trimmed)
     ]
     return result
 

pandas/tests/series/test_repr.py

@@ -237,6 +237,18 @@ def test_series_repr_nat(self):
         )
         assert result == expected
 
+    def test_series_repr_float_like_object_no_truncate(self):
+        series = Series(["3.50"])
+        result = repr(series)
+        expected = "0    3.50\ndtype: object"
+        assert result == expected
+
+    def test_mixed_series_repr_float_like_object_no_truncate(self):
+        series = Series([1.20, "1.00"])
+        result = repr(series)
+        expected = "0     1.2\n1    1.00\ndtype: object"
+        assert result == expected
+
 
 class TestCategoricalRepr:
     def test_categorical_repr_unicode(self):