BUG: complex Series/DataFrame display all complex nans as nan+0j (pandas-dev#53844)

* BUG: complex Series/DataFrame display all complex nans as nan+0j

* resolve mypy via type: ignore[arg-type]

Author: Charlie-XIAO

pandas/io/formats/format.py

@@ -1492,6 +1492,35 @@ def format_with_na_rep(values: ArrayLike, formatter: Callable, na_rep: str):
             ).reshape(values.shape)
             return formatted
 
+        def format_complex_with_na_rep(
+            values: ArrayLike, formatter: Callable, na_rep: str
+        ):
+            real_values = np.real(values).ravel()  # type: ignore[arg-type]
+            imag_values = np.imag(values).ravel()  # type: ignore[arg-type]
+            real_mask, imag_mask = isna(real_values), isna(imag_values)
+            formatted_lst = []
+            for val, real_val, imag_val, re_isna, im_isna in zip(
+                values.ravel(),
+                real_values,
+                imag_values,
+                real_mask,
+                imag_mask,
+            ):
+                if not re_isna and not im_isna:
+                    formatted_lst.append(formatter(val))
+                elif not re_isna:  # xxx+nanj
+                    formatted_lst.append(f"{formatter(real_val)}+{na_rep}j")
+                elif not im_isna:  # nan[+/-]xxxj
+                    # The imaginary part may either start with a "-" or a space
+                    imag_formatted = formatter(imag_val).strip()
+                    if imag_formatted.startswith("-"):
+                        formatted_lst.append(f"{na_rep}{imag_formatted}j")
+                    else:
+                        formatted_lst.append(f"{na_rep}+{imag_formatted}j")
+                else:  # nan+nanj
+                    formatted_lst.append(f"{na_rep}+{na_rep}j")
+            return np.array(formatted_lst).reshape(values.shape)
+
         if self.formatter is not None:
             return format_with_na_rep(self.values, self.formatter, self.na_rep)
 
@@ -1512,11 +1541,12 @@ def format_values_with(float_format):
             # need to distinguish complex and float NaNs (GH #53762)
             values = self.values
             is_complex = is_complex_dtype(values)
-            if is_complex:
-                na_rep = f"{na_rep}+{0:.{self.digits}f}j"
 
             # separate the wheat from the chaff
-            values = format_with_na_rep(values, formatter, na_rep)
+            if is_complex:
+                values = format_complex_with_na_rep(values, formatter, na_rep)
+            else:
+                values = format_with_na_rep(values, formatter, na_rep)
 
             if self.fixed_width:
                 if is_complex:
@@ -1917,7 +1947,7 @@ def _trim_zeros_complex(str_complexes: np.ndarray, decimal: str = ".") -> list[s
     real_part, imag_part = [], []
     for x in str_complexes:
         # Complex numbers are represented as "(-)xxx(+/-)xxxj"
-        # The split will give [maybe "-", "xxx", "+/-", "xxx", "j", ""]
+        # The split will give [{"", "-"}, "xxx", "+/-", "xxx", "j", ""]
         # Therefore, the imaginary part is the 4th and 3rd last elements,
         # and the real part is everything before the imaginary part
         trimmed = re.split(r"([j+-])", x)
@@ -1929,11 +1959,13 @@ def _trim_zeros_complex(str_complexes: np.ndarray, decimal: str = ".") -> list[s
     # in the array
     n = len(str_complexes)
     padded_parts = _trim_zeros_float(real_part + imag_part, decimal)
+    padded_length = max(len(part) for part in padded_parts) - 1
     padded = [
-        padded_parts[i]  # real part (including - or space, possibly "NaN")
-        + padded_parts[i + n]  # imaginary part (including + or -)
+        real_pt  # real part, possibly NaN
+        + imag_pt[0]  # +/-
+        + f"{imag_pt[1:]:>{padded_length}}"  # complex part (no sign), possibly nan
         + "j"
-        for i in range(n)
+        for real_pt, imag_pt in zip(padded_parts[:n], padded_parts[n:])
     ]
     return padded
 

pandas/tests/io/formats/test_printing.py

@@ -218,11 +218,23 @@ def test_multiindex_long_element():
         ([-2, complex("nan"), -1], ["-2.0+0.0j", " NaN+0.0j", "-1.0+0.0j"]),
         ([-1.23j, complex("nan"), -1], ["-0.00-1.23j", "  NaN+0.00j", "-1.00+0.00j"]),
         ([1.23j, complex("nan"), 1.23], [" 0.00+1.23j", "  NaN+0.00j", " 1.23+0.00j"]),
+        (
+            [-1.23j, complex(np.nan, np.nan), 1],
+            ["-0.00-1.23j", "  NaN+ NaNj", " 1.00+0.00j"],
+        ),
+        (
+            [-1.23j, complex(1.2, np.nan), 1],
+            ["-0.00-1.23j", " 1.20+ NaNj", " 1.00+0.00j"],
+        ),
+        (
+            [-1.23j, complex(np.nan, -1.2), 1],
+            ["-0.00-1.23j", "  NaN-1.20j", " 1.00+0.00j"],
+        ),
     ],
 )
 @pytest.mark.parametrize("as_frame", [True, False])
 def test_ser_df_with_complex_nans(data, output, as_frame):
-    # GH#53762
+    # GH#53762, GH#53841
     obj = pd.Series(data)
     if as_frame:
         obj = obj.to_frame(name="val")