BUG: Fix to_csv microsecond inconsistency (#62111)

doc/source/whatsnew/v3.0.0.rst

@@ -953,6 +953,7 @@ I/O
 - Bug in :meth:`DataFrame._repr_html_` which ignored the ``"display.float_format"`` option (:issue:`59876`)
 - Bug in :meth:`DataFrame.from_records` ignoring ``columns`` and ``index`` parameters when ``data`` is an empty iterator and ``nrows=0``. (:issue:`61140`)
 - Bug in :meth:`DataFrame.from_records` where ``columns`` parameter with numpy structured array was not reordering and filtering out the columns (:issue:`59717`)
+- Bug in :meth:`DataFrame.to_csv` / :meth:`Series.to_csv` formatting tz-aware datetimes (microseconds dropped, offset lacked colon); now consistently emits ``YYYY-MM-DD HH:MM:SS.ffffff+HH:MM`` when ``date_format=None``. (:issue:`62111`)
 - Bug in :meth:`DataFrame.to_dict` raises unnecessary ``UserWarning`` when columns are not unique and ``orient='tight'``. (:issue:`58281`)
 - Bug in :meth:`DataFrame.to_excel` when writing empty :class:`DataFrame` with :class:`MultiIndex` on both axes (:issue:`57696`)
 - Bug in :meth:`DataFrame.to_excel` where the :class:`MultiIndex` index with a period level was not a date (:issue:`60099`)

pandas/io/formats/csvs.py

@@ -11,6 +11,7 @@
     Sequence,
 )
 import csv as csvlib
+from datetime import datetime as _pydatetime
 import os
 from typing import (
     TYPE_CHECKING,
@@ -24,6 +25,8 @@
 from pandas._typing import SequenceNotStr
 from pandas.util._decorators import cache_readonly
 
+from pandas.core.dtypes.common import is_object_dtype
+from pandas.core.dtypes.dtypes import DatetimeTZDtype
 from pandas.core.dtypes.generic import (
     ABCDatetimeIndex,
     ABCIndex,
@@ -47,6 +50,8 @@
         npt,
     )
 
+    from pandas.core.series import Series
+
     from pandas.io.formats.format import DataFrameFormatter
 
 
@@ -312,11 +317,64 @@ def _save_body(self) -> None:
                 break
             self._save_chunk(start_i, end_i)
 
+    # tz-aware CSV formatting helper
+    @staticmethod
+    def _csv_format_datetime_tz_ea(ser: Series, na_rep: str) -> Series:
+        """
+        Consistent tz-aware formatting for ExtensionArray datetimes:
+        'YYYY-MM-DD HH:MM:SS.ffffff+HH:MM'
+        """
+        # +HHMM → +HH:MM
+        s = ser.dt.strftime("%Y-%m-%d %H:%M:%S.%f%z")
+        s = s.str.replace(r"([+-]\d{2})(\d{2})$", r"\1:\2", regex=True)
+        return s.fillna(na_rep)
+
+    # tz-aware CSV formatting helper
+    @staticmethod
+    def _csv_format_py_tz_aware_obj(ser: Series, na_rep: str) -> Series:
+        """
+        For object-dtype Series containing stdlib tz-aware datetimes, render
+        with microseconds and colonized offset. Leave other objects untouched.
+        """
+        if ser.empty:
+            return ser.astype(str)
+
+        vals = ser.to_numpy(object, copy=False)
+
+        def _is_tzaware_dt(x: object) -> bool:
+            if not isinstance(x, _pydatetime):
+                return False
+            tz = getattr(x, "tzinfo", None)
+            return tz is not None and tz.utcoffset(x) is not None
+
+        mask = np.fromiter(
+            (_is_tzaware_dt(x) for x in vals), dtype=bool, count=len(vals)
+        )
+        if mask.any():
+            out = vals.copy()
+            # isoformat gives 'YYYY-MM-DD HH:MM:SS.ffffff+HH:MM'
+            out[mask] = [
+                x.isoformat(sep=" ", timespec="microseconds") for x in out[mask]
+            ]
+            ser = ser._constructor(out, index=ser.index, name=ser.name)
+
+        return ser.fillna(na_rep)
+
     def _save_chunk(self, start_i: int, end_i: int) -> None:
         # create the data for a chunk
         slicer = slice(start_i, end_i)
         df = self.obj.iloc[slicer]
 
+        # If user didn't set date_format, normalize tz-aware datetimes to a
+        # single canonical string form for CSV (GH 62111).
+        if self.date_format is None:
+            for col in df.columns:
+                col_dtype = df.dtypes[col]
+                if isinstance(col_dtype, DatetimeTZDtype):
+                    df[col] = self._csv_format_datetime_tz_ea(df[col], self.na_rep)
+                elif is_object_dtype(col_dtype):
+                    df[col] = self._csv_format_py_tz_aware_obj(df[col], self.na_rep)
+
         res = df._get_values_for_csv(**self._number_format)
         data = list(res._iter_column_arrays())
 

pandas/tests/io/formats/test_to_csv.py

@@ -1,3 +1,8 @@
+from datetime import (
+    datetime,
+    timedelta,
+    timezone,
+)
 import io
 import os
 import sys
@@ -712,6 +717,102 @@ def test_to_csv_encoding_binary_handle(self, mode):
                 handle.seek(0)
                 assert handle.read().startswith(b'\xef\xbb\xbf""')
 
+    """
+    tz-aware timestamps with/without microseconds should be written consistently
+    Checks if the .ffffff format is consistent, even when microseconds==0
+
+    GH 62111
+    """
+
+    def test_to_csv_tz_aware_consistent_microseconds_formatting_python_datetime(self):
+        df = DataFrame(
+            {
+                "timestamp": [
+                    datetime(2025, 8, 14, 12, 34, 56, 0, tzinfo=timezone.utc),
+                    datetime(2025, 8, 14, 12, 34, 56, 1, tzinfo=timezone.utc),
+                ]
+            }
+        )
+        with tm.ensure_clean("test.csv") as path:
+            df.to_csv(path, index=False, lineterminator="\n")
+            with open(path, encoding="utf-8") as f:
+                contents = f.read()
+
+        expected = (
+            "timestamp\n"
+            "2025-08-14 12:34:56.000000+00:00\n"
+            "2025-08-14 12:34:56.000001+00:00\n"
+        )
+        assert contents == expected
+
+    def test_to_csv_tz_aware_consistent_microseconds_formatting_timestamp(self):
+        df = DataFrame(
+            {
+                "timestamp": [
+                    pd.Timestamp("2025-08-14 12:34:56+00:00"),
+                    pd.Timestamp("2025-08-14 12:34:56.000001+00:00"),
+                ]
+            }
+        )
+        with tm.ensure_clean("test.csv") as path:
+            df.to_csv(path, index=False, lineterminator="\n")
+            with open(path, encoding="utf-8") as f:
+                contents = f.read()
+
+        expected = (
+            "timestamp\n"
+            "2025-08-14 12:34:56.000000+00:00\n"
+            "2025-08-14 12:34:56.000001+00:00\n"
+        )
+        assert contents == expected
+
+    def test_to_csv_tz_aware_respects_date_format_python_datetime(self):
+        # No microseconds in date_format; %z produces +0000 (no colon) by design.
+        df = DataFrame(
+            {
+                "timestamp": [
+                    datetime(2025, 8, 14, 12, 34, 56, 0, tzinfo=timezone.utc),
+                    datetime(2025, 8, 14, 12, 34, 56, 1, tzinfo=timezone.utc),
+                ]
+            }
+        )
+        with tm.ensure_clean("test.csv") as path:
+            df.to_csv(
+                path,
+                index=False,
+                lineterminator="\n",
+                date_format="%Y-%m-%d %H:%M:%S%z",
+            )
+            with open(path, encoding="utf-8") as f:
+                contents = f.read()
+
+        expected = "timestamp\n2025-08-14 12:34:56+0000\n2025-08-14 12:34:56+0000\n"
+        assert contents == expected
+
+    def test_to_csv_tz_aware_consistent_microseconds_non_utc_offset_python_datetime(
+        self,
+    ):
+        am_tz = timezone(timedelta(hours=4))  # +04:00 (Armenia / Asia/Yerevan)
+        df = DataFrame(
+            {
+                "timestamp": [
+                    datetime(2025, 8, 14, 12, 34, 56, 0, tzinfo=am_tz),
+                    datetime(2025, 8, 14, 12, 34, 56, 1, tzinfo=am_tz),
+                ]
+            }
+        )
+        with tm.ensure_clean("test.csv") as path:
+            df.to_csv(path, index=False, lineterminator="\n")
+            with open(path, encoding="utf-8") as f:
+                contents = f.read()
+
+        expected = (
+            "timestamp\n"
+            "2025-08-14 12:34:56.000000+04:00\n"
+            "2025-08-14 12:34:56.000001+04:00\n"
+        )
+        assert contents == expected
+
 
 def test_to_csv_iterative_compression_name(compression):
     # GH 38714