diff --git a/pandas/core/arrays/datetimes.py b/pandas/core/arrays/datetimes.py
index 70df708d36b3b..732f819e743a4 100644
--- a/pandas/core/arrays/datetimes.py
+++ b/pandas/core/arrays/datetimes.py
@@ -1063,6 +1063,7 @@ def tz_localize(self, tz, ambiguous="raise", nonexistent="raise", errors=None):
 
         Be careful with DST changes. When there is sequential data, pandas can
         infer the DST time:
+
         >>> s = pd.to_datetime(pd.Series(['2018-10-28 01:30:00',
         ...                               '2018-10-28 02:00:00',
         ...                               '2018-10-28 02:30:00',
@@ -1094,6 +1095,7 @@ def tz_localize(self, tz, ambiguous="raise", nonexistent="raise", errors=None):
         If the DST transition causes nonexistent times, you can shift these
         dates forward or backwards with a timedelta object or `'shift_forward'`
         or `'shift_backwards'`.
+
         >>> s = pd.to_datetime(pd.Series(['2015-03-29 02:30:00',
         ...                               '2015-03-29 03:30:00']))
         >>> s.dt.tz_localize('Europe/Warsaw', nonexistent='shift_forward')