📝 add example of reading csv file with mixed formats

Author: MarcoGorelli

doc/source/user_guide/io.rst

@@ -1023,7 +1023,14 @@ format.
    df
 
 In the case that you have mixed datetime formats within the same column, you'll need to
-first read it in the file, and then apply :func:`to_datetime` to each element.
+first read it in as an object dtype and then apply :func:`to_datetime` to each element.
+
+.. ipython:: python
+
+   data = io.StringIO("date\n12 Jan 2000\n2000-01-13\n")
+   df = pd.read_csv(data)
+   df['date'] = df['date'].apply(pd.to_datetime)
+   df
 
 .. ipython:: python
    :suppress:

doc/source/whatsnew/v2.0.0.rst

@@ -118,7 +118,7 @@ Datetimes are now parsed with a consistent format
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 :func:`to_datetime` now parses dates with a consistent format, which is guessed from the first non-NA value
-(unless ``format`` is specified). Previously, it would've guessed the format for each element individually.
+(unless ``format`` is specified). Previously, it would have guessed the format for each element individually.
 
 *Old behavior*:
 

pandas/_libs/tslibs/parsing.pyx

@@ -1117,13 +1117,13 @@ cdef void _maybe_warn_about_dayfirst(format: str, bint dayfirst):
         if (day_index > month_index) and dayfirst:
             warnings.warn(
                 f"Parsing dates in {format} format when dayfirst=True was specified. "
-                f"Pass `dayfirst=False` or specify a format to silence this warning.",
+                "Pass `dayfirst=False` or specify a format to silence this warning.",
                 stacklevel=find_stack_level(),
             )
         if (day_index < month_index) and not dayfirst:
             warnings.warn(
                 f"Parsing dates in {format} format when dayfirst=False was specified. "
-                f"Pass `dayfirst=True` or specify a format to silence this warning.",
+                "Pass `dayfirst=True` or specify a format to silence this warning.",
                 stacklevel=find_stack_level(),
             )