clean up merge

Author: Matt Roeschke

doc/source/io.rst

@@ -4959,7 +4959,36 @@ default ``Text`` type for string columns:
  Because of this, reading the database table back in does **not** generate
  a categorical.
 
-<<<<<<< HEAD
+.. _io.sql_datetime_data:
+
+Datetime data types
+'''''''''''''''''''
+
+Using SQLAlchemy, :func:`~pandas.DataFrame.to_sql` is capable of writing
+datetime data that is timezone naive or timezone aware. However, the resulting
+data stored in the database ultimately depends on the supported data type
+for datetime data of the database system being used.
+
+The following table lists supported data types for datetime data for some
+common databases. Other database dialects may have different data types for
+datetime data.
+
+=========== ============================================= ===================
+Database SQL Datetime Types Timezone Support
+=========== ============================================= ===================
+SQLite ``TEXT`` No
+MySQL ``TIMESTAMP`` or ``DATETIME`` No
+PostgreSQL ``TIMESTAMP`` or ``TIMESTAMP WITH TIME ZONE`` Yes
+=========== ============================================= ===================
+
+When writing timezone aware data to databases that do not support timezones,
+the data will be written as timezone naive timestamps that are in local time
+with respect to the timezone.
+
+:func:`~pandas.read_sql_table` is also capable of reading datetime data that is
+timezone aware or naive. When reading ``TIMESTAMP WITH TIME ZONE`` types, pandas
+will convert the data to UTC.
+
 .. _io.sql.method:
 
 Insertion Method
@@ -5008,38 +5037,6 @@ Example of a callable using PostgreSQL `COPY clause
  table_name, columns)
  cur.copy_expert(sql=sql, file=s_buf)
 
-=======
-.. _io.sql_datetime_data:
-
-Datetime data types
-'''''''''''''''''''
-
-Using SQLAlchemy, :func:`~pandas.DataFrame.to_sql` is capable of writing
-datetime data that is timezone naive or timezone aware. However, the resulting
-data stored in the database ultimately depends on the supported data type
-for datetime data of the database system being used.
-
-The following table lists supported data types for datetime data for some
-common databases. Other database dialects may have different data types for
-datetime data.
-
-=========== ============================================= ===================
-Database SQL Datetime Types Timezone Support
-=========== ============================================= ===================
-SQLite ``TEXT`` No
-MySQL ``TIMESTAMP`` or ``DATETIME`` No
-PostgreSQL ``TIMESTAMP`` or ``TIMESTAMP WITH TIME ZONE`` Yes
-=========== ============================================= ===================
-
-When writing timezone aware data to databases that do not support timezones,
-the data will be written as timezone naive timestamps that are in local time
-with respect to the timezone.
-
-:func:`~pandas.read_sql_table` is also capable of reading datetime data that is
-timezone aware or naive. When reading ``TIMESTAMP WITH TIME ZONE`` types, pandas
-will convert the data to UTC.
->>>>>>> upstream/master
-
 Reading Tables
 ''''''''''''''
 

doc/source/whatsnew/v0.24.0.rst

@@ -331,12 +331,7 @@ Other Enhancements
 
 - :func:`to_datetime` now supports the ``%Z`` and ``%z`` directive when passed into ``format`` (:issue:`13486`)
 - :func:`Series.mode` and :func:`DataFrame.mode` now support the ``dropna`` parameter which can be used to specify whether ``NaN``/``NaT`` values should be considered (:issue:`17534`)
-<<<<<<< HEAD:doc/source/whatsnew/v0.24.0.txt
-- :func:`to_csv` now supports ``compression`` keyword when a file handle is passed. (:issue:`21227`)
-- :func:`~pandas.DataFrame.to_sql` add parameter ``method`` to control SQL insertion clause (:8953:)
-=======
 - :func:`DataFrame.to_csv` and :func:`Series.to_csv` now support the ``compression`` keyword when a file handle is passed. (:issue:`21227`)
->>>>>>> upstream/master:doc/source/whatsnew/v0.24.0.rst
 - :meth:`Index.droplevel` is now implemented also for flat indexes, for compatibility with :class:`MultiIndex` (:issue:`21115`)
 - :meth:`Series.droplevel` and :meth:`DataFrame.droplevel` are now implemented (:issue:`20342`)
 - Added support for reading from/writing to Google Cloud Storage via the ``gcsfs`` library (:issue:`19454`, :issue:`23094`)
@@ -378,6 +373,7 @@ Other Enhancements
 - :meth:`DataFrame.between_time` and :meth:`DataFrame.at_time` have gained the an ``axis`` parameter (:issue:`8839`)
 - The ``scatter_matrix``, ``andrews_curves``, ``parallel_coordinates``, ``lag_plot``, ``autocorrelation_plot``, ``bootstrap_plot``, and ``radviz`` plots from the ``pandas.plotting`` module are now accessible from calling :meth:`DataFrame.plot` (:issue:`11978`)
 - :class:`IntervalIndex` has gained the :attr:`~IntervalIndex.is_overlapping` attribute to indicate if the ``IntervalIndex`` contains any overlapping intervals (:issue:`23309`)
+- :func:`pandas.DataFrame.to_sql` has gained the ``method`` argument to control SQL insertion clause (:issue:`8953`)
 
 .. _whatsnew_0240.api_breaking: