pandas: powerful Python data analysis toolkit, Release 0.25.3 Join SQL style merges. See the Database style joining section. In [77]: left = pd.DataFrame({'key': ['foo', 'foo'], 'lval': [1, 2]}) In found within pandas tests. Well read the data into a DataFrame called tips and assume we have a database table of the same name and structure. In [3]: url = ('https://raw.github.com/pandas-dev' ...: DataFrame({'key': ['B', 'D', 'D', 'E'], ....: 'value': np.random.randn(4)}) ....: Assume we have two database tables of the same name and structure as our DataFrames. Now lets go over the various types of

objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 463 17.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 472 enhancements: • Added the ability to specify the SQL type of columns when writing a DataFrame to a database (GH8778). For example, specifying to use the sqlalchemy String type instead of the default Text cut/qcut when using Series and retbins=True (GH8589) • Bug in writing Categorical columns to an SQL database with to_sql (GH8624). • Bug in comparing Categorical of datetime raising when being compared to

objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 453 17.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 462 cut/qcut when using Series and retbins=True (GH8589) • Bug in writing Categorical columns to an SQL database with to_sql (GH8624). • Bug in comparing Categorical of datetime raising when being compared to values with to_sql (GH2754). • Added support for writing datetime64 columns with to_sql for all database flavors (GH7103). 1.2.2 Backwards incompatible API changes Breaking changes API changes related

objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 547 18.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 558 io functions now accept a SQLAlchemy connectable. (GH7877) • pd.read_sql and to_sql can accept database URI as con parameter (GH10214) • read_sql_table will now allow reading from views (GH10750). • enhancements: • Added the ability to specify the SQL type of columns when writing a DataFrame to a database (GH8778). For example, specifying to use the sqlalchemy String type instead of the default Text

objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 377 14.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 386 containing the pivoted data. 1.1.5 SQL The SQL reading and writing functions now support more database flavors through SQLAlchemy (GH2717, GH4163, GH5950, GH6292). All databases supported by SQLAlchemy wrapper around the other two and will delegate to specific function depending on the provided input (database table name or sql query). In practice, you have to provide a SQLAlchemy engine to the sql functions

Appending rows to a DataFrame . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 688 18.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 689 io functions now accept a SQLAlchemy connectable. (GH7877) • pd.read_sql and to_sql can accept database URI as con parameter (GH10214) • read_sql_table will now allow reading from views (GH10750). • enhancements: • Added the ability to specify the SQL type of columns when writing a DataFrame to a database (GH8778). For example, specifying to use the sqlalchemy String type instead of the default Text

Appending rows to a DataFrame . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 690 18.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 691 io functions now accept a SQLAlchemy connectable. (GH7877) • pd.read_sql and to_sql can accept database URI as con parameter (GH10214) • read_sql_table will now allow reading from views (GH10750). • enhancements: • Added the ability to specify the SQL type of columns when writing a DataFrame to a database (GH8778). For example, specifying to use the sqlalchemy String type instead of the default Text

Appending rows to a DataFrame . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 770 17.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 771 io functions now accept a SQLAlchemy connectable. (GH7877) • pd.read_sql and to_sql can accept database URI as con parameter (GH10214) • read_sql_table will now allow reading from views (GH10750). • enhancements: • Added the ability to specify the SQL type of columns when writing a DataFrame to a database (GH8778). For example, specifying to use the sqlalchemy String type instead of the default Text

Appending rows to a DataFrame . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 766 17.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 767 io functions now accept a SQLAlchemy connectable. (GH7877) • pd.read_sql and to_sql can accept database URI as con parameter (GH10214) • read_sql_table will now allow reading from views (GH10750). • enhancements: • Added the ability to specify the SQL type of columns when writing a DataFrame to a database (GH8778). For example, specifying to use the sqlalchemy String type instead of the default Text

Appending rows to a DataFrame . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 800 17.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 801 io functions now accept a SQLAlchemy connectable. (GH7877) • pd.read_sql and to_sql can accept database URI as con parameter (GH10214) • read_sql_table will now allow reading from views (GH10750). • enhancements: • Added the ability to specify the SQL type of columns when writing a DataFrame to a database (GH8778). For example, specifying to use the sqlalchemy String type instead of the default Text