objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 257 13.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 266 same name and • timezone instead of an array (GH2563) 1.3.2 New features • MySQL support for database (contribution from Dan Allan) 1.3.3 HDFStore You may need to upgrade your existing data files 1.11.1 New features • Add to_clipboard function to pandas namespace for writing objects to the system clipboard (GH774) • Add itertuples method to DataFrame for iterating through the rows of a dataframe

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 rolling mean mode (mean=True) so that the calculated weighted means (e.g. ‘triang’, ‘gaussian’) are distributed about the same means as those calculated without weighting (i.e. ‘boxcar’). See the note on normalization

Appending rows to a DataFrame . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 688 18.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 689 (GH11302) • Series.sort_index() now correctly handles the inplace option (GH11402) • Incorrectly distributed .c file in the build on PyPi when reading a csv of floats and passing na_values= would 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). •

Appending rows to a DataFrame . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 690 18.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 691 (GH11302) • Series.sort_index() now correctly handles the inplace option (GH11402) • Incorrectly distributed .c file in the build on PyPi when reading a csv of floats and passing na_values= would 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). •

Appending rows to a DataFrame . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 770 17.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 771 (GH11302) • Series.sort_index() now correctly handles the inplace option (GH11402) • Incorrectly distributed .c file in the build on PyPi when reading a csv of floats and passing na_values= would 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). •

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

Appending rows to a DataFrame . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 766 17.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 767 (GH11302) • Series.sort_index() now correctly handles the inplace option (GH11402) • Incorrectly distributed .c file in the build on PyPi when reading a csv of floats and passing na_values= would 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). •

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

objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 341 14.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 350 Google’s BigQuery Data Sets by way of pandas DataFrames. BigQuery is a high performance SQL-like database service, useful for performing ad-hoc queries against extremely large datasets. See the docs 1 pandas: powerful Python data analysis toolkit, Release 0.13.1 1.5.2 New features • MySQL support for database (contribution from Dan Allan) 1.5.3 HDFStore You may need to upgrade your existing data files