objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 11.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 package providing fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive. It aims to be the fundamental high-level building block 1.2.1 New features • New unified merge function for efficiently performing full gamut of database / relational-algebra operations. Refactored existing join methods to use the new infrastructure, resulting

objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 11.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 package providing fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive. It aims to be the fundamental high-level building block 1.3.1 New features • New unified merge function for efficiently performing full gamut of database / relational-algebra operations. Refactored existing join methods to use the new infrastructure, resulting

objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 11.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 package providing fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive. It aims to be the fundamental high-level building block 1.4.1 New features • New unified merge function for efficiently performing full gamut of database / relational-algebra operations. Refactored existing join methods to use the new infrastructure, resulting

objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 257 13.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 266 package providing fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive. It aims to be the fundamental high-level building block 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

package providing fast, flexible, and expressive data structures designed to make working with relational or labeled data both easy and intuitive. It aims to be the fundamental high-level building block combining together Series and DataFrame objects with various kinds of set logic for the indexes and relational algebra functionality in the case of join / merge-type operations. See the Merging section. Concatenating 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

objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 377 14.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 386 package providing fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive. It aims to be the fundamental high-level building block 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

objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 341 14.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 350 package providing fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive. It aims to be the fundamental high-level building block 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

objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 463 17.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 472 package providing fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive. It aims to be the fundamental high-level building block 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 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 453 17.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 462 package providing fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive. It aims to be the fundamental high-level building block 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 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 547 18.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 558 package providing fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive. It aims to be the fundamental high-level building block 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). •