8.0 Google Big Query access psycopg2 PostgreSQL engine for sqlalchemy pyarrow 0.9.0 Parquet and feather reading / writing pymysql 0.7.11 MySQL engine for sqlalchemy pyreadstat SPSS files (.sav) reading 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' ...:

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 Text type for string columns: from sqlalchemy.types import String data.to_sql(’data_dtype’, engine, dtype={’Col_1’: String}) • Series.all and Series.any now support the level and skipna parameters (GH8302):

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 read_sql_table and to_sql (GH7441, GH7952). For example: df.to_sql(’table’, engine, schema=’other_schema’) pd.read_sql_table(’table’, engine, schema=’other_schema’) • Added support for writing NaN values with

objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 377 14.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 386 specified with delim_whitespace=True in read_csv()/read_table() (GH6607) • Raise ValueError when engine=’c’ specified with unsupported options in read_csv()/read_table() (GH6607) • Raise ValueError when 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 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 547 18.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 558 arcsinh, arctanh, abs and arctan2. These functions map to the intrinsics for the NumExpr engine. For the Python engine, they are mapped to NumPy calls. Changes to Excel with MultiIndex In version 0.16.2 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 chunk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1021 24.1.24 Specifying the parser engine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1022 24.1.25 Reading remote files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1095 24.10.9 Engine connection examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1096 24.10

Appending rows to a DataFrame . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 690 18.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 691 chunk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 924 25.1.22 Specifying the parser engine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 925 25.1.23 Writing out Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 992 25.9.9 Engine connection examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 993 25.9

Appending rows to a DataFrame . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 766 17.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 767 chunk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1017 24.1.24 Specifying the parser engine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1018 24.1.25 Reading remote files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1094 24.10.9 Engine connection examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1095 24.10

Appending rows to a DataFrame . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 688 18.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 689 chunk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 922 25.1.22 Specifying the parser engine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 923 25.1.23 Writing out Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 989 25.9.9 Engine connection examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 991 25.9

Appending rows to a DataFrame . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 800 17.2 Database-style DataFrame joining/merging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 801 chunk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1056 24.1.24 Specifying the parser engine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1057 24.1.25 Reading remote files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1130 24.11.9 Engine connection examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1131 24.11