sion Notes SciPy 1.7.1 Miscellaneous statistical functions numba 0.53.1 Alternative execution engine for rolling operations (see Enhancing Perfor- mance) xarray 0.19.0 pandas-like API for N-dimensional 4.16 SQL support for databases other than sqlite psycopg2 2.8.6 PostgreSQL engine for sqlalchemy pymysql 1.0.2 MySQL engine for sqlalchemy Other data sources Dependency Minimum Version Notes PyTables ase.py:3794, in Index.get_loc(self, key, method,␣ ˓→tolerance) 3793 try: -> 3794 return self._engine.get_loc(casted_key) 3795 except KeyError as err: File /pandas/pandas/_libs/index.pyx:138, in pandas

users should pay close attention to. 1.4.1 File parsing new features The delimited file parsing engine (the guts of read_csv and read_table) has been rewritten from the ground up and now uses a fraction both simple axis indexing and multi-level / hierarchical axis indexing • An integrated group by engine for aggregating and transforming data sets • Date range generation (date_range) and custom date can extract some data into a DataFrame. In the following example, we use the SQlite SQL database engine. You can use a temporary SQLite database where data are stored in “memory”. Just do: import sqlite3

users should pay close attention to. 1.6.1 File parsing new features The delimited file parsing engine (the guts of read_csv and read_table) has been rewritten from the ground up and now uses a fraction both simple axis indexing and multi-level / hierarchical axis indexing • An integrated group by engine for aggregating and transforming data sets • Date range generation (date_range) and custom date default Excel writer engine for ’xls’ files. Available options: ’xlwt’ (the default). io.excel.xlsm.writer: [default: openpyxl] [currently: openpyxl] : string The default Excel writer engine for ’xlsm’ files

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 a SQLAlchemy engine to the sql functions. To connect with SQLAlchemy you use the create_engine() function to create an engine object from database URI. You only need to create the engine once per database Release 0.14.0 In [43]: from sqlalchemy import create_engine # Create your connection. In [44]: engine = create_engine(’sqlite:///:memory:’) This engine can then be used to write or read data to/from this

sion Notes SciPy 1.4.1 Miscellaneous statistical functions numba 0.50.1 Alternative execution engine for rolling operations (see Enhancing Perfor- mance) xarray 0.15.1 pandas-like API for N-dimensional 4.0 SQL support for databases other than sqlite psycopg2 2.8.4 PostgreSQL engine for sqlalchemy pymysql 0.10.1 MySQL engine for sqlalchemy Other data sources Dependency Minimum Version Notes PyTables \t for read_table()] Delimiter to use. If sep is None, the C engine cannot automatically detect the separator, but the Python parsing engine can, meaning the latter will be used and automatically detect

default 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 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 now has a keyword parameter float_precision which specifies which floating-point converter the C engine should use during parsing, see here (GH8002, GH8044) • Added searchsorted method to Series objects

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 now has a keyword parameter float_precision which specifies which floating-point converter the C engine should use during parsing, see here (GH8002, GH8044) • Added searchsorted method to Series objects method engine keyword now recognizes openpyxl1 and openpyxl2 which will explicitly require openpyxl v1 and v2 respectively, failing if the requested version is not available. The openpyxl engine is a now

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 resets name from its result, but retains in result’s Index. (GH10150) • Bug in pd.eval using numexpr engine coerces 1 element numpy array to scalar (GH10546) • Bug in pd.concat with axis=0 when column is Bug in indexing with a PeriodIndex on an object with a PeriodIndex (GH4125) • Bug in read_csv with engine=’c’: EOF preceded by a comment, blank line, etc. was not handled correctly (GH10728, GH10548) •

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 (GH16637) 1.1.1.3 I/O • Bug in read_csv() in which files weren’t opened as binary files by the C engine on Windows, causing EOF characters mid-field, which would fail (GH16039, GH16559, GH16675) • Bug

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 • Bug in DataFrame.update() with overwrite=False and NaN values (GH15593) • Passing an invalid engine to read_csv() now raises an informative ValueError rather than UnboundLocalError. (GH16511) • Bug