read_csv(StringIO(lines), index_col=0, parse_dates=True)[::-1] 136 /Library/Frameworks/EPD64.framework/Versions/7.3/lib/python2.7/urllib.pyc in urlopen(url, data, proxies) 84 opener = _urlopener 85 return opener.open(url) 87 else: 88 return opener.open(url, data) /Library/Frameworks/EPD64.framework/Versions/7.3/lib/python2.7/urllib.pyc in open(self, fullurl, data) 205 try: 206 if data is None: getattr(self, name)(url) 208 else: 209 return getattr(self, name)(url, data) /Library/Frameworks/EPD64.framework/Versions/7.3/lib/python2.7/urllib.pyc in open_http(self, url, data) 342 if realhost: h.putheader(’Host’

23 version of cython to avoid problems with character encodings (GH14699) • Switched the test framework to use pytest (GH13097) • Reorganization of tests directory layout (GH14854, GH15707). 1.3.4 Deprecations All databases supported by SQLAlchemy can be used, such as PostgreSQL, MySQL, Oracle, Microsoft SQL server (see documentation of SQLAlchemy on included dialects). The functionality of providing DBAPI connection Going forward, we are moving to a more functional style using the pytest framework, which offers a richer testing framework that will facilitate testing and developing. Thus, instead of writing test

23 version of cython to avoid problems with character encodings (GH14699) • Switched the test framework to use pytest (GH13097) • Reorganization of tests directory layout (GH14854, GH15707). 1.2.4 Deprecations All databases supported by SQLAlchemy can be used, such as PostgreSQL, MySQL, Oracle, Microsoft SQL server (see documentation of SQLAlchemy on included dialects). The functionality of providing DBAPI connection Going forward, we are moving to a more functional style using the pytest framework, which offers a richer testing framework that will facilitate testing and developing. Thus, instead of writing test

23 version of cython to avoid problems with character encodings (GH14699) • Switched the test framework to use pytest (GH13097) • Reorganization of tests directory layout (GH14854, GH15707). 1.5.4 Deprecations All databases supported by SQLAlchemy can be used, such as PostgreSQL, MySQL, Oracle, Microsoft SQL server (see documentation of SQLAlchemy on included dialects). The functionality of providing DBAPI connection Going forward, we are moving to a more functional style using the pytest framework, which offers a richer testing framework that will facilitate testing and developing. Thus, instead of writing test

from a filelike handle Modifying formatting in XlsxWriter output HTML Reading HTML tables from a server that cannot handle the default request header HDFStore The HDFStores docs Simple queries with account private key in JSON format. Can be file path or string contents. This is useful for remote server authentication (eg. Jupyter/IPython notebook on remote host). verbose [None, deprecated] Deprecated account private key in JSON format. Can be file path or string contents. This is useful for remote server authentication (eg. Jupyter/IPython notebook on remote host). See also: pandas_gbq.to_gbq This

pandas: powerful Python data analysis toolkit, Release 0.25.1 HTML Reading HTML tables from a server that cannot handle the default request header HDFStore The HDFStores docs Simple queries with account private key in JSON format. Can be file path or string contents. This is useful for remote server authentication (eg. Jupyter/IPython notebook on remote host). verbose [None, deprecated] Deprecated account private key in JSON format. Can be file path or string contents. This is useful for remote server authentication (eg. Jupyter/IPython notebook on remote host). See also: pandas_gbq.to_gbq This

from a filelike handle Modifying formatting in XlsxWriter output HTML Reading HTML tables from a server that cannot handle the default request header HDFStore The HDFStores docs Simple Queries with account private key in JSON format. Can be file path or string contents. This is useful for remote server authentication (eg. Jupyter/IPython notebook on remote host). verbose [None, deprecated] Deprecated account private key in JSON format. Can be file path or string contents. This is useful for remote server authentication (eg. Jupyter/IPython notebook on remote host). See also: pandas_gbq.to_gbq This

All databases supported by SQLAlchemy can be used, such as PostgreSQL, MySQL, Oracle, Microsoft SQL server (see documentation of SQLAlchemy on included dialects). The functionality of providing DBAPI connection supports both python2 and python3. Note: The asv benchmark suite was translated from the previous framework, vbench, so many stylistic issues are likely a result of automated transformation of the code. from a filelike handle Modifying formatting in XlsxWriter output HTML Reading HTML tables from a server that cannot handle the default request header HDFStore The HDFStores docs Simple Queries with

All databases supported by SQLAlchemy can be used, such as PostgreSQL, MySQL, Oracle, Microsoft SQL server (see documentation of SQLAlchemy on included dialects). The functionality of providing DBAPI connection supports both python2 and python3. Note: The asv benchmark suite was translated from the previous framework, vbench, so many stylistic issues are likely a result of automated transformation of the code. from a filelike handle Modifying formatting in XlsxWriter output HTML Reading HTML tables from a server that cannot handle the default request header HDFStore The HDFStores docs Simple Queries with

Using the tips dataset again, let’s find the average gratuity by size of the party and sex of the server. In Excel, we use the following configuration for the PivotTable: The equivalent in pandas: In output Loading only visible sheets GH19842#issuecomment-892150745 HTML Reading HTML tables from a server that cannot handle the default request header 1026 Chapter 2. User Guide pandas: powerful Python test_cool_feature_aspect(self): pass We prefer a more functional style using the pytest framework, which offers a richer testing framework that will facilitate testing and developing. Thus, instead of writing test