loc[tips['tip'] <= 9] {{ header }} 3.5.3 Comparison with SAS For potential users coming from SAS this page is meant to demonstrate how different SAS operations would be performed in pandas. If youre new DataFrame. This is often used in interactive work (e.g. Jupyter notebook or terminal) - the equivalent in SAS would be: proc print data=df(obs=5); run; 150 Chapter 3. Getting started pandas: powerful Python terminology translation pandas SAS DataFrame data set column variable row observation groupby BY-group NaN . DataFrame / Series A DataFrame in pandas is analogous to a SAS data set - a two-dimensional

Representation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150 1.10.1.12 pd.read_sas() changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150 1.10.1.13 Other enhancements Frequency Enhancement . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179 1.12.1.6 Support for SAS XPORT files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179 1.12.1.7 Support for Math Categorical Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1135 24.14 SAS Formats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Representation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 1.8.1.12 pd.read_sas() changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 1.8.1.13 Other enhancements Frequency Enhancement . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150 1.10.1.6 Support for SAS XPORT files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150 1.10.1.7 Support for Math Categorical Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1100 24.13 SAS Formats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Representation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 1.7.1.12 pd.read_sas() changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 1.7.1.13 Other enhancements Frequency Enhancement . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148 1.9.1.6 Support for SAS XPORT files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149 1.9.1.7 Support for Math Categorical Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1098 24.13 SAS Formats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Representation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 pd.read_sas() changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 Other enhancements Frequency Enhancement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 Support for SAS XPORT files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 Support for Math Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1002 25.12 SAS Formats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Representation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 pd.read_sas() changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 Other enhancements Frequency Enhancement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 Support for SAS XPORT files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 Support for Math Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1000 25.12 SAS Formats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

loc[tips['tip'] <= 9] {{ header }} 2.6.3 Comparison with SAS For potential users coming from SAS this page is meant to demonstrate how different SAS operations would be performed in pandas. If you’re new DataFrame. This is often used in interactive work (e.g. Jupyter notebook or terminal) - the equivalent in SAS would be: proc print data=df(obs=5); run; 188 Chapter 2. Getting started pandas: powerful Python terminology translation pandas SAS DataFrame data set column variable row observation groupby BY-group NaN . DataFrame / Series A DataFrame in pandas is analogous to a SAS data set - a two-dimensional

loc[tips['tip'] <= 9] {{ header }} 3.5.3 Comparison with SAS For potential users coming from SAS this page is meant to demonstrate how different SAS operations would be performed in pandas. If you’re new DataFrame. This is often used in interactive work (e.g. Jupyter notebook or terminal) - the equivalent in SAS would be: 3.5. Comparison with other tools 181 pandas: powerful Python data analysis toolkit, Release terminology translation pandas SAS DataFrame data set column variable row observation groupby BY-group NaN . DataFrame / Series A DataFrame in pandas is analogous to a SAS data set - a two-dimensional

loc[tips['tip'] <= 9] {{ header }} 3.5.3 Comparison with SAS For potential users coming from SAS this page is meant to demonstrate how different SAS operations would be performed in pandas. If you’re new DataFrame. This is often used in interactive work (e.g. Jupyter notebook or terminal) - the equivalent in SAS would be: proc print data=df(obs=5); run; 3.5. Comparison with other tools 181 pandas: powerful terminology translation pandas SAS DataFrame data set column variable row observation groupby BY-group NaN . DataFrame / Series A DataFrame in pandas is analogous to a SAS data set - a two-dimensional

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 847 24.13 SAS Format . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 921 33 Comparison with SAS 923 33.1 Data Structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . benchmarking with the Air Speed Velocity library (GH8361) • Support for reading SAS xport files, see here • Documentation comparing SAS to pandas, see here • Removal of the automatic TimeSeries broadcasting