SASPy Library
for developers
Getting started with SASPy
This module creates a bridge between Python and SAS 9.4. SASPy enables a Python developer, familiar with Pandas dataframes or SAS datasets, to leverage the power of SAS by connecting a Python process to a SAS 9.4 installation, where it will run SAS code. Features:
- SAS code is generated by the supplied Python object and methods
- Results return in various forms, including Pandas Data Frames
- Run analytics and return graphics and data to the Python process
- Convert data between SAS Data Sets and Pandas Data Frames
- Supports local and remote connections
- Interface with Jupyter notebooks or interactive and batch Python
Sample code
The sample code below establishes a connection and returns descriptive statistics on a table. To see further sample code, visit the samples page on GitHub.
Get descriptive statistics
>>> import saspy
>>> sas = saspy.SASsession()
SAS Connection established. Subprocess id is 3664
>>> cars = sas.sasdata( 'cars','sashelp')
>>> cars.describe()
Variable Label N NMiss Median Mean StdDev Min P25 P50 P75 Max
0 MSRP NaN 428 0 27635.0 32774.855140 19431.716674 10280.0 20329.50 27635.0 39215.0 192465.0
1 Invoice NaN 428 0 25294.5 30014.700935 17642.117750 9875.0 18851.00 25294.5 35732.5 173560.0
2 EngineSize Engine Size (L) 428 0 3.0 3.196729 1.108595 1.3 2.35 3.0 3.9 8.3
3 Cylinders NaN 426 2 6.0 5.807512 1.558443 3.0 4.00 6.0 6.0 12.0
4 Horsepower NaN 428 0 210.0 215.885514 71.836032 73.0 165.00 210.0 255.0 500.0
5 MPG_City MPG (City) 428 0 19.0 20.060748 5.238218 10.0 17.00 19.0 21.5 60.0
6 MPG_Highway MPG (Highway) 428 0 26.0 26.843458 5.741201 12.0 24.00 26.0 29.0 66.0
7 Weight Weight (LBS) 428 0 3474.5 3577.953271 758.983215 1850.0 3103.00 3474.5 3978.5 7190.0
8 Wheelbase Wheelbase (IN) 428 0 107.0 108.154206 8.311813 89.0 103.00 107.0 112.0 144.0
9 Length Length (IN) 428 0 187.0 186.362150 14.357991 143.0 178.00 187.0 194.0 238.0
>>>