Introduction to SASPy: Using SAS in Python
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Use SAS in Python: SASPy
Introduction (1)
WHARTON
RESEARCH
DATA
SERVICES
Eunji Oh, PhD
June 2020
Agenda
SASPY INTRODUCTION / HOW TO USE
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2
What is SASPy?
•
Python APIs to the SAS system
•
Start a SAS session on the same host as Python
•
Exchange data between SAS data sets and Pandas data frames
•
Useful SAS and Pandas methods are available: describe(), head(),
sort(),
where()
and etc.
•
Documentation:
https://sassoftware.github.io/saspy/
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3
Why SASPy?
Typical Workflow with both SAS and non-SAS data
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4
Create / Export
SAS Dataset
Software/kernel change
Import
Create / Export
Output data
(ex - csv)
Software/Kernel change
Import
Why SASPy?
New workflow using SASPy
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5
Create /
Export
SAS Dataset
Software/kernel change
Import
C
o
n
v
e
r
t
Create /
Export
Output data
(ex - csv)
Software/Kernel change
Import
C
o
n
v
e
r
t
Why SASPy?
•
Run SAS code within a Python program
•
Without changing kernel or software
•
Conveniently transferring data as well as macro variables
•
Overcome the famous memory issue of Python
•
No need to read huge data into memory
•
Bypass Python’s memory problem by connecting to a SAS session
running in the background in your Python program
•
Keep using familiar SAS language
•
No need to translate your old SAS codes into Python code
•
Utilize Python’s great expandability
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6
SASPy environment requirements
•
Requirements for your local environment
•
Python3.4 or higher
•
SAS 9.4 or higher
•
Optional: Jupyter Notebook for Jupyter Magic
•
Requirements for WRDS cloud environment
•
Access to WRDS Cloud:
WRDS Jupyter Lab
•
Optional: Your own virtual environment to install custom python
packages
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7
How to setup SASPy – From Local Computer
1. Install from (anaconda) command prompt
•
pip install saspy
•
conda install saspy
2. Add the path below to SYSTEM PATH environment
variable (Windows only, path may vary by individual)
•
C:\Program Files\SASHome\SASFoundation\9.4\core\sasext
3. Run Python and Import SASPy
•
import
saspy
4. Configure SASPy (Windows)
•
from
saspy
import
autocfg
autocfg.main()
#sascfg_personal.py file will be generated
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How to use SASPy - WRDS Jupyter Lab
1.
Access WRDS Jupyter Lab (Login with WRDS ID and
Password)
•
Manual:
https://wrds-
www.wharton.upenn.edu/pages/support/programming-
wrds/programming-python/jupyterhub-wrds/
•
Jupyter Lab:
https://wrds-jupyter.Wharton.upenn.edu/
2. Open a notebook with Python3 kernel
•
Either default Python 3 kernel or your own virtual environment kernel
3. Simply import the pre-installed SASPy
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9
Summary
SASPy could be useful for SAS users learning Python
SASPy helps easily integrating SAS code in Python code
Next video:
Useful SASPy functions
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10
10
Learn about SASPy, a Python API to the SAS system that allows for seamless interaction between SAS and Python environments. Explore how to start a SAS session, exchange data between SAS datasets and Pandas data frames, and utilize various useful methods. Discover the benefits of incorporating SASPy in your workflow to overcome memory issues, retain SAS language familiarity, and enhance expandability with Python.
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Presentation Transcript
WHARTON RESEARCH DATASERVICES Use SAS in Python: SASPy Introduction (1) Eunji Oh, PhD June 2020
Agenda SASPY INTRODUCTION / HOW TO USE 1 SASPy Introduction 2 SASPy Configuration 2 Wharton Research Data Services
What is SASPy? Python APIs to the SAS system Start a SAS session on the same host as Python Exchange data between SAS data sets and Pandas data frames Useful SAS and Pandas methods are available: describe(), head(), sort(), where() and etc. Documentation: https://sassoftware.github.io/saspy/ 3 Wharton Research Data Services
Why SASPy? Typical Workflow with both SAS and non-SAS data Create / Export SAS Dataset Software/Kernel change Import Software/kernel change Import Create / Export Output data (ex - csv) 4 Wharton Research Data Services
Why SASPy? New workflow using SASPy Create / Export SAS Dataset Software/Kernel change Import Convert Software/kernel change Import Convert Create / Export Output data (ex - csv) 5 Wharton Research Data Services
Why SASPy? Run SAS code within a Python program Without changing kernel or software Conveniently transferring data as well as macro variables Overcome the famous memory issue of Python No need to read huge data into memory Bypass Python s memory problem by connecting to a SAS session running in the background in your Python program Keep using familiar SAS language No need to translate your old SAS codes into Python code Utilize Python s great expandability 6 Wharton Research Data Services
SASPy environment requirements Requirements for your local environment Python3.4 or higher SAS 9.4 or higher Optional: Jupyter Notebook for Jupyter Magic Requirements for WRDS cloud environment Access to WRDS Cloud: WRDS Jupyter Lab Optional: Your own virtual environment to install custom python packages 7 Wharton Research Data Services
How to setup SASPy From Local Computer 1. Install from (anaconda) command prompt pip install saspy conda install saspy 2. Add the path below to SYSTEM PATH environment variable (Windows only, path may vary by individual) C:\Program Files\SASHome\SASFoundation\9.4\core\sasext 3. Run Python and Import SASPy import saspy 4. Configure SASPy (Windows) from saspy import autocfg autocfg.main() #sascfg_personal.py file will be generated 8 Wharton Research Data Services
How to use SASPy - WRDS Jupyter Lab 1. Access WRDS Jupyter Lab (Login with WRDS ID and Password) Manual: https://wrds- www.wharton.upenn.edu/pages/support/programming- wrds/programming-python/jupyterhub-wrds/ Jupyter Lab: https://wrds-jupyter.Wharton.upenn.edu/ 2. Open a notebook with Python3 kernel Either default Python 3 kernel or your own virtual environment kernel 3. Simply import the pre-installed SASPy 9 Wharton Research Data Services
Summary SASPy could be useful for SAS users learning Python SASPy helps easily integrating SAS code in Python code Next video: Useful SASPy functions 10 Wharton Research Data Services
