Data Science Rosetta Stone
Frequently Asked Questions
How can I propose an edit or improvement to these tutorials?
Which version of SAS was used to make this tutorial?
- SAS/STAT 14.2
- SAS/ETS 14.2
- SAS/OR 14.2
- SAS/IML 14.2
- SAS/QC 14.2
- SAS Enterprise Miner Workstation 14.2
Which version of Python was used to make this tutorial?
- pandas (0.20.2)
- NumPy (1.12.1)
- Matplotlib.PyPlot
- seaborn (0.7.1)
- re (2.2.1)
- decimal (1.70)
- sklearn (0.18.2)
- statsmodels.api
- xgboost (0.6)
- pyclustering
- PyFlux (0.4.15)
- FBProphet
Which version of R was used to make this tutorial?
- gdata
- rjson
- ggplot2
- dplyr
- tree
- randomForest
- gbm
- xgboost
- e1071
- RSNNS
- caret
- kernlab
- dbscan
- kohonen
- forecast
- prophet
Please visit our GitHub repository at https://github.com/datasciencerosettastone/ to propose edits and/or improvements to the tutorials. Thank you in advance!
SAS 14.2, including the following products:
Python 3.5.2, including the following packages:
These packages are explained in more detail in the Python Tutorial. To install these packages, use pip or conda as appropriate. Usually, the package documentation will indicate how to install the package.
R 3.3.1, including the following packages:
These packages, and installation procedures, are explained in more detail in the R Tutorial.