Bill Lattner recently published a good, if somewhat technical, post titled Forget Python vs. R: how they can work together. The article discusses methods to combine the strengths of Python and R, for example by using C to produce functions callable by both. Much has been made about the relative strengths and weakness of Python and R. I think the more important takeaway is that most things can be done well by either language.
Both Languages are Great
While there is some truth to the comments that R is more suited for statistics and Python better for web integration or external database connectivity, in reality both languages will satisfy the needs of most data scientists. In my opinion the common strength of the software suites is that they are free and cross-platform, with large user communities that contribute to external packages and are available to answer questions. That they are free allows all of us to explore with each without monetary investment and on whatever device we are using at the time.
Understand Your Goals
Sometimes we just want to play with some data. That is great and one of the most enjoyable parts of growing as a data scientist. However, sometimes we approach a dataset with a specific goal in mind. If that is the case for you, it might be worth doing some searching prior to starting to avoid reinventing the wheel. If an external package that meets your needs is already available take advantage of that contribution. Make sure, however, to be careful with community-produced solutions as there are many examples of hidden errors that are not caught until after they have been used by many people, if ever.
Conclusion
Howard and I hope that the different examples presented on this site stimulate your own questions that may be answered by data science. Don’t get caught up worrying about which software suite to use. There is no wrong answer.
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Joe Wildenberg, MD/PhD is an interventional radiology fellow at University of Pennsylvania. His interests include applying data science to radiology and medical data, interventional radiology, and traveling the world.
Joe will finish training in June 2018 and is moving back to Wisconsin to practice with the Mayo Clinic Health System.
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Its not Python OR R, its Python AND R
Bill Lattner recently published a good, if somewhat technical, post titled Forget Python vs. R: how they can work together. The article discusses methods to combine the strengths of Python and R, for example by using C to produce functions callable by both. Much has been made about the relative strengths and weakness of Python and R. I think the more important takeaway is that most things can be done well by either language.
Both Languages are Great
While there is some truth to the comments that R is more suited for statistics and Python better for web integration or external database connectivity, in reality both languages will satisfy the needs of most data scientists. In my opinion the common strength of the software suites is that they are free and cross-platform, with large user communities that contribute to external packages and are available to answer questions. That they are free allows all of us to explore with each without monetary investment and on whatever device we are using at the time.
Understand Your Goals
Sometimes we just want to play with some data. That is great and one of the most enjoyable parts of growing as a data scientist. However, sometimes we approach a dataset with a specific goal in mind. If that is the case for you, it might be worth doing some searching prior to starting to avoid reinventing the wheel. If an external package that meets your needs is already available take advantage of that contribution. Make sure, however, to be careful with community-produced solutions as there are many examples of hidden errors that are not caught until after they have been used by many people, if ever.
Conclusion
Howard and I hope that the different examples presented on this site stimulate your own questions that may be answered by data science. Don’t get caught up worrying about which software suite to use. There is no wrong answer.
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Joe will finish training in June 2018 and is moving back to Wisconsin to practice with the Mayo Clinic Health System.