Python - to learn or not to learn


I’ve been doing research recently, and I feel like being able to use Python would help me grow as an evaluator and be able to do more complex data analysis with data sets from sources like Kaggle. Do you agree? If so, what is the best way to learn Python? If not, why not?

If you have any experience learning Python independently, I’d love to hear your tips and tricks.



Hey @maddisonstasz, not sure I know any evaluators who are well-versed in Python. Most evaluators I know who start getting more into the complex data world seem to opt for R. Which makes sense because so many already have some comfort level with the S worlds (SPSS, SAS, S+) and R isn’t as big of a jump.

I see a lot more Python when connecting with coders, and other people who come into data science from areas outside of academic disciplines.

All that said, I don’t think it’s a bad idea to push your way outside what other evaluators do. We are in an age where knowing something different from the people around you can give you an edge.

For either R or Python, there are a number of courses available for free through Coursera. Another alternative with practical self-paced courses would be


I agree, R seems to be much more used in the evaluation world compared to anything. That being said, from what I gather Python can do pretty much all the same things R can do (and RStudio can do both Python and R).

DataCamp was a resource I used to always recommend, but the company went through a sexual assault scandal that makes me hesitant to promote them any longer. However, David Keyes has a great R course on his website R for the Rest of Us. The “Getting Started with R” course is free. I’ve previewed all of the course and think it’s a great course for getting started and learning the basics of R and some of the most useful packages in R.

Here’s a link to his courses (note: it’s an affiliate referral link):


Count me out of the loop on the datacamp issue. For anyone interested in the story >


Thanks, @danawanzer, for mentioning R for the Rest of Us. If anyone has questions about R, please let me know. I’d be happy to discuss!

If you’re looking for other resources to explore R, I’ve posted some on the resources page .

You can also check this out. That was developed by folks who wanted to curate a list of alternatives to DataCamp in light of the awful goings-on there.

My biggest piece of advice for folks starting out with R is to use what’s known as the Tidyverse. It makes working with R so much easier.


That’s a great resource @dgkeyes , thanks for sharing.

Curious, I know you’re partial to R, but what are the merits for someone like @maddisonstasz to jump into Python?

If you’re going to choose to start with one of the two as an evaluator, I would think R is the way to go. But is there a good counter argument.


Unfortunately, I don’t have any experience with Python so I can’t speak to it personally. My understanding is that R was designed for data analysis (though it can do much more than that now) while Python was developed as an all-purpose language and then people have begun using it for data stuff. One other thing I’d say is that the community of R users is incredible. Super open to newcomers, which makes it much easier to get started (you can ask questions without being told you should know more). I wrote a bit about this here.


Hi everyone,

Thank you so much for all of this great feedback. I think the answer is clear: R seems like the best option to learn about this point. Thank you!


I agree that R just has so much for functionality for evaluators. In addition to getting familiar with the Tidyverse, definitely check out RMarkdown. It’s a wonderful way to generate reports and presentations as well as to learn R because it has troubleshooting built into its structure in a clearer way than R directly or R Studio (PS, use R Studio).

I do have a colleague who was first fluent in Python before learning R and apparently the two languages are quite similar and therefore, learning R could facilitate learning Python. Many of the same resources available for learning R (for free, too!) are also available in Python version. Python tends to be geared more towards Data Scientists whereas, R is geared more towards Data Analysts (and now so many more of us!).


I’ve been wanting to learn one of the two as well. Let me know if you want an accountability partner!!

I’ve noticed that R is more popular in academic fields. Whereas Python is more popular is non-academic roles. Evaluation tends to fall closer to the academic side.

For example, if you’re interested in having the option of becoming a “Data Scientist” or consulting for corporations, Python might be the way to go.


Hi Michelle and Everyone,

I am planning to attend R or Python course online but find it hard to commit. Would be interested in finding an accountability partner, should you or someone else be interested. Let me know.


If you don’t know either R or Python - I’d probably learn R first. IMO it’s better suited as statistical tool, and there’s more documentation for things like the survey package - which is indispensable in evaluation. However, I want to make a case for learning python as well.

If you’re doing GIS or text analysis - Python might be better suited for those. You would, for example, find ArcGIS and QGIS much more efficient with a broader set of specific tools at your fingertips with a knowledge of python.

That said - I think ArcGIS Desktop is currently still stuck on Python 2, when the rest of the world (including QGIS) has moved to Python 3. SO, if you want to use python for GIS, and you mainly use Arc - then might be better to wait it out.


Feel free to email me about being an accountability partner: [email protected]