The best platform for Python analytics.
August 08, 2016
The best platform for Python analytics.
Score 10 out of 10
Vetted Review
Verified User
Overall Satisfaction with Anaconda
I'm still a bit new here, but we have many different places where we do analytics. Some people like SAS, some like R, some like Python, some like SQL, some like Excel, etc. Anaconda is the "no duh" default distribution for doing analytics or anything scientific in Python. In particular, once you do your pull from the server, it's really necessary to have a powerful tool for data analysis. SQL "can" do a lot of things, but it is just horrible for analytics. Like using vice grips to brush your teeth.
Pros
- Anaconda (i.e. Python with lots of packages and the fabulous iPython/Jupyter Notebook) does analytics well. In analytics, or "data science" or whatever buzzword, you have to pick your poison: Python, R, or SAS. Python is the only one that's good at doing other things as well.
- Like visualization...The quality of the built in types of scientific visualization in Python vs. R and their aesthetics is up for grabs. However, Python can do a whole lot of different kinds of visualization above and beyond R. Similarly, JavaScript probably can do more/better visualization than Python, but it's not meant for analytics. Anaconda has enough visualization packages to get you started.
Cons
- It's still a little buggy. Especially the launcher.
- It's not always easy to set up. It's not exactly difficult: a Google search away for most things, but silly stuff like path names, installing custom fonts and colors. That kind of thing.
Simple story. I tried both. Canopy felt somehow unintuitive to use.
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