Hello! Our team is working on creating a publication to help get views and leads for freelancers, consultants and bloggers. We enjoyed reading your article and thought it would be great to add to our marketing page.
Would you be interested in publishing your stories in our publication? We will also be creating a website that…
a) that was a faux pas on me
b) Using R doesn’t qualify someone to be a data scientist?
R and SAS are two other common tools of a data scientist. Even then, there are still more tools for modeling. Personally, my experience is with R, python and Matlab. Never been a fan of the latter.
A statistician can make a great data scientist as long as they have SQL and python abilities. Being purely a statistician limits how large of data you can manage.
There is nothing wrong with tools like Excel. But if we are trying to distinguish the semantic differences between data scientist and statistician then it would probably be in the tools they use and how they apply them.
Thanks for the catch! I was trying to point out the fact that both are python but separate libraries and it is actually really easy to know one and not the other.
Thats why I always tell people they should clarify what kind of interview questions they will be getting when python is on the table. Will it be using Pandas, Luigi or will it just be operational.
That is a great solution! I have only used that clause once and totally forgot about it. You are correct. You could cut out the two temp tables and just have one query that gets both the current value and the next leading value for the date.
The one caveat here is if you need to compare multiple columns. Not just one as in…