Website Investing & Pricing Analytics
Every day or so, I perform a little ritual on one of my projects that those of you who have blogs are well familiar with. I log into the admin console and moderate comments.
Which brings me face-to-face with THEM. Spammers, in overwhelming numbers. It has gotten to the point where I actually “grade” them on the quality of their blog comment spam. There is a definite hierarchy in terms of blog comment spam quality.
Read moreBlog Comment Spam vs. Effective Marketing – Managing The Balance
Spent most of the past week working on my first “serious” R scripting project.
I’ve been using R for a couple of years, generally as a free minitab replacement (using the R Commander GUI interface) and adjunct to Python projects. Most of my analytics projects to date have been coded in Python, since they are generally heavy on data (eg. require good integration with our data warehouse, dynamic SQL) and require either custom statistics or heavy text parsing. The latest project is somewhat the reverse – involving a relatively small dataset (very painful to assemble, since it reconciles data from two different transaction systems, but small) that I’m going to run a bunch of prepackaged statistical studies and graphics again. Sounds like a perfect fit for R.