#SEQUENT-336.50
1.618% is (337) further Fibonacci extension likely if sustain rise above 337(weekly closing)

#Perspective

Pretending that voting for Trump or denying climate change or suggesting the solution to every problem is more guns is a legitimate point of view, worthy of respect is not "how America works." It is how it dies.

People in a free society are entitled to any point of view no matter how obviously wrong or outlandish or destructive provided they do not impose their views on others.

But suggesting that something ignorant or divorced from reality warrants the same kind of treatment in public debate as something based in fact or at least credible is absurd and when done on behalf of a society in public media or academic settings it is self-destructive.

We would not grant media coverage or much bandwidth at all to a group that argued that unicorns exist or that there was a pot of gold at the end of the rainbow. Yet views like denying climate change or basing policy decisions on sweeping, obvious lies, are just as unsound.

Somewhere, somehow, judgments must be made. Some behaviors are wrong and must be condemned. Someone must challenge lies and demand facts. Coddling people who embrace idiocies does not help them no matter how loudly they demand to be coddled.

This post is pretty bizarre, but it manages to hit on so many false beliefs that I've seen hurt junior data scientists that it deserves some explicit

(1) The notion that R is well-suited to "building web applications" seems totally out of left field. I don't feel like most R loyalists think this is a good idea, but it's worth calling out that no normal company will be glad you wrote your entire web app in R.

(2) It is true that Python had some issues historically with the 2-to-3 transition, but it's not such a big deal these days. On the flip side, I have found interesting R code that doesn't run in modern R interpreters because of changes in core operations (e.g. assignment syntax).

(3) "Most of the time we only need a latest, working interpreter with the latest packages to run the code" -- this is where things get real and reveal some things that hurt data scientists. If this sentence is true, it's likely because you don't share code with coworkers.

(3) Really is a broader issue in data science: people only think of what they need to do their work if no one else existed and code was never maintained. Junior data scientists almost always operate on projects they start from scratch and don't have to maintain for long.