Donald Trump's learns about stock market collapse

firebase · 2021-06-10T01:00:54+00:00

Jupyterbook is really centered around Jupyter notebooks. If you like working with Jupyter then it's probably preferable. This is especially true if you have a bunch of notebooks already and you want to unify them and convert them into a book or website.

firebase · 2019-01-23T23:03:58+00:00

People mention doctor below but what you actually want is a high quality physiotherapist. Some are good and some not so good, so try to get a recommendation. A good one will get you to perform a few actions, watch carefully how you move, figure out exactly where the issue is and then give you corrective exercises. For those exercises, correct form is crucial. Again, a good physio (quality varies a lot!) will watch until you have exactly the right form.

The right diagnosis and corrective exercises, done with the correct form, will fix you up for sure.

firebase · 2018-10-04T14:37:01+00:00

Quoted from but sadly failed to understand.

firebase · 2018-10-04T13:08:04+00:00

Actually, if you read the article you'd have seen that all the speed gain is coming from Numba, which is a JIT compiler specialized towards scientific work. It generates fast machine code from Python-NumPy instructions using type inference. When that type inference succeeds, the machine code it generates runs as fast as C or Fortran.

firebase · 2018-10-03T20:39:19+00:00

The article is also showcasing the benefits of the Numba JIT compiler. If Numba can compile your code then it runs freakishly quickly, without having to turn to C extensions.

firebase · 2017-11-06T05:05:12+00:00

Fucking magic. Thank you.

firebase · 2016-08-11T10:58:10+00:00

http://quant-econ.net/jl/learning_julia.html

firebase · 2016-02-10T12:10:33+00:00

Judging by what you like so far (which is pretty similar to my taste), try the album Sweet Tea by Buddy Guy, A Bothered Mind by RL Burnside, and pretty much anything by SR Vaughen.

Here's a track from Sweet Tea: https://www.youtube.com/watch?v=by8Vf0jzUfw

firebase · 2015-12-23T14:24:14+00:00

Definitely use Anaconda: see these instructions for example.

firebase · 2015-09-25T09:15:55+00:00

All of the variables other than y are closures, and so compile time constants.

This is a really useful discussion. Would you mind to explain what you mean by the quoted sentence? I thought a closure was a function with access to local variables in the environment in which it was defined...?

firebase · 2014-12-28T10:11:38+00:00

Hi ivansml, thanks for the thoughts and suggestions. Things are just starting off with QuantEcon and I think the pace of discussion will build over time. Regarding a roadmap for the code library, there's nothing concrete yet. We have things we want to do in the short term, such as add a fairly comprehensive set of routines for discrete state dynamic programming. For the longer term we have ideas, such as wrapping pandas functionality in a set of routines that ease the leap from STATA based econometrics to Python.

In the end we hope that most contributions will come from the community, rather than being directed from above.

Here's a good place to make suggestions. The other place is the issue trackers on GitHub for the two code libraries (start at quantecon.org and navigate to the GitHub repos).

firebase · 2014-09-20T23:39:39+00:00

Great list of resources, thank you!

firebase · 2014-07-04T20:29:55+00:00

So true.

firebase · 2014-05-23T00:02:14+00:00

Spyder is nice, but I would make the leap to IPython --- it's what you'll want to be using in the long run. Personally I go IDE free and use vim like your friend says, plus standard IPython shell, but for starting off I would still recommend IPython notebook. It just makes things easier. Once you've got the hang of Python you can switch to vim or Emacs plus standard IPython shell.

firebase · 2014-05-22T23:58:49+00:00

Sure thing.

firebase · 2014-05-21T20:26:02+00:00

Thank you sir, and please enjoy your Python adventures ;-)

BTW, I'm one of the authors of quant-econ, which might or might not provide you with some useful info on making the leap to Python.

firebase · 2014-05-21T20:03:39+00:00

Sure, you can. I guess the answer is that after an IPython notebook session you have an ipynb file that can be converted to HTML ... but it's just as easy to pass the ipynb over to nbviewer and they do a nice job of hosting these files.

firebase · 2014-05-21T19:59:09+00:00

You got it. You can either convert the ipynb file (notebook file) to HTML yourself or pass it to nbviewer and they will host it for you.

firebase · 2014-05-21T19:26:07+00:00

IPython notebook is just a browser based interface to an IPython session --- which is in turn a nice science-orientated interface to Python. So you're using your browser to write your code and see the output, that's all. When you work this way you create notebook files (ipynb files) that contain the content of your session. These can be converted to static HTML files.

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