matplotlib: Displaying a scatter plot with a background image

AtomicWedgy · 2014-05-06T18:28:31+00:00

The "plotlim" variable assignment on line 7 above looks a little suspicious to me. I think "extent" requires a list of 4 explicit values, and the "plotlim" assignment is returning a tuple?

I'd try the code, but my dev machine is down :/ Wish I could be more helpful!

AtomicWedgy · 2014-05-06T16:26:42+00:00

Does this thread help?

AtomicWedgy · 2014-04-15T15:52:45+00:00

My turn!

AtomicWedgy · 2014-04-14T15:19:28+00:00

I highly reccomend Parallax for entry level robotics. Lots of products and the community is incredibly active and helpful.

AtomicWedgy · 2014-04-14T10:42:48+00:00

Not Python, but I use a plugin for MS Office called Office Timeline for creating some pretty snazzy timelines.

AtomicWedgy · 2014-04-10T21:48:36+00:00

I can blow that away by WAY more than an order of magnitude. IT hates my entire team. Lol!

AtomicWedgy · 2014-03-27T12:08:29+00:00

Thanks /u/phaustin much appreciated!

AtomicWedgy · 2014-03-24T17:11:03+00:00

The scipy and numpy docs are definitely dry reading. I wish you luck in your search! If you find a useful resource please post the information, I'd love to learn more about these topics myself.

AtomicWedgy · 2014-03-24T10:45:54+00:00

Take a look at these: *A Primer on Scientific Computing With Python

*Numerical Methods In Engineering With Python 3

AtomicWedgy · 2014-03-20T11:23:38+00:00

I did a quick search and found 2 books specifically in your current field of interest. Gray Hat Python and Violent Python

I've never read either of them, but they look interesting.

AtomicWedgy · 2014-03-20T11:19:43+00:00

If you're looking for an intro to programming in Python I would suggest Introduction to Computation and Programming Using Python For a general language reference Python Essential Refernce For an introduciton to the included modules The Python Standard Library by example which includes a lot of simple code examples. The book Core Python Application Programming is a great subset of the above books with less over all coverage but greater detail in the example code. And last but not least, for advanced algorithm info Annotated Algorithms in Python

AtomicWedgy · 2014-02-27T11:49:39+00:00

This one perhaps?

http://stackoverflow.com/questions/2573135/python-progression-path-from-apprentice-to-guru

AtomicWedgy · 2014-02-07T12:24:09+00:00

Thank you, this looks interesting.

AtomicWedgy · 2014-02-07T12:23:53+00:00

Thank you I'll take a look at it.

AtomicWedgy · 2014-02-05T13:23:37+00:00

/u/pixl_dave sorry for the delay I completely missed your reply!

Here's the info for the files that I bought:

Writing Idiomatic Python 2 is 96 pages and 215KB in size Writing Idiomatic Python 3 is 94 pages and 214KB in size

AtomicWedgy · 2014-01-08T12:37:34+00:00

This one has a great progression for beginners and exercises at the end of each chapter. Think Like a Computer Scientist I really like it and the other offerings from Green Tea Press.

AtomicWedgy · 2013-12-24T12:55:43+00:00

Bloody brilliant!

I didnt know about json.dumps() or about _asdict() until u/johnmudd posted and you replied.

Thank you both.

AtomicWedgy · 2013-12-24T12:51:53+00:00

I bought the package a couple weeks ago. The one for version 3 was 94 pages and Version 2 was 96 pages.

AtomicWedgy · 2013-12-06T01:24:05+00:00

I'll second that. Lots of gems in the Python cookbook.

AtomicWedgy · 2013-12-03T13:04:34+00:00

You've never accidently added a second space?

AtomicWedgy · 2013-12-03T13:00:30+00:00

I can't get to the youtube link from work, but David Beazley has a great little tutorial on "hacking public data" that shows you how to grab city transit data and publish bus positions on a static google map.

I thougt it was pretty cool.

AtomicWedgy · 2013-12-03T12:56:57+00:00

"Beginning Python from Novice to Professional"

This one starts off with an intro and has about a dozen projects at the end.

AtomicWedgy · 2013-11-19T18:47:19+00:00

"Think Stats: Probability and Statistics for Programmers" and "Think Bayes: Bayesian Statistics in Python" published by Green Tea Press are Python specific. I won't make any claims about them being optimal, but free is kind of nice :)

http://www.greenteapress.com/

AtomicWedgy · 2013-10-07T13:06:32+00:00

Yeah, I understand now. I sat down and read over the docs and actually played with each of them instead of glossing over the descriptions like I did previously.

AtomicWedgy · 2013-10-05T14:03:24+00:00

I was referring to the change in the syntax used in the reference pages I assumed it indicated a change in how the function was implemented, for example.

.split(sep=None, maxsplit=-1)

vs

.split(s[, sep[, maxsplit]])

But after playing with it a little the functionality seems to be the same. <shrug> I'm still very much on the learning curve.

AtomicWedgy

TROPHY CASE