http://www.opencircuits.com/index.php?title=Python_Resources_for_Math_499&feed=atom&action=historyPython Resources for Math 499 - Revision history2024-03-28T18:44:13ZRevision history for this page on the wikiMediaWiki 1.34.2http://www.opencircuits.com/index.php?title=Python_Resources_for_Math_499&diff=78811&oldid=prevRuss hensel: 1 revision2017-01-06T17:28:54Z<p>1 revision</p>
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</td></tr></table>Russ henselhttp://www.opencircuits.com/index.php?title=Python_Resources_for_Math_499&diff=78238&oldid=prevRuss hensel: /* Readings, Documentation, and Similar Resources */2016-09-23T18:41:15Z<p><span dir="auto"><span class="autocomment">Readings, Documentation, and Similar Resources</span></span></p>
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<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">Contact me [[https://us.bbcollab.com/guest/BC92DC6A75D3993282C5D6A72A55051F Black Board Colab]]</ins></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr>
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</table>Russ henselhttp://www.opencircuits.com/index.php?title=Python_Resources_for_Math_499&diff=78209&oldid=prevRuss hensel: /* Problem Domains and Python */2016-09-21T15:20:07Z<p><span dir="auto"><span class="autocomment">Problem Domains and Python</span></span></p>
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</table>Russ henselhttp://www.opencircuits.com/index.php?title=Python_Resources_for_Math_499&diff=78208&oldid=prevRuss hensel: /* Problem Domains and Python */2016-09-21T15:16:12Z<p><span dir="auto"><span class="autocomment">Problem Domains and Python</span></span></p>
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</table>Russ henselhttp://www.opencircuits.com/index.php?title=Python_Resources_for_Math_499&diff=78207&oldid=prevRuss hensel: /* Problem Domains and Python */2016-09-21T14:57:10Z<p><span dir="auto"><span class="autocomment">Problem Domains and Python</span></span></p>
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</table>Russ henselhttp://www.opencircuits.com/index.php?title=Python_Resources_for_Math_499&diff=78204&oldid=prevRuss hensel: /* Programming In Python */2016-09-15T00:33:41Z<p><span dir="auto"><span class="autocomment">Programming In Python</span></span></p>
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<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Python for Data Analysis by Wes McKinney a good book for use of pandas which can be particularly useful in, at least mid-sized, data analysis. The book is from Published by O’Reilly Media, Inc., which is a great source of computer technology books, but often quite expensive. This appears to be a free, legal, PDF: '''[http://www.cin.ufpe.br/~embat/Python%20for%20Data%20Analysis.pdf Python for Data Analysis (PDF)]'''</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Python for Data Analysis by Wes McKinney a good book for use of pandas which can be particularly useful in, at least mid-sized, data analysis. The book is from Published by O’Reilly Media, Inc., which is a great source of computer technology books, but often quite expensive. This appears to be a free, legal, PDF: '''[http://www.cin.ufpe.br/~embat/Python%20for%20Data%20Analysis.pdf Python for Data Analysis (PDF)]'''</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>*'''[https://www.amazon.com/Python-Data-Analysis-Wrangling-IPython/dp/1449319793 Python for Data Analysis at Amazon]''' Price especially used, not too bad. But <del class="diffchange diffchange-inline">not as good as </del>free above.</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>*'''[https://www.amazon.com/Python-Data-Analysis-Wrangling-IPython/dp/1449319793 Python for Data Analysis at Amazon]''' Price especially used, not too bad. But <ins class="diffchange diffchange-inline">more than </ins>free above.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>*'''[https://vimeo.com/59324550 10-minute tour of pandas from Wes McKinney]''' A video tour.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>*'''[https://vimeo.com/59324550 10-minute tour of pandas from Wes McKinney]''' A video tour.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>*'''[https://www.datacamp.com/community/tutorials/r-or-python-for-data-analysis Choosing R or Python for data analysis? An infographic]''' Use Python or use R? Find out ( one opinion ).</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>*'''[https://www.datacamp.com/community/tutorials/r-or-python-for-data-analysis Choosing R or Python for data analysis? An infographic]''' Use Python or use R? Find out ( one opinion ).</div></td></tr>
</table>Russ henselhttp://www.opencircuits.com/index.php?title=Python_Resources_for_Math_499&diff=78810&oldid=prevRuss hensel: /* Programming In Python */2016-09-15T00:30:25Z<p><span dir="auto"><span class="autocomment">Programming In Python</span></span></p>
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<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Python for Data Analysis by Wes McKinney a good book for use of pandas which can be particularly useful in, at least mid-sized, data analysis. The book is from Published by O’Reilly Media, Inc., which is a great source of computer technology books, but often quite expensive. This appears to be a free, legal, PDF: '''[http://www.cin.ufpe.br/~embat/Python%20for%20Data%20Analysis.pdf Python for Data Analysis (PDF)]'''</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>* Python for Data Analysis by Wes McKinney a good book for use of pandas which can be particularly useful in, at least mid-sized, data analysis. The book is from Published by O’Reilly Media, Inc., which is a great source of computer technology books, but often quite expensive. This appears to be a free, legal, PDF: '''[http://www.cin.ufpe.br/~embat/Python%20for%20Data%20Analysis.pdf Python for Data Analysis (PDF)]'''</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>*'''[https://www.amazon.com/Python-Data-Analysis-Wrangling-IPython/dp/1449319793 Python for Data Analysis at Amazon]''' Price especially used, not too bad.</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>*'''[https://www.amazon.com/Python-Data-Analysis-Wrangling-IPython/dp/1449319793 Python for Data Analysis at Amazon]''' Price especially used, not too bad<ins class="diffchange diffchange-inline">. But not as good as free above</ins>.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>*'''[https://vimeo.com/59324550 10-minute tour of pandas from Wes McKinney]''' A video tour.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>*'''[https://vimeo.com/59324550 10-minute tour of pandas from Wes McKinney]''' A video tour.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>*'''[https://www.datacamp.com/community/tutorials/r-or-python-for-data-analysis Choosing R or Python for data analysis? An infographic]''' Use Python or use R? Find out ( one opinion ).</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>*'''[https://www.datacamp.com/community/tutorials/r-or-python-for-data-analysis Choosing R or Python for data analysis? An infographic]''' Use Python or use R? Find out ( one opinion ).</div></td></tr>
</table>Russ henselhttp://www.opencircuits.com/index.php?title=Python_Resources_for_Math_499&diff=78183&oldid=prevRuss hensel: 1 revision2016-09-13T16:33:12Z<p>1 revision</p>
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<td colspan="1" style="background-color: #fff; color: #222; text-align: center;">Revision as of 16:33, 13 September 2016</td>
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</td></tr></table>Russ henselhttp://www.opencircuits.com/index.php?title=Python_Resources_for_Math_499&diff=78182&oldid=prevRuss hensel: /* Programming In Python */2016-09-03T20:12:12Z<p><span dir="auto"><span class="autocomment">Programming In Python</span></span></p>
<p><b>New page</b></p><div>This is a draft for material that may be moved to the official course site<br />
<br />
= Software =<br />
== Install Anaconda Python/Spyder for Python ==<br />
<br />
Why install Anaconda rather than some other perfectly reasonable download? Because:<br />
<br />
* It does an install of both core Python and lots of extensions of use in science and mathematics.<br />
* It includes a nice ( but not perfect ) Integrated Development Environment, IDE.<br />
* It has a good command line update tool ( called "conda" this is in addition to the usual "pip" ).<br />
* It is well supported, has good resources on web.<br />
* Of course, it is free.<br />
<br />
Download for all operating system at: '''[https://www.continuum.io/downloads DOWNLOAD ANACONDA NOW]''' Anaconda supports both Python 2.7 and 3.x, generally we prefer 2.7 as not all packages that you want may have been upgraded to 3.x. Anaconda can support both with easy version switching, but Russ at any rate has not figured this out. <br />
<br />
For a list of the extensions in Anaconda see: '''[https://docs.continuum.io/anaconda/pkg-docs Anaconda package list]''' The list also has links to more information on the packages.<br />
<br />
== Python Extensions You May Want ==<br />
<br />
Most of these already in the Anaconda install but if you are not using it you may want to add extensions. Anaconda extensions are supported with the conda utility. If conda will not do the trick you may need another installation path. When conda does not work try installing with pip or Google or ask Russ.<br />
<br />
* SciPy (pronounced “Sigh Pie”) is a Python-based ecosystem of open-source software for mathematics, science, and engineering. In particular, these are some of the core packages: NumPy ( numerical methods ) , SciPy ( scientific computing ), Matplotlib ( plotting ), Sympy ( symbolic mathematics), pandas ( data structures & analysis ) and more ...... '''[https://www.scipy.org SciPy.org]'''<br />
* TkInter for construction of Graphical User Interfaces ( GUI's ) '''[https://wiki.python.org/moin/TkInter TkInter]'''<br />
* Beautiful Soup for screen scraping, web data harvesting. '''[https://www.crummy.com/software/BeautifulSoup/ Beautiful Soup]'''<br />
<br />
== SageMath ==<br />
<br />
Is a version of Python and an environment for running it especially developed for math and science. Once you are set up to use it access is from your web browser and work is saved in notebooks. It is, at least to me, a very interesting environment similar in many ways to Matlab or Mathematica. They are closed source, this is open.<br />
<br />
There are several free servers you can point your browse at but they may not offer great availability or performance. My ( Russ ) preferred method of running it is to install a server on my laptop and connect as local host. This is too big a topic for me to author a good treatment here ( and now ) but you should at least be aware of this option.<br />
<br />
If you are adventurous Google Sagemath and see what you can do.<br />
<br />
= Readings, Documentation, and Similar Resources =<br />
<br />
== Programming In Python ==<br />
<br />
* Python for Data Analysis by Wes McKinney a good book for use of pandas which can be particularly useful in, at least mid-sized, data analysis. The book is from Published by O’Reilly Media, Inc., which is a great source of computer technology books, but often quite expensive. This appears to be a free, legal, PDF: '''[http://www.cin.ufpe.br/~embat/Python%20for%20Data%20Analysis.pdf Python for Data Analysis (PDF)]'''<br />
*'''[https://www.amazon.com/Python-Data-Analysis-Wrangling-IPython/dp/1449319793 Python for Data Analysis at Amazon]''' Price especially used, not too bad.<br />
*'''[https://vimeo.com/59324550 10-minute tour of pandas from Wes McKinney]''' A video tour.<br />
*'''[https://www.datacamp.com/community/tutorials/r-or-python-for-data-analysis Choosing R or Python for data analysis? An infographic]''' Use Python or use R? Find out ( one opinion ).<br />
*'''[https://www.analyticsvidhya.com/blog/2016/01/complete-tutorial-learn-data-science-python-scratch-2/ A Complete Tutorial to Learn Data Science with Python from Scratch]'''<br />
*'''[https://www.facebook.com/sagemathorg/?hc_ref=NEWSFEED&fref=nf (33) Sage Math On Facebook]'''<br />
<br />
== Meta Python == <br />
*'''[https://www.python.org/doc/humor/ Python Humor]'''<br />
*'''[https://python-history.blogspot.com/2010/06/import-antigravity.html The History of Python: import antigravity ]'''<br />
<br />
= Business Problems in Python =<br />
<br />
Business often seeks maximum profit, or minimum cost. Thus problems of optimization may be useful. Another area of interest is data analysis. It would be nice to have a matrix of math methods and the software that supports the method. In the way old days the software was just choosing the "best" language ( usually the one you knew ) and then going at it. Now days the language choice is greatly influenced not just but the characteristics of the language but also the packages that are already programed in much of the problem domain you need. It would be nice to have a chart of the problem domains and the software tools that might apply. I am working on this for Python, stay tuned.<br />
<br />
<br />
=== Problem Domains and Python ===<br />
{| class="wikitable"<br />
<!--------------------------------><br />
|-valign="top"<br />
|Problem Domain<br />
|Python<br />
|Comment<br />
<!--------------------------------><br />
|-valign="top"<br />
|Function Maximization ( calculus )<br />
|SageMath packages already installed.<br />
|Both symbolic and numerical methods are available. '''[http://www.sagemath.org/calctut/ Sagemath Calculus Tutorial]'''<br />
<!--------------------------------><br />
|-valign="top"<br />
|Linear Programming<br />
|<br />
|<br />
<br />
<br />
<br />
<!--------------------------------><br />
|-valign="top"<br />
|Monte Carlo Simulation<br />
|<br />
|*'''[https://www.chrisstucchio.com/blog/2013/basic_income_vs_basic_job.html Modelling a Basic Income with Python and Monte Carlo Simulation - Chris Stucchio ]'''<br />
<br />
<!--------------------------------><br />
|-valign="top"<br />
|<br />
|<br />
|<br />
<br />
<!--------------------------------<br />
|-valign="top"<br />
|<br />
|<br />
|<br />
<!--------------------------------<br />
|-valign="top"<br />
|<br />
|<br />
|<br />
<br />
<!--------------------------------<br />
|-valign="top"<br />
|Col 1 text<br />
|Col 2 text<br />
|Col 3 text<br />
<!--------------------------------<br />
|-valign="top"<br />
|Col 1 text<br />
|Col 2 text<br />
|Col 3 text<br />
<br />
<br />
<br />
<!-----------end of table---------------------><br />
<br />
|}<br />
<br />
<br />
<br />
[[category:Python]]</div>Russ hensel