Besides the mistakes in the pdf (random.shuffle) the idea is to get the right environment then py basics then numpy+pandas then viz seaborn or minimal matplotlib
Abdur-Rahmaan Janhangeer http://www.pythonmembers.club | https://github.com/Abdur-rahmaanJ Mauritius On Thu, 21 Nov 2019, 00:49 Abdur-Rahmaan Janhangeer, <arj.pyt...@gmail.com> wrote: > I have a draft of a concise py book for data people which i am preparing, > might be useful to you. > > > https://drive.google.com/file/d/1IKLBuJJWQKvcTWu-REsgm-JUGSvytBUu/view?usp=drivesdk > > Abdur-Rahmaan Janhangeer > http://www.pythonmembers.club | https://github.com/Abdur-rahmaanJ > Mauritius > > On Wed, 20 Nov 2019, 20:54 Göktuğ Kayaalp, <s...@gkayaalp.com> wrote: > >> Hi all, >> >> I am responsible of giving my colleagues in from linguistics MA >> programme an intro to Python, and programming, with a focus on >> statistics. It’ll be a single lecture, and I probably won’t be able to >> do more than give some demos and then some pointers to actually properly >> learn how to use the tools. >> >> The problem is I’m a rather techie power user and my audience the exact >> opposite, so I feel like I could make use of some guidance as to how to >> bridge the gap and be useful. >> >> I want to stick to Python 3, demo them a few basics of programming, then >> how to use matplotlib, Jupyter notebooks (is this what IPyNBs became?), >> and some descriptive statistics. All this needs to happen within the >> span of a single lecture (tho if people are interested I’ll offer to do >> a few more in our own time), so 45min~1h. >> >> The first problem is installation: apart from me, a Debian user, >> everybody has Windows or Mac laptops, and IDK how you install Python on >> them. I feel like choosing one of the distros is a good idea: I could >> just put the installers on a USB and hand it out, or just send them a >> message with simple steps to follow and set themselves up beforehand. >> Thing is, IDK nothing about distros. Anaconda seems to be the best >> options, but comes with complications like an IDE, as opposed to just >> working with notebooks, and is huge. Also, seems to include R stuff. >> Spyder looks nice, but I don’t want to freak people out with such an >> unfamiliar environment as an IDE just within the first few moments they >> encounter programming. These are all humanities people. Another >> problem is that Anaconda has ‘conda’, a non-standard package manager, >> and I’m kinda vary of introducing that to people: should I talk of pip, >> should I leave it out? I feel like I should just stick to pip and leave >> conda out, but IDK. Python(x,y) is interesting, but it’s apparently >> Py2k only, and that’s a no-no. >> >> So, am I better off telling people to install Anaconda, or plain Py3k + >> a selection of packages (which maybe I make into a .zip or something)? >> >> Then, I need good pointers to hand out: links to good introductions to >> Python, programming, and statistical use of Python. Thing is, I’ve >> always learned the hacker way, i.e. skip the docs, tinker with stuff. >> Thus, IDK of any good resources out of experience, and I want to ask you >> all for some recommendations. I prefer free and tutorial-like stuff, >> but I’ll teach them how to use the stdlib reference too. >> >> What are some good self-teaching material for those who are new to >> programming and Python, and need to mainly do statistics with >> experimental data? >> >> Finally, I’m looking for recommendations on what to show and how. My >> current master plan is >> >> - what’s the use of programming for a linguist >> - an abstract idea of what programming is >> - basic intro to Python syntax >> - demo how to load and clean up some data >> - demo matplotlib >> - demo jupyter notebooks >> - compare with alternatives: R, SPSS, other? >> - briefly refer to libraries for >> - NLP >> - AI? >> - lots of links on >> - how to learn enough coding for number crunching and plotmaking >> - how to make use of stdlib reference >> - how to find and utilise packages and their docs >> - ...? >> >> I plan to produce a handout with all this info neatly organised, and >> just go with a (few) Jupyter notebooks for the rest (resisting hard the >> urge to go in with Emacs Org Mode instead :)). >> >> I’m looking forward to any recommendations from youse. The deadline is >> about a month and a half away, and I really want to give people >> something operationable. People are stuck with BS like SPSS, too simple >> and too pricy, when a few lines of Python (or R) is all they need. I >> came here because IDK teaching about this stuff, and I haven’t left the >> comfort zones of a programmer ever before, so this is some new >> experience for me and I don’t want to botch it. >> >> Thanks a lot in advance, >> >> Göktuğ. >> >> -- >> İ. Göktuğ Kayaalp <https://www.gkayaalp.com/> >> 024C 30DD 597D 142B 49AC >> 40EB 465C D949 B101 2427 >> -- >> https://mail.python.org/mailman/listinfo/python-list >> > -- https://mail.python.org/mailman/listinfo/python-list
