initial commit

outline.md

+# swc workshop 2017 Fall
+
+## Open questions
+
+Frank: formulate targets (Python specific)
+Stefan/Marvin/Peter/Martin: how(+why) to integrate shell usage in later R sessions
+?: prepare time series files
+Stefan/Marvin: if + where to introduce tidyverse
+
+
+## DAY 1 AM --- both
+
+### Session AM1 (get started, know what we're doing these days)
+- intro
+- lightning talks participants 
+- course outline
+
+### Session AM2 (basic concepts, reasons why, basis for later use cases)
+- shell 
+- git 
+
+Each shorter than spring 2017, will be picked up in later sessions
+
+
+## DAY 1 PM --- Python
+
+### Session PM1 Python Intro (basic overview)
+- python+anaconda+conda+jupyter+history
+- operators, data structures (tuples, lists, dicts, nparrays, panda.df, etc)
+- object types (string, number, boolean, complex, etc)
+- provided functions + methods, atrributes
+- control flows: loops + conditions
+- numpy
+- read file, simple plot (or in session PM2)
+
+### Session PM2 Python (structuring code, defensive programming, using prepared ts files)
+- write function + module
+- put under version control
+- simple test (assert)
+- documentation
+- write script + call from bash
+- traceback, errors
+
+not covered: closures, argpars, numba
+
+
+
+
+## DAY 1 PM --- R
+
+### Session PM1 R Intro (basic intro)
+- R+Rstudio+CRAN+history
+- operators, vector, df, object structures (vector,df,list,other), read file, subset df
+- object class (string, number, boolean, complex, etc)
+- simple plot
+- read help for functions
+- install.packages, library + fun vs pack::fun
+
+### Session PM2 R (overview of code structuring)
+- conditions, loops, *apply
+- write function (with comments for documentation)
+- put under version control
+- simple test (testthat)
+
+not covered: package with structured documentation with devtools/Roxygen/sinew (but link to https://github.com/brry/course#packs)
+
+
+
+
+## DAY 2 AM --- both
+
+### Session AM1: Time series, functions, plotting
+- reading + understanding documentation of functions
+
+Global temperature average development 1750-2010
+http://berkeleyearth.lbl.gov/auto/Global/Raw_TAVG_complete.txt
+
+- download file (optional: call shell with wget from python/R)
+- read, process
+- moving average
+- plot with uncertainty band
+- write function (exercise!)
+
+### Session AM2:
+using shell:
+
+- if possible: get list of available files in http://berkeleyearth.lbl.gov/auto/Regional/TAVG/Text/
+- with wget: Get all textfiles (country temp development) starting with B (or with >3 consonants or whatever)
+- apply function to several textfiles
+
+Mix:
+
+- Python: APIs: numpy, pandas, xarray
+- R: Tidyverse?
+- BUFFER (previous sessions potentially too full)
+
+## DAY 2 PM --- both
+
+### Session PM1: higher dimensional (spatial) data, advanced plotting + cartography, application of aquired knowledge
+gridded data Europe: 
+
+- read netcdf file
+- plot map of one time slice 
+- now compare plot with given cuteplot function by Joachim
+- extract time series Potsdam
+- compare with global average from Berkeley
+
+### Session PM2: Git in practice (optional if we ran out of time)
+- use git: final commit
+- create github/gitlab account + create repos + add remote
+- git push + inspect online
+- github/gitlab release
+- outro, feedback
+