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swc-bb
swc-lessons
python-notebooks
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9c268993
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9c268993
authored
Oct 13, 2017
by
Frank Hellmann
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GitHub
Oct 13, 2017
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Update to outline Meeting 13.10.
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9c268993
# Python lesson outline
## Target audience
-
knows what a loop is/some experience in any language
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no python experience required
## Targets for the course
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Structure your code (functions and modules, everything else is out of scope)
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@@ -25,8 +30,9 @@
### Session PM2 Python Intro (basic overview) (Sebastian)
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python+anaconda+conda+jupyter+history
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(notebooks vs. interpreter vs. scripts)
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python
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anaconda+conda+jupyter+history(+dependencies)
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notebooks vs. interpreter vs. scripts (sehr kurz)
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object types (string, number, boolean, complex, etc) and operators
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data structures (tuples, lists, dicts, nparrays, panda.df, etc)
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list comprehensions
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@@ -35,7 +41,7 @@
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control flow: loops + conditionals
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(code indentation)
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numpy
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(io)
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(io
, for example simply iterating over a csv we will use later
)
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read file, simple plot (or in session PM2)
### What is missing?
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@@ -49,14 +55,22 @@
### Session AM1 Python (structuring code, defensive programming, using prepared ts files) (Frank)
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write function + module
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put under version control
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simple test (assert)
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documentation
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write script + call from bash
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traceback, errors
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numpy
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%timeit and numba
not covered: closures, argpars, numba
### Session AM2: Time series, functions, plotting (Robert)
### Session AM2: (Tim, Marius)
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simple test (assert)
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## DAY 2 PM
### Session PM1: Time series, functions, plotting (Robert)
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reading + understanding documentation of functions
Global temperature average development 1750-2010
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@@ -68,18 +82,14 @@ http://berkeleyearth.lbl.gov/auto/Global/Raw_TAVG_complete.txt
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plot with uncertainty band
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write function (exercise!)
## DAY 2 PM
### Session PM1: higher dimensional (spatial) data, advanced plotting + cartography, application of aquired knowledge (Joachim/Benoit?)
gridded data Europe:
### Session PM2: Git in practice (optional if we ran out of time)
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Joachim zeigt higher dimensional (spatial) data, advanced plotting + cartography (tool showcase)
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read netcdf file
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plot map of one time slice
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now compare plot with given cuteplot function by Joachim
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extract time series Potsdam
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compare with global average from Berkeley
### Session PM2: Git in practice (optional if we ran out of time)
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use git: final commit
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create github/gitlab account + create repos + add remote
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git push + inspect online
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