Minor reorganization to improve readability

module2/ressources/jupyter.org

@@ -6,7 +6,7 @@
 #+OPTIONS: num:nil toc:t
 #+PROPERTY: header-args :eval never-export
 
-* 1. Tips and tricks
+* 1. Jupyter Tips and tricks
 The following [[https://www.dataquest.io/blog/jupyter-notebook-tips-tricks-shortcuts/][webpage]] lists several Jupyter tricks (in particular, it
 illustrates many =Ipython magic= commands) that should improve your
 efficiency (note that this blog post is about two years old so some of
@@ -29,29 +29,75 @@ now).
    %%R -i df
    plot(df)
    #+end_src
-Note that this =%%R= notation allows you to use R for the whole cell but
+Note that this =%%R= notation indicates that R should be used for the whole cell but
 an other possibility is to use =%R= to have a single line of R within a
 python cell.
+** Other languages
+For any reason, you may be unsatisfied with the use of R or of
+Python. Many other languages are available:
+[[https://github.com/jupyter/jupyter/wiki/Jupyter-kernels][https://github.com/jupyter/jupyter/wiki/Jupyter-kernels]], including
+non-free languages like SAS, Mathematica, Matlab...
+
+None of these other languages have been deployed in the context of our
+MOOC but you may want to read the next sections to know more about how
+to set up your own Jupyter notebooks on your computer and benefit from these
+extensions.
+* 2. Installing and configuring Jupyter on your computer
+In this Section, we provide information on how to set up on your own
+computer a Jupyter environment similar to the one deployed for this
+MOOC.
+
+Note that Jupyter notebooks are only a small part of the picture and
+that Jupyter is now part of a bigger project: [[https://blog.jupyter.org/jupyterlab-is-ready-for-users-5a6f039b8906][JupyterLab]], which allows
+you to mix various components (including notebooks) in your
+browser. In the context of this MOOC, our time frame was too short to
+benefit from JupyterLab which was still under active development but
+this is probably the best option now if you want to benefit from
+cutting-edge Jupyter notebooks.
+
+** 2.1 Installing Jupyter
+Follow these instructions if you wish to have a Jupyter environment on
+your own computer similar to the one we set up for this MOOC.
 
-* 2. Installing and configuring Jupyter on your machine
-** 2.1 Existing install of Jupyter
+First, download and install the [[https://conda.io/miniconda.html][latest version of Miniconda]]. We use
+Miniconda version =4.5.4= and Python version =3.6= on our server.
+
+Miniconda is a light version of Anaconda, which includes Python, the Jupyter Notebook, and other commonly used packages for scientific computing and data science.
+
+Then download the [[https://gist.github.com/brospars/4671d9013f0d99e1c961482dab533c57][mooc_rr environment file]] and create the environment using conda:
+#+begin_src shell :results output :exports both
+conda env create -f environment.yml
+
+# Windows activate the environment
+activate mooc_rr
+
+# Linux and MacOS activate the environment
+source activate mooc_rr
+
+# Linux, MacOS and Windows: launch the notebook
+jupyter notebook
+#+end_src
+** 2.2 Making sure Jupyter allows you to use R
+The previous environment should ship with R but if you proceeded
+otherwise and only have python available in Jupyter, you may want to
+read the following section.
 *** • Installing [[https://github.com/IRkernel/IRkernel][IRKernel]] (R package)
 Do the following in R console:
 
-Install =devtools= package:
+Install the =devtools= package:
 
 #+begin_src R :results output :session *R* :exports both
 install.packages('devtools',dep=TRUE)
 #+end_src
 
-Define proxy if needed:
+Define a proxy if needed:
 
 #+begin_src R :results output :session *R* :exports both
 library(httr)
 set_config(use_proxy(url="proxy", port=80, username="username", password="password")) 
 #+end_src
 
-Install =IRkernel= package:
+Install the =IRkernel= package:
 
 #+begin_src R :results output :session *R* :exports both
 devtools::install_github('IRkernel/IRkernel')
@@ -59,6 +105,7 @@ IRkernel::installspec()  # to register the kernel in the current R installation
 #+end_src
 
 *** • Installing rpy2 (Python package)
+On Linux, the rpy2 package is available in standard distributions
 #+begin_src shell :results output :exports both
 sudo apt-get install python3-rpy2 python3-tzlocal
 #+end_src
@@ -81,33 +128,10 @@ Install also =tzlocal=:
 #+begin_src shell :results output :exports both
 python -m pip install tzlocal
 #+end_src
-
-** 2.2 New install of Jupyter
-Follow these instructions if you wish to have a Jupyter environment on
-your own machine similar to the one we set up for this MOOC.
-
-First, download and install the [[https://conda.io/miniconda.html][latest version of Miniconda]]. We use
-Miniconda version =4.5.4= and Python version =3.6= on our server.
-
-Miniconda is a light version of Anaconda, which includes Python, the Jupyter Notebook, and other commonly used packages for scientific computing and data science.
-
-Then download the [[https://gist.github.com/brospars/4671d9013f0d99e1c961482dab533c57][mooc_rr environment file]] and create the environment using conda:
-#+begin_src shell :results output :exports both
-conda env create -f environment.yml
-
-# Windows activate the environment
-activate mooc_rr
-
-# Linux and MacOS activate the environment
-source activate mooc_rr
-
-jupyter notebook
-#+end_src
-
 ** 2.3 Additional tips
 *** • Exporting a notebook
-Here is what we had to install on our recent debian machine to make sure
-the notebook export via latex works:
+Here is what we had to install on our recent debian computer to make sure
+the notebook export via LaTeX works:
 #+begin_src shell :results output :exports both
 sudo apt-get install texlive-xetex wkhtmltopdf
 #+end_src
@@ -135,14 +159,6 @@ by choosing the right operating system. You will be prompted to install some spe
 packages when exporting to pdf.
 
 *** • Side note about Jupyter, JupyterLab, JupyterHub...
-Note that Jupyter notebooks are only a small part of the picture and
-that Jupyter is now part of a bigger project: [[https://blog.jupyter.org/jupyterlab-is-ready-for-users-5a6f039b8906][JupyterLab]], which allows
-you to mix various components (including notebooks) in your
-browser. In the context of this MOOC, our time frame was too short to
-benefit from JupyterLab which was still under active development but
-this is probably the best option now if you want to benefit from
-cutting-edge Jupyter notebooks.
-
 *** • Improving notebook readability
 Here are a few extensions that can ease your life:
 - [[https://stackoverflow.com/questions/33159518/collapse-cell-in-jupyter-notebook][Code folding]] to improve readability when browsing the notebook.