From f06dbd7245cab6b62702f958cb41be9d07a7f57b Mon Sep 17 00:00:00 2001 From: Arnaud Legrand Date: Wed, 20 Feb 2019 15:32:58 +0100 Subject: [PATCH] Fix the TOC --- module2/ressources/jupyter.md | 30 +++++++++++++++--------------- module2/ressources/jupyter.org | 20 ++++++++++---------- module2/ressources/jupyter_fr.md | 30 +++++++++++++++--------------- module2/ressources/jupyter_fr.org | 20 ++++++++++---------- 4 files changed, 50 insertions(+), 50 deletions(-) diff --git a/module2/ressources/jupyter.md b/module2/ressources/jupyter.md index b680784..48affe0 100644 --- a/module2/ressources/jupyter.md +++ b/module2/ressources/jupyter.md @@ -7,22 +7,22 @@ Date: Tue Feb 19 15:42:13 2019 Table of Contents ============================================================== -- [1. Jupyter tips and tricks](#1-jupyter-tips-and-tricks) - - [Creating or importing a notebook](#creating-or-importing-a-notebook) - - [Running R and Python in the same notebook](#running-r-and-python-in-the-same-notebook) - - [Other languages](#other-languages) -- [2. Installing and configuring Jupyter on your computer](#2-installing-and-configuring-jupyter-on-your-computer) +- [1 Jupyter tips and tricks](#1-jupyter-tips-and-tricks) + - [1.1 Creating or importing a notebook](#11-creating-or-importing-a-notebook) + - [1.2 Running R and Python in the same notebook](#12-running-r-and-python-in-the-same-notebook) + - [1.3 Other languages](#13-other-languages) +- [2 Installing and configuring Jupyter on your computer](#2-installing-and-configuring-jupyter-on-your-computer) - [2.1 Installing Jupyter](#21-installing-jupyter) - [2.2 Making sure Jupyter allows you to use R](#22-making-sure-jupyter-allows-you-to-use-r) - [2.3 Additional tips](#23-additional-tips) -1. Jupyter tips and tricks -========================== +1 Jupyter tips and tricks +========================= The following [webpage](https://www.dataquest.io/blog/jupyter-notebook-tips-tricks-shortcuts/) 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 the tricks may have been integrated in the default behavior of Jupyter now). -Creating or importing a notebook --------------------------------- +1.1 Creating or importing a notebook +------------------------------------ Using the Jupyter environment we deployed for this MOOC will allow to easily access any file from your default GitLab project. There are situations however where you may want to play with other notebooks. @@ -45,8 +45,8 @@ If your notebook is already in your GitLab project, then simply synchronize by u 3. Then from the top right button, `Upload` the previously downloaded notebook and confirm the upload. 4. Open the freshly uploaded notebook through the Jupyter file manager. -Running R and Python in the same notebook ------------------------------------------ +1.2 Running R and Python in the same notebook +--------------------------------------------- `rpy2` package allows to use both languages in the same notebook by: @@ -72,8 +72,8 @@ Running R and Python in the same notebook 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 ---------------- +1.3 Other languages +------------------- Jupyter is not limited to Pytyhon and R. Many other languages are available: [](https://github.com/jupyter/jupyter/wiki/Jupyter-kernels), including non-free languages like SAS, Mathematica, Matlab... Note that the maturity of these kernels differs widely. @@ -83,8 +83,8 @@ Since the question was asked several times, if you really need to stay with SAS, Since proprietary software such as SAS cannot easily be inspected, we discourage its use as it hinders reproducibility by essence. But perfection does not exist anyway and using Jupyter literate programming approach allied with systematic control version and environment control will certainly help anyway. -2. Installing and configuring Jupyter on your computer -====================================================== +2 Installing and configuring Jupyter on your computer +===================================================== In this section, we explain how to set up a Jupyter environment on your own computer similar to the one deployed for this MOOC. diff --git a/module2/ressources/jupyter.org b/module2/ressources/jupyter.org index 875905f..d3afc58 100644 --- a/module2/ressources/jupyter.org +++ b/module2/ressources/jupyter.org @@ -7,22 +7,22 @@ #+PROPERTY: header-args :eval never-export * Table of Contents :TOC: -- [[#1-jupyter-tips-and-tricks][1. Jupyter tips and tricks]] - - [[#creating-or-importing-a-notebook][Creating or importing a notebook]] - - [[#running-r-and-python-in-the-same-notebook][Running R and Python in the same notebook]] - - [[#other-languages][Other languages]] -- [[#2-installing-and-configuring-jupyter-on-your-computer][2. Installing and configuring Jupyter on your computer]] +- [[#1-jupyter-tips-and-tricks][1 Jupyter tips and tricks]] + - [[#11-creating-or-importing-a-notebook][1.1 Creating or importing a notebook]] + - [[#12-running-r-and-python-in-the-same-notebook][1.2 Running R and Python in the same notebook]] + - [[#13-other-languages][1.3 Other languages]] +- [[#2-installing-and-configuring-jupyter-on-your-computer][2 Installing and configuring Jupyter on your computer]] - [[#21-installing-jupyter][2.1 Installing Jupyter]] - [[#22-making-sure-jupyter-allows-you-to-use-r][2.2 Making sure Jupyter allows you to use R]] - [[#23-additional-tips][2.3 Additional tips]] -* 1. Jupyter 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 the tricks may have been integrated in the default behavior of Jupyter now). -** Creating or importing a notebook +** 1.1 Creating or importing a notebook Using the Jupyter environment we deployed for this MOOC will allow to easily access any file from your default GitLab project. There are situations however where you may want to play with other notebooks. @@ -54,7 +54,7 @@ situations however where you may want to play with other notebooks. notebook and confirm the upload. 4. Open the freshly uploaded notebook through the Jupyter file manager. -** Running R and Python in the same notebook +** 1.2 Running R and Python in the same notebook =rpy2= package allows to use both languages in the same notebook by: 1. Loading =rpy2=: #+begin_src python :results output :exports both @@ -74,7 +74,7 @@ situations however where you may want to play with other notebooks. 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 +** 1.3 Other languages Jupyter is not limited to Pytyhon and R. 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... Note that the maturity of these kernels differs widely. @@ -93,7 +93,7 @@ essence. But perfection does not exist anyway and using Jupyter literate programming approach allied with systematic control version and environment control will certainly help anyway. -* 2. Installing and configuring Jupyter on your computer +* 2 Installing and configuring Jupyter on your computer In this section, we explain how to set up a Jupyter environment on your own computer similar to the one deployed for this MOOC. diff --git a/module2/ressources/jupyter_fr.md b/module2/ressources/jupyter_fr.md index 5346827..ab3aec1 100644 --- a/module2/ressources/jupyter_fr.md +++ b/module2/ressources/jupyter_fr.md @@ -7,22 +7,22 @@ Date: Tue Feb 19 17:43:42 2019 Table of Contents ============================================================== -- [1. Jupyter tips and tricks](#1-jupyter-tips-and-tricks) - - [Creating or importing a notebook](#creating-or-importing-a-notebook) - - [Running R and Python in the same notebook](#running-r-and-python-in-the-same-notebook) - - [Other languages](#other-languages) -- [2. Installing and configuring Jupyter on your computer](#2-installing-and-configuring-jupyter-on-your-computer) +- [1 Jupyter tips and tricks](#1-jupyter-tips-and-tricks) + - [1.1 Creating or importing a notebook](#11-creating-or-importing-a-notebook) + - [1.2 Running R and Python in the same notebook](#12-running-r-and-python-in-the-same-notebook) + - [1.3 Other languages](#13-other-languages) +- [2 Installing and configuring Jupyter on your computer](#2-installing-and-configuring-jupyter-on-your-computer) - [2.1 Installing Jupyter](#21-installing-jupyter) - [2.2 Making sure Jupyter allows you to use R](#22-making-sure-jupyter-allows-you-to-use-r) - [2.3 Additional tips](#23-additional-tips) -1. Jupyter tips and tricks -========================== +1 Jupyter tips and tricks +========================= The following [webpage](https://www.dataquest.io/blog/jupyter-notebook-tips-tricks-shortcuts/) 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 the tricks may have been integrated in the default behavior of Jupyter now). -Creating or importing a notebook --------------------------------- +1.1 Creating or importing a notebook +------------------------------------ Using the Jupyter environment we deployed for this MOOC will allow to easily access any file from your default GitLab project. There are situations however where you may want to play with other notebooks. @@ -45,8 +45,8 @@ If your notebook is already in your GitLab project, then simply synchronize by u 3. Then from the top right button, `Upload` the previously downloaded notebook and confirm the upload. 4. Open the freshly uploaded notebook through the Jupyter file manager. -Running R and Python in the same notebook ------------------------------------------ +1.2 Running R and Python in the same notebook +--------------------------------------------- `rpy2` package allows to use both languages in the same notebook by: @@ -72,8 +72,8 @@ Running R and Python in the same notebook 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 ---------------- +1.3 Other languages +------------------- Jupyter is not limited to Pytyhon and R. Many other languages are available: [](https://github.com/jupyter/jupyter/wiki/Jupyter-kernels), including non-free languages like SAS, Mathematica, Matlab... Note that the maturity of these kernels differs widely. @@ -83,8 +83,8 @@ Since the question was asked several times, if you really need to stay with SAS, Since proprietary software such as SAS cannot easily be inspected, we discourage its use as it hinders reproducibility by essence. But perfection does not exist anyway and using Jupyter literate programming approach allied with systematic control version and environment control will certainly help anyway. -2. Installing and configuring Jupyter on your computer -====================================================== +2 Installing and configuring Jupyter on your computer +===================================================== In this section, we explain how to set up a Jupyter environment on your own computer similar to the one deployed for this MOOC. diff --git a/module2/ressources/jupyter_fr.org b/module2/ressources/jupyter_fr.org index 6406265..fe3ee07 100644 --- a/module2/ressources/jupyter_fr.org +++ b/module2/ressources/jupyter_fr.org @@ -7,22 +7,22 @@ #+PROPERTY: header-args :eval never-export * Table of Contents :TOC: -- [[#1-jupyter-tips-and-tricks][1. Jupyter tips and tricks]] - - [[#creating-or-importing-a-notebook][Creating or importing a notebook]] - - [[#running-r-and-python-in-the-same-notebook][Running R and Python in the same notebook]] - - [[#other-languages][Other languages]] -- [[#2-installing-and-configuring-jupyter-on-your-computer][2. Installing and configuring Jupyter on your computer]] +- [[#1-jupyter-tips-and-tricks][1 Jupyter tips and tricks]] + - [[#11-creating-or-importing-a-notebook][1.1 Creating or importing a notebook]] + - [[#12-running-r-and-python-in-the-same-notebook][1.2 Running R and Python in the same notebook]] + - [[#13-other-languages][1.3 Other languages]] +- [[#2-installing-and-configuring-jupyter-on-your-computer][2 Installing and configuring Jupyter on your computer]] - [[#21-installing-jupyter][2.1 Installing Jupyter]] - [[#22-making-sure-jupyter-allows-you-to-use-r][2.2 Making sure Jupyter allows you to use R]] - [[#23-additional-tips][2.3 Additional tips]] -* 1. Jupyter 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 the tricks may have been integrated in the default behavior of Jupyter now). -** Creating or importing a notebook +** 1.1 Creating or importing a notebook Using the Jupyter environment we deployed for this MOOC will allow to easily access any file from your default GitLab project. There are situations however where you may want to play with other notebooks. @@ -54,7 +54,7 @@ situations however where you may want to play with other notebooks. notebook and confirm the upload. 4. Open the freshly uploaded notebook through the Jupyter file manager. -** Running R and Python in the same notebook +** 1.2 Running R and Python in the same notebook =rpy2= package allows to use both languages in the same notebook by: 1. Loading =rpy2=: #+begin_src python :results output :exports both @@ -74,7 +74,7 @@ situations however where you may want to play with other notebooks. 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 +** 1.3 Other languages Jupyter is not limited to Pytyhon and R. 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... Note that the maturity of these kernels differs widely. @@ -93,7 +93,7 @@ essence. But perfection does not exist anyway and using Jupyter literate programming approach allied with systematic control version and environment control will certainly help anyway. -* 2. Installing and configuring Jupyter on your computer +* 2 Installing and configuring Jupyter on your computer In this section, we explain how to set up a Jupyter environment on your own computer similar to the one deployed for this MOOC. -- 2.18.1