diff --git a/PreStSauveur/TESL/Polynomes_derivation/exercises/T1_etude_sgn-exercise-1-exercise-body.tex b/PreStSauveur/TESL/Polynomes_derivation/exercises/T1_etude_sgn-exercise-1-exercise-body.tex
new file mode 100644
index 0000000..6a2e4ef
--- /dev/null
+++ b/PreStSauveur/TESL/Polynomes_derivation/exercises/T1_etude_sgn-exercise-1-exercise-body.tex
@@ -0,0 +1,18 @@
+% ------------------------------------------------------------------------
+% file `T1_etude_sgn-exercise-1-exercise-body.tex'
+%   in folder `exercises/'
+%
+%     exercise of type `exercise' with id `1'
+%
+% generated by the `exercise' environment of the
+%   `xsim' package v0.11 (2018/02/12)
+% from source `T1_etude_sgn' on 2018/09/07 on line 55
+% ------------------------------------------------------------------------
+    Tracer le tableau de signe des polynômes suivants
+    \begin{multicols}{3}
+        \begin{enumerate}
+            \item $a(x) = 3x^2 + 2x - 5$
+            \item $b(x) = x^2 + 2x + 1$
+            \item $c(x) = -x^2 + 5x$
+        \end{enumerate}
+    \end{multicols}
diff --git a/PreStSauveur/TESL/Polynomes_derivation/exercises/T1_etude_sgn-exercise-2-exercise-body.tex b/PreStSauveur/TESL/Polynomes_derivation/exercises/T1_etude_sgn-exercise-2-exercise-body.tex
new file mode 100644
index 0000000..de51963
--- /dev/null
+++ b/PreStSauveur/TESL/Polynomes_derivation/exercises/T1_etude_sgn-exercise-2-exercise-body.tex
@@ -0,0 +1,18 @@
+% ------------------------------------------------------------------------
+% file `T1_etude_sgn-exercise-2-exercise-body.tex'
+%   in folder `exercises/'
+%
+%     exercise of type `exercise' with id `2'
+%
+% generated by the `exercise' environment of the
+%   `xsim' package v0.11 (2018/02/12)
+% from source `T1_etude_sgn' on 2018/09/07 on line 67
+% ------------------------------------------------------------------------
+    Résoudre les équations suivantes
+    \begin{multicols}{3}
+        \begin{enumerate}
+            \item $4x^2 -  5x + 3 > 0$
+            \item $5x + 3 > 6x - 3$
+            \item $4x^2 -  5x + 3 > 0$
+        \end{enumerate}
+    \end{multicols}
diff --git a/tools/README.rst b/tools/README.rst
new file mode 100644
index 0000000..9c6e7ba
--- /dev/null
+++ b/tools/README.rst
@@ -0,0 +1,50 @@
+Logique et organisation des styles Latex
+########################################
+
+:date: 2017-06-08
+:modified: 2017-06-08
+:tags: Outils
+:category: Autres
+:authors: Bertrand Benjamin
+:summary: Explications autour des classes latex utilisées.
+
+
+Pour profiter des classes
+-------------------------
+
+    export TEXINPUTS=".:/chemin/vers/fichiers/tools/style//::"
+
+Pour moi
+
+    export TEXINPUTS=".:/media/documents/Cours/Prof/Enseignements/2017-2018/tools/style//::"
+
+
+Description des classes
+-----------------------
+
+
+Les propriétés globables et les racourcis sont définis dans `base.sty <style/base.sty>`_.
+
+Les couleurs sont définies dans `theme.sty <style/theme.sty>`_.
+
+Classes latex
+-------------
+
+* classCours: (dérivée de la classe de base Article): Classe adapté pour les cours
+* classConn: Classe pour les petits contrôles de connaissances de début de cours.
+* Exo et DS: Classe pour les fiches d'exercices et les devoirs
+* classReport
+
+
+DS, DM, examen, etc
+^^^^^^^^^^^^^^^^^^^
+
+Toutes ces classes dérivent de la classe `Exam <http://www.ctan.org/tex-archive/macros/latex/contrib/exam/>`_. Ce qui permet de bénéficier de la gestion des exercices, des points etc.
+
+On y a ajouter quelques commande pour produire un titre ou un page de garde (pour les examens en particulier). Pour cela quelques éléments doivent être définis
+
+* :code:`\titre{...}` le titre du document
+* :code:`\duree{...}` Définit le temps pour faire le devoir.
+* :code:`\sujet{...}` Pour produire différentes versions d'un sujet
+* :code:`\ptpres{...}` Points de présentation (/!\ n'apparaît pas dans la page de présentation si l'on veut faire le total des points)
+
diff --git a/tools/example/Conn.pdf b/tools/example/Conn.pdf
new file mode 100644
index 0000000..9f2d397
Binary files /dev/null and b/tools/example/Conn.pdf differ
diff --git a/tools/example/Conn.tex b/tools/example/Conn.tex
new file mode 100644
index 0000000..602aa47
--- /dev/null
+++ b/tools/example/Conn.tex
@@ -0,0 +1,52 @@
+\documentclass{classConn}
+
+
+% Title Page
+\title{}
+\author{}
+\date{Aujourd'hui}
+\classe{Une classe}
+
+
+\begin{document}
+
+    
+\sujet
+
+\begin{Exo}
+		Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod
+		tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At
+		vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren,
+		no sea takimata sanctus est Lorem ipsum dolor sit amet.
+\end{Exo}
+
+
+\begin{Exo}
+		Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod
+		tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At
+		vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren,
+		no sea takimata sanctus est Lorem ipsum dolor sit amet.
+\end{Exo}
+
+\sujet
+
+\begin{Exo}
+		Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod
+		tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At
+		vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren,
+		no sea takimata sanctus est Lorem ipsum dolor sit amet.
+\end{Exo}
+
+\begin{Exo}
+		Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod
+		tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At
+		vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren,
+		no sea takimata sanctus est Lorem ipsum dolor sit amet.
+\end{Exo}
+
+\end{document}
+
+%%% Local Variables: 
+%%% mode: latex
+%%% TeX-master: "master"
+%%% End:
diff --git a/tools/example/DS.pdf b/tools/example/DS.pdf
new file mode 100644
index 0000000..1aeaa71
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diff --git a/tools/example/DS.tex b/tools/example/DS.tex
new file mode 100644
index 0000000..84ae2a3
--- /dev/null
+++ b/tools/example/DS.tex
@@ -0,0 +1,98 @@
+\documentclass[a4paper,12pt]{article}
+\usepackage{myXsim}
+
+\title{DS}
+\date{date}
+\tribe{Classe}
+\duree{durée}
+
+\begin{document}
+\maketitle
+
+\begin{exercise}[ subtitle={\Com} ]
+    \begin{enumerate}
+        \item x, $x$ et $\times$
+        \item Ensembles
+            \begin{itemize}
+                \item \verb"\N" $\N$
+                \item \verb"\Z" $\Z$
+                \item \verb"\Q" $\Q$
+                \item \verb"\R" $\R$
+                \item \verb"\C" $\C$
+            \end{itemize}
+        \item Intervalles
+            \begin{itemize}
+                \item \verb"\intOO{1}{2}" $\intOO{1}{2}$
+                \item \verb"\intOF{1}{2}" $\intOF{1}{2}$
+                \item \verb"\intFO{1}{2}" $\intFO{1}{2}$
+                \item \verb"\intFF{1}{2}" $\intFF{1}{2}$
+            \end{itemize}
+        \item Logique
+            \begin{itemize}
+                \item \verb"\equiv" $\equiv$
+            \end{itemize}
+        \item Vecteurs
+            \begin{itemize}
+                \item \verb"\vec{A}" $\vec{AB}$
+                \item \verb"\norme{AB}" $\norme{AB}$
+                \item \verb"\scal{u}{u}" $\scal{u}{v} $
+                \item \verb"\vectCoord{1}{2}" $\vectCoord{1}{2}$ 
+            \end{itemize}
+        \item Proba
+            \begin{itemize}
+                \item \verb"\coefBino{20}{2}" $\coefBino{20}{2}$
+            \end{itemize}
+        \item Les compétences
+            \begin{itemize}
+                \item Connaître \Con
+                \item Chercher \Cher
+                \item Modéliser \Mod
+                \item Représenter \Rep
+                \item Raisonner \Rai
+                \item Calculer \Cal
+                \item Communiquer \Com
+            \end{itemize}
+    \end{enumerate}
+\end{exercise}
+
+\pagebreak
+
+\begin{exercise}[subtitle={\Mod}]
+    \begin{enumerate}
+        \item
+            Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod
+            tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At
+            vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren,
+            no sea takimata sanctus est Lorem ipsum dolor sit amet.
+        \item
+            Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod
+            tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At
+            vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren,
+            no sea takimata sanctus est Lorem ipsum dolor sit amet.
+        \item
+            \begin{enumerate}
+                \item 
+                    Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod
+                    tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At
+                    vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren,
+                    no sea takimata sanctus est Lorem ipsum dolor sit amet.
+                \item 
+                    Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod
+                    tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At
+                    vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren,
+                    no sea takimata sanctus est Lorem ipsum dolor sit amet.
+                \item 
+                    Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod
+                    tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At
+                    vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren,
+                    no sea takimata sanctus est Lorem ipsum dolor sit amet.
+            \end{enumerate}
+    \end{enumerate}
+\end{exercise}
+\end{document}
+
+%%% Local Variables: 
+%%% mode: latex
+%%% TeX-master: "master"
+%%% End:
+
diff --git a/tools/example/examen.pdf b/tools/example/examen.pdf
new file mode 100644
index 0000000..3715a87
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diff --git a/tools/example/examen.tex b/tools/example/examen.tex
new file mode 100644
index 0000000..f4ba14d
--- /dev/null
+++ b/tools/example/examen.tex
@@ -0,0 +1,42 @@
+\documentclass[a4paper,12pt]{article}
+\usepackage{myXsim}
+
+\author{}
+\date{date}
+\title{Examen}
+\tribe{Classe}
+\duree{2heures}
+
+\begin{document}
+
+\titlepage
+
+Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod
+tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At
+vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren,
+no sea takimata sanctus est Lorem ipsum dolor sit amet.
+
+\begin{exercise}[subtitle=Chipo, points=3]
+    \begin{enumerate}
+        \item (\addpoints{1.4}) Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod
+        \item \addpoints*{2} tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At
+        \item  vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren,
+        \item no sea takimata sanctus est Lorem ipsum dolor sit amet.
+    \end{enumerate}
+\end{exercise}
+
+\begin{exercise}[subtitle=Plop, points=2]
+		Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod
+		tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At
+		vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren,
+		no sea takimata sanctus est Lorem ipsum dolor sit amet.
+\end{exercise}
+
+
+\end{document}
+
+%%% Local Variables: 
+%%% mode: latex
+%%% TeX-master: "master"
+%%% End:
+
diff --git a/tools/example/exo.pdf b/tools/example/exo.pdf
new file mode 100644
index 0000000..ac6b977
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diff --git a/tools/example/exo.tex b/tools/example/exo.tex
new file mode 100644
index 0000000..c95bef1
--- /dev/null
+++ b/tools/example/exo.tex
@@ -0,0 +1,75 @@
+\documentclass[a4paper,12pt,landscape, twocolumn]{article}
+\usepackage{myXsim}
+
+\author{}
+\date{date}
+\title{Titre}
+\tribe{Classe}
+
+\begin{document}
+
+\begin{exercise}[subtitle={\Com\Cher[scale=0.3]}]
+    
+        \begin{enumerate}
+            \item
+		Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod
+		tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At
+		vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren,
+		no sea takimata sanctus est Lorem ipsum dolor sit amet.
+            \item
+		Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod
+		tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At
+		vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren,
+		no sea takimata sanctus est Lorem ipsum dolor sit amet.
+            \item
+            \begin{enumerate}
+                \item 
+		Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod
+		tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At
+		vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren,
+		no sea takimata sanctus est Lorem ipsum dolor sit amet.
+                \item 
+		Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod
+		tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At
+		vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren,
+		no sea takimata sanctus est Lorem ipsum dolor sit amet.
+                \item 
+		Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod
+		tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At
+		vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren,
+		no sea takimata sanctus est Lorem ipsum dolor sit amet.
+            \end{enumerate}
+            
+        \end{enumerate}
+\end{exercise}
+
+\eject
+
+\begin{exercise}
+
+    Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod
+    tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At
+    vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren,
+    no sea takimata sanctus est Lorem ipsum dolor sit amet.
+\end{exercise}
+
+\begin{exercise}
+    Coucou
+\end{exercise}
+
+\begin{exercise}
+    Coucou
+\end{exercise}
+
+\begin{exercise}[subtitle={Design}]
+    Plot
+\end{exercise}
+
+
+\end{document}
+
+%%% Local Variables: 
+%%% mode: latex
+%%% TeX-master: "master"
+%%% End:
+
diff --git a/tools/example/presentation.pdf b/tools/example/presentation.pdf
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index 0000000..0a7f2c7
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diff --git a/tools/example/presentation.tex b/tools/example/presentation.tex
new file mode 100755
index 0000000..572f960
--- /dev/null
+++ b/tools/example/presentation.tex
@@ -0,0 +1,44 @@
+\documentclass[a4paper,10pt,xcolor=table]{classPres}
+
+\author{}
+\title{}
+\date{}
+
+\begin{document}
+    
+\begin{frame}{Une slide}
+
+    \begin{Exo}
+        \begin{enumerate}
+            \item 
+		Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod
+		tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At
+		vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren,
+    \item
+		Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod
+		tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At
+    \item
+            \begin{enumerate}
+                \item
+		Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod
+		tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At
+		vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren,
+    \item
+		Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod
+		tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At
+		vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren,
+    \item
+		Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod
+		tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua. At
+		vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren,
+            \end{enumerate}
+            
+        \end{enumerate}
+        
+    \end{Exo}
+    
+\end{frame}
+
+
+
+\end{document}
diff --git a/tools/example/report.pdf b/tools/example/report.pdf
new file mode 100644
index 0000000..9e1b99f
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diff --git a/tools/example/report.tex b/tools/example/report.tex
new file mode 100644
index 0000000..817cae7
--- /dev/null
+++ b/tools/example/report.tex
@@ -0,0 +1,73 @@
+\documentclass[a5paper,12pt]{article}
+\usepackage{myXsim}
+
+\title{Devoir surveillé n}
+\tribe{Une classe}
+\date{10 mars 2015}
+
+
+\begin{document}
+
+\maketitle
+
+\begin{minipage}{0.5\linewidth}
+    \Large
+    Nom
+
+    Prénom
+    
+\end{minipage}
+\begin{minipage}{0.3\linewidth}
+    \begin{flushright}
+        \Huge 15 / 20
+    \end{flushright}
+\end{minipage}
+
+\vfill
+
+\fbox{%
+    \begin{minipage}{0.9\linewidth}
+        \hfill
+        \vspace{2cm}
+    \end{minipage}
+}
+
+\vfill
+\begin{tabular}{|p{3cm}|p{3cm}|p{3cm}|}
+    \hline
+    \rowcolor{highlightbg} Exercices & Barème & réussite \\
+    \hline
+     Exercice 1 & 10 & 9 \\
+    \hline
+    1 & 1 & \RepLevel{.} \\
+    \hline
+    2 & 1 & \RepLevel{0} \\
+    \hline
+    3 & 1 & \RepLevel{1} \\
+    \hline
+    3 & 1 & \RepLevel{2} \\
+    \hline
+    3 & 1 & \RepLevel{3} \\
+    \hline
+\end{tabular}
+
+\vfill
+
+Bilan par compétences
+
+\begin{itemize}
+    \item \Cher Chercher: \Assesment{0}
+    \item \Mod Modéliser: \Assesment{1}
+    \item \Rep Représente: \Assesment{2}
+    \item \Rai Raisonner: \Assesment{3}
+\end{itemize}
+
+\pagebreak
+
+\end{document}
+
+%%% Local Variables: 
+%%% mode: latex
+%%% TeX-master: "master"
+%%% End:
+
diff --git a/tools/skeleton/Bilan.ipynb b/tools/skeleton/Bilan.ipynb
new file mode 100644
index 0000000..10ccc7f
--- /dev/null
+++ b/tools/skeleton/Bilan.ipynb
@@ -0,0 +1,1929 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 90,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "from opytex import texenv\n",
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "plt.style.use(\"seaborn-notebook\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Informations sur le devoir"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'classe': '', 'date': '', 'titre': ''}"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_name = \"\"\n",
+    "classe = \"\"\n",
+    "\n",
+    "latex_info = {}\n",
+    "latex_info['titre'] =  \"\"\n",
+    "latex_info['classe'] = \"\"\n",
+    "latex_info['date'] = \"\"\n",
+    "latex_info"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Import et premiers traitements"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "notes = pd.ExcelFile(\"./../../../../notes/\"+classe+\".xlsx\")\n",
+    "notes.sheet_names\n",
+    "notes = notes.parse(ds_name)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['BB_16_01_23', 'Présentation', 'Exercice 1', 'Réponse', 'Rédaction',\n",
+       "       'Exercice 2', '1. Developper', '2. Evaluer', 'Exercice 3',\n",
+       "       'Comparaison', 'Pythagore', 'Thalès', 'Exercice 4', '1. Lecture',\n",
+       "       '2. Max', '3. Moyenne', '4. Etendue', '5. Médiane', 'Exercice 5',\n",
+       "       '1. Opérations', '2. Équation', '3. Probabilité', 'Exercice 6',\n",
+       "       '1. Tableur', '2. Tableur', '3. PGCD', '4. Fraction',\n",
+       "       'Exercice 7 (QCM)'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "notes.index"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "notes = notes.T"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "#notes = notes.drop('av_arrondi', axis=1)\n",
+    "#notes = notes.drop('num_sujet', axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "barem = notes[:1]\n",
+    "notes = notes[1:]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>BB_16_01_23</th>\n",
+       "      <th>Présentation</th>\n",
+       "      <th>Exercice 1</th>\n",
+       "      <th>Réponse</th>\n",
+       "      <th>Rédaction</th>\n",
+       "      <th>Exercice 2</th>\n",
+       "      <th>1. Developper</th>\n",
+       "      <th>2. Evaluer</th>\n",
+       "      <th>Exercice 3</th>\n",
+       "      <th>Comparaison</th>\n",
+       "      <th>...</th>\n",
+       "      <th>Exercice 5</th>\n",
+       "      <th>1. Opérations</th>\n",
+       "      <th>2. Équation</th>\n",
+       "      <th>3. Probabilité</th>\n",
+       "      <th>Exercice 6</th>\n",
+       "      <th>1. Tableur</th>\n",
+       "      <th>2. Tableur</th>\n",
+       "      <th>3. PGCD</th>\n",
+       "      <th>4. Fraction</th>\n",
+       "      <th>Exercice 7 (QCM)</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>ABDOU Farida</th>\n",
+       "      <td>22.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2.333333</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6.333333</td>\n",
+       "      <td>1</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ABOU BACAR Djaha</th>\n",
+       "      <td>20.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.666667</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4.000000</td>\n",
+       "      <td>3</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>1</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>AHAMADA Nabaouya</th>\n",
+       "      <td>23.0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.666667</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4.333333</td>\n",
+       "      <td>1</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4.5</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>AHAMADI Faina</th>\n",
+       "      <td>9.0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ALI Mardhuia</th>\n",
+       "      <td>20.5</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1.666667</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4.000000</td>\n",
+       "      <td>3</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2.5</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ALI SOULAIMANA Chamsia</th>\n",
+       "      <td>24.0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1.666667</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6.333333</td>\n",
+       "      <td>1</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3.5</td>\n",
+       "      <td>3</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ALSENE ALI MADI Stela</th>\n",
+       "      <td>14.5</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2.666667</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ANDRIATAHIANA Hoby</th>\n",
+       "      <td>22.5</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.666667</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2.5</td>\n",
+       "      <td>2</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ANLI Emeline</th>\n",
+       "      <td>13.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ATHOUMANE Naouidat</th>\n",
+       "      <td>19.5</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1.666667</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.666667</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5.666667</td>\n",
+       "      <td>2</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>BOUDRA Nassifanya</th>\n",
+       "      <td>27.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1.666667</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6.000000</td>\n",
+       "      <td>3</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5.5</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>CHANFI Nadhrati</th>\n",
+       "      <td>10.5</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>COMBO Moinécha</th>\n",
+       "      <td>26.0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1.666667</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2.666667</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>HALIDI Nisma</th>\n",
+       "      <td>26.0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6.333333</td>\n",
+       "      <td>1</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>4.5</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>HAMZA Samianti</th>\n",
+       "      <td>16.0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>1</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>HOUMADI Mouslimati</th>\n",
+       "      <td>17.0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.333333</td>\n",
+       "      <td>1</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>HOUMADI Chaharazadi</th>\n",
+       "      <td>22.0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>HOUMADI Nasmi</th>\n",
+       "      <td>20.0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>1</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4.5</td>\n",
+       "      <td>3</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>HOUMADI Dhoirfia</th>\n",
+       "      <td>21.5</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>5.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>LOUTOUFI Nachima</th>\n",
+       "      <td>14.5</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1.666667</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>1</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>MALIDE El-Anzize</th>\n",
+       "      <td>18.5</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>6.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>MONNE Kevin</th>\n",
+       "      <td>24.0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1.666667</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2.666667</td>\n",
+       "      <td>2</td>\n",
+       "      <td>...</td>\n",
+       "      <td>4.000000</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>3.5</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>MOUSSA Roibouanti</th>\n",
+       "      <td>24.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1.666667</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>3.333333</td>\n",
+       "      <td>1</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3.5</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>OUSSENI Hilma</th>\n",
+       "      <td>18.0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.5</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SAANLI Natali</th>\n",
+       "      <td>31.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>6.666667</td>\n",
+       "      <td>2</td>\n",
+       "      <td>...</td>\n",
+       "      <td>4.000000</td>\n",
+       "      <td>2</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4.5</td>\n",
+       "      <td>3</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SAID AHAMADA Roukaya</th>\n",
+       "      <td>20.5</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1.666667</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4.5</td>\n",
+       "      <td>3</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SANDA Issoufi</th>\n",
+       "      <td>13.0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1.666667</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SOILIHI Soifia</th>\n",
+       "      <td>20.5</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1.333333</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2.333333</td>\n",
+       "      <td>1</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SOUFIANI Laila</th>\n",
+       "      <td>10.5</td>\n",
+       "      <td>4</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>YOUSSOUF Sitirati</th>\n",
+       "      <td>10.5</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.333333</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.666667</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>30 rows × 28 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                        BB_16_01_23  Présentation  Exercice 1  Réponse  \\\n",
+       "ABDOU Farida                   22.0             3    2.333333        3   \n",
+       "ABOU BACAR Djaha               20.0             3    1.333333        2   \n",
+       "AHAMADA Nabaouya               23.0             4    1.000000        1   \n",
+       "AHAMADI Faina                   9.0             4    0.666667        0   \n",
+       "ALI Mardhuia                   20.5             4    1.666667        3   \n",
+       "ALI SOULAIMANA Chamsia         24.0             4    1.666667        3   \n",
+       "ALSENE ALI MADI Stela          14.5             4    1.333333        2   \n",
+       "ANDRIATAHIANA Hoby             22.5             4    1.333333        2   \n",
+       "ANLI Emeline                   13.0             3    0.666667        0   \n",
+       "ATHOUMANE Naouidat             19.5             4    1.666667        3   \n",
+       "BOUDRA Nassifanya              27.0             3    1.666667        3   \n",
+       "CHANFI Nadhrati                10.5             4    0.666667        0   \n",
+       "COMBO Moinécha                 26.0             2    1.666667        3   \n",
+       "HALIDI Nisma                   26.0             4    1.000000        1   \n",
+       "HAMZA Samianti                 16.0             4    0.666667        0   \n",
+       "HOUMADI Mouslimati             17.0             2    1.333333        2   \n",
+       "HOUMADI Chaharazadi            22.0             4    1.333333        2   \n",
+       "HOUMADI Nasmi                  20.0             4    1.333333        2   \n",
+       "HOUMADI Dhoirfia               21.5             3    1.333333        2   \n",
+       "LOUTOUFI Nachima               14.5             4    1.666667        3   \n",
+       "MALIDE El-Anzize               18.5             4    1.000000        1   \n",
+       "MONNE Kevin                    24.0             4    1.666667        3   \n",
+       "MOUSSA Roibouanti              24.0             3    1.666667        3   \n",
+       "OUSSENI Hilma                  18.0             4    1.333333        2   \n",
+       "SAANLI Natali                  31.0             3    3.000000        3   \n",
+       "SAID AHAMADA Roukaya           20.5             4    0.000000      NaN   \n",
+       "SANDA Issoufi                  13.0             4    1.666667        3   \n",
+       "SOILIHI Soifia                 20.5             4    1.333333        2   \n",
+       "SOUFIANI Laila                 10.5             4    0.666667        0   \n",
+       "YOUSSOUF Sitirati              10.5             4    1.000000        1   \n",
+       "\n",
+       "                        Rédaction  Exercice 2  1. Developper  2. Evaluer  \\\n",
+       "ABDOU Farida                    2    0.666667              1           0   \n",
+       "ABOU BACAR Djaha                1    1.666667              2           1   \n",
+       "AHAMADA Nabaouya                1    1.666667              2           1   \n",
+       "AHAMADI Faina                   1    1.000000              1           1   \n",
+       "ALI Mardhuia                    1    1.000000              1           1   \n",
+       "ALI SOULAIMANA Chamsia          1    1.333333              2           0   \n",
+       "ALSENE ALI MADI Stela           1    1.000000              1           1   \n",
+       "ANDRIATAHIANA Hoby              1    1.666667              2           1   \n",
+       "ANLI Emeline                    1    0.333333              0           1   \n",
+       "ATHOUMANE Naouidat              1    1.666667              2           1   \n",
+       "BOUDRA Nassifanya               1    2.000000              3           0   \n",
+       "CHANFI Nadhrati                 1    0.000000              0           0   \n",
+       "COMBO Moinécha                  1    0.666667              1           0   \n",
+       "HALIDI Nisma                    1    0.000000              0           0   \n",
+       "HAMZA Samianti                  1    2.000000              3           0   \n",
+       "HOUMADI Mouslimati              1    0.666667              1           0   \n",
+       "HOUMADI Chaharazadi             1    1.000000              1           1   \n",
+       "HOUMADI Nasmi                   1    1.000000              1           1   \n",
+       "HOUMADI Dhoirfia                1    1.333333              2           0   \n",
+       "LOUTOUFI Nachima                1    0.333333              0           1   \n",
+       "MALIDE El-Anzize                1    0.333333              0           1   \n",
+       "MONNE Kevin                     1    1.000000              1           1   \n",
+       "MOUSSA Roibouanti               1    2.000000              2           2   \n",
+       "OUSSENI Hilma                   1    0.666667              1           0   \n",
+       "SAANLI Natali                   3    2.000000              2           2   \n",
+       "SAID AHAMADA Roukaya          NaN    1.666667              2           1   \n",
+       "SANDA Issoufi                   1    0.333333              0           1   \n",
+       "SOILIHI Soifia                  1    0.666667              1           0   \n",
+       "SOUFIANI Laila                  1    0.333333              0           1   \n",
+       "YOUSSOUF Sitirati               1    0.333333              0           1   \n",
+       "\n",
+       "                        Exercice 3  Comparaison        ...         Exercice 5  \\\n",
+       "ABDOU Farida              6.333333            1        ...           0.000000   \n",
+       "ABOU BACAR Djaha          4.000000            3        ...           0.666667   \n",
+       "AHAMADA Nabaouya          4.333333            1        ...           0.000000   \n",
+       "AHAMADI Faina             0.000000            0        ...           0.666667   \n",
+       "ALI Mardhuia              4.000000            3        ...           1.333333   \n",
+       "ALI SOULAIMANA Chamsia    6.333333            1        ...           0.666667   \n",
+       "ALSENE ALI MADI Stela     2.000000          NaN        ...           2.666667   \n",
+       "ANDRIATAHIANA Hoby        3.000000          NaN        ...           1.333333   \n",
+       "ANLI Emeline              1.000000          NaN        ...           0.000000   \n",
+       "ATHOUMANE Naouidat        5.666667            2        ...           0.000000   \n",
+       "BOUDRA Nassifanya         6.000000            3        ...           1.333333   \n",
+       "CHANFI Nadhrati           0.000000          NaN        ...           0.666667   \n",
+       "COMBO Moinécha            6.000000            0        ...           2.666667   \n",
+       "HALIDI Nisma              6.333333            1        ...           2.000000   \n",
+       "HAMZA Samianti            0.333333            1        ...           0.000000   \n",
+       "HOUMADI Mouslimati        2.333333            1        ...           2.000000   \n",
+       "HOUMADI Chaharazadi       5.000000          NaN        ...           1.333333   \n",
+       "HOUMADI Nasmi             0.333333            1        ...           0.666667   \n",
+       "HOUMADI Dhoirfia          5.000000          NaN        ...           0.666667   \n",
+       "LOUTOUFI Nachima          1.333333            1        ...           0.000000   \n",
+       "MALIDE El-Anzize          6.000000            0        ...           0.000000   \n",
+       "MONNE Kevin               2.666667            2        ...           4.000000   \n",
+       "MOUSSA Roibouanti         3.333333            1        ...           1.333333   \n",
+       "OUSSENI Hilma             4.000000            0        ...           0.666667   \n",
+       "SAANLI Natali             6.666667            2        ...           4.000000   \n",
+       "SAID AHAMADA Roukaya      0.000000          NaN        ...           0.666667   \n",
+       "SANDA Issoufi             0.000000          NaN        ...           0.666667   \n",
+       "SOILIHI Soifia            2.333333            1        ...           2.000000   \n",
+       "SOUFIANI Laila            0.000000          NaN        ...           0.000000   \n",
+       "YOUSSOUF Sitirati         1.000000          NaN        ...           0.666667   \n",
+       "\n",
+       "                        1. Opérations  2. Équation  3. Probabilité  \\\n",
+       "ABDOU Farida                      NaN          NaN             NaN   \n",
+       "ABOU BACAR Djaha                    1          NaN             NaN   \n",
+       "AHAMADA Nabaouya                    0            0               0   \n",
+       "AHAMADI Faina                       0            0               1   \n",
+       "ALI Mardhuia                        1            0               1   \n",
+       "ALI SOULAIMANA Chamsia              1            0               0   \n",
+       "ALSENE ALI MADI Stela               1            1               2   \n",
+       "ANDRIATAHIANA Hoby                  0            1               1   \n",
+       "ANLI Emeline                      NaN          NaN               0   \n",
+       "ATHOUMANE Naouidat                  0            0               0   \n",
+       "BOUDRA Nassifanya                   1            0               1   \n",
+       "CHANFI Nadhrati                     1            0               0   \n",
+       "COMBO Moinécha                      2            2             NaN   \n",
+       "HALIDI Nisma                        1            0               2   \n",
+       "HAMZA Samianti                      0          NaN             NaN   \n",
+       "HOUMADI Mouslimati                  1            2             NaN   \n",
+       "HOUMADI Chaharazadi                 0            1               1   \n",
+       "HOUMADI Nasmi                       0            0               1   \n",
+       "HOUMADI Dhoirfia                    0            0               1   \n",
+       "LOUTOUFI Nachima                    0            0             NaN   \n",
+       "MALIDE El-Anzize                    0            0               0   \n",
+       "MONNE Kevin                         2            2               2   \n",
+       "MOUSSA Roibouanti                   1            0               1   \n",
+       "OUSSENI Hilma                       0            0               1   \n",
+       "SAANLI Natali                       2            3               1   \n",
+       "SAID AHAMADA Roukaya                0          NaN               1   \n",
+       "SANDA Issoufi                       1            0               0   \n",
+       "SOILIHI Soifia                      2            0               1   \n",
+       "SOUFIANI Laila                      0            0               0   \n",
+       "YOUSSOUF Sitirati                   0            1             NaN   \n",
+       "\n",
+       "                        Exercice 6  1. Tableur  2. Tableur  3. PGCD  \\\n",
+       "ABDOU Farida                   1.0           1           1        0   \n",
+       "ABOU BACAR Djaha               0.0         NaN         NaN      NaN   \n",
+       "AHAMADA Nabaouya               4.5           3           1        3   \n",
+       "AHAMADI Faina                  1.5           0           1        0   \n",
+       "ALI Mardhuia                   2.5           0           0        2   \n",
+       "ALI SOULAIMANA Chamsia         3.5           3         NaN        3   \n",
+       "ALSENE ALI MADI Stela          0.0         NaN         NaN      NaN   \n",
+       "ANDRIATAHIANA Hoby             2.5           2         NaN      NaN   \n",
+       "ANLI Emeline                   1.5         NaN         NaN      NaN   \n",
+       "ATHOUMANE Naouidat             1.5         NaN         NaN        3   \n",
+       "BOUDRA Nassifanya              5.5           3           2        3   \n",
+       "CHANFI Nadhrati                0.5         NaN           0        0   \n",
+       "COMBO Moinécha                 3.0           2           0        1   \n",
+       "HALIDI Nisma                   4.5           3           0        3   \n",
+       "HAMZA Samianti                 1.0           0           0        0   \n",
+       "HOUMADI Mouslimati             0.0         NaN         NaN      NaN   \n",
+       "HOUMADI Chaharazadi            1.5           0           0        0   \n",
+       "HOUMADI Nasmi                  4.5           3         NaN        3   \n",
+       "HOUMADI Dhoirfia               4.0           3           0        2   \n",
+       "LOUTOUFI Nachima               1.0           1           0        0   \n",
+       "MALIDE El-Anzize               1.0         NaN         NaN      NaN   \n",
+       "MONNE Kevin                    3.5           3           0        2   \n",
+       "MOUSSA Roibouanti              3.5           2           0        2   \n",
+       "OUSSENI Hilma                  0.5           0           0        0   \n",
+       "SAANLI Natali                  4.5           3         NaN        3   \n",
+       "SAID AHAMADA Roukaya           4.5           3         NaN        3   \n",
+       "SANDA Issoufi                  1.5           1           0        2   \n",
+       "SOILIHI Soifia                 2.0         NaN         NaN        3   \n",
+       "SOUFIANI Laila                 1.5           0         NaN        3   \n",
+       "YOUSSOUF Sitirati              1.0         NaN         NaN        2   \n",
+       "\n",
+       "                        4. Fraction  Exercice 7 (QCM)  \n",
+       "ABDOU Farida                    NaN                 3  \n",
+       "ABOU BACAR Djaha                NaN                 4  \n",
+       "AHAMADA Nabaouya                  2                 2  \n",
+       "AHAMADI Faina                     2                 1  \n",
+       "ALI Mardhuia                      3                 2  \n",
+       "ALI SOULAIMANA Chamsia            1                 3  \n",
+       "ALSENE ALI MADI Stela           NaN                 0  \n",
+       "ANDRIATAHIANA Hoby                3                 3  \n",
+       "ANLI Emeline                      3                 3  \n",
+       "ATHOUMANE Naouidat                0                 1  \n",
+       "BOUDRA Nassifanya                 3                 3  \n",
+       "CHANFI Nadhrati                   1                 3  \n",
+       "COMBO Moinécha                    3                 4  \n",
+       "HALIDI Nisma                      3                 4  \n",
+       "HAMZA Samianti                    2                 4  \n",
+       "HOUMADI Mouslimati              NaN                 5  \n",
+       "HOUMADI Chaharazadi               3                 4  \n",
+       "HOUMADI Nasmi                     3                 3  \n",
+       "HOUMADI Dhoirfia                  3                 3  \n",
+       "LOUTOUFI Nachima                  1                 3  \n",
+       "MALIDE El-Anzize                  2                 2  \n",
+       "MONNE Kevin                       2                 3  \n",
+       "MOUSSA Roibouanti                 3                 4  \n",
+       "OUSSENI Hilma                     1                 2  \n",
+       "SAANLI Natali                     3                 2  \n",
+       "SAID AHAMADA Roukaya              3                 4  \n",
+       "SANDA Issoufi                     0                 3  \n",
+       "SOILIHI Soifia                    1                 5  \n",
+       "SOUFIANI Laila                    0                 2  \n",
+       "YOUSSOUF Sitirati               NaN                 0  \n",
+       "\n",
+       "[30 rows x 28 columns]"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "notes\n",
+    "#barem"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Supression des notes inutiles "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/lafrite/.virtualenvs/enseignement/lib/python3.5/site-packages/pandas/core/ops.py:680: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison\n",
+      "  result = getattr(x, name)(y)\n"
+     ]
+    },
+    {
+     "ename": "TypeError",
+     "evalue": "invalid type comparison",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[1;32m<ipython-input-9-5bb918f5a68f>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0mnotes\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnotes\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mnotes\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mds_name\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnotnull\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mnotes\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnotes\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mnotes\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mds_name\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m!=\u001b[0m \u001b[1;34m'abs'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[1;32m/home/lafrite/.virtualenvs/enseignement/lib/python3.5/site-packages/pandas/core/ops.py\u001b[0m in \u001b[0;36mwrapper\u001b[1;34m(self, other, axis)\u001b[0m\n\u001b[0;32m    724\u001b[0m                 \u001b[0mother\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0masarray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mother\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    725\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 726\u001b[1;33m             \u001b[0mres\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mna_op\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvalues\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mother\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    727\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0misscalar\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mres\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    728\u001b[0m                 raise TypeError('Could not compare %s type with Series'\n",
+      "\u001b[1;32m/home/lafrite/.virtualenvs/enseignement/lib/python3.5/site-packages/pandas/core/ops.py\u001b[0m in \u001b[0;36mna_op\u001b[1;34m(x, y)\u001b[0m\n\u001b[0;32m    680\u001b[0m                 \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    681\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[0mresult\u001b[0m \u001b[1;32mis\u001b[0m \u001b[0mNotImplemented\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 682\u001b[1;33m                     \u001b[1;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"invalid type comparison\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    683\u001b[0m             \u001b[1;32mexcept\u001b[0m \u001b[0mAttributeError\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    684\u001b[0m                 \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mop\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;31mTypeError\u001b[0m: invalid type comparison"
+     ]
+    }
+   ],
+   "source": [
+    "notes = notes[notes[ds_name].notnull()]\n",
+    "notes = notes[notes[ds_name] != 'abs']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "notes = notes.astype(float)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Traitement des notes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['BB_16_01_23', 'Présentation', 'Exercice 1', 'Réponse', 'Rédaction',\n",
+       "       'Exercice 2', '1. Developper', '2. Evaluer', 'Exercice 3',\n",
+       "       'Comparaison', 'Pythagore', 'Thalès', 'Exercice 4', '1. Lecture',\n",
+       "       '2. Max', '3. Moyenne', '4. Etendue', '5. Médiane', 'Exercice 5',\n",
+       "       '1. Opérations', '2. Équation', '3. Probabilité', 'Exercice 6',\n",
+       "       '1. Tableur', '2. Tableur', '3. PGCD', '4. Fraction',\n",
+       "       'Exercice 7 (QCM)'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "notes.T.index"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Liste des exercices (non noté en compétences)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": false
+   },
+   "source": [
+    "list_exo = [\"Exercice \"+str(i+1) for i in range(6)] + [\"Exercice 7 (QCM)\"]\n",
+    "list_exo"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Les autres types de notes (presentation, malus...) qui ne sont pas en compétences"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "autres_notes = [\"Présentation\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "notes[list_exo] = notes[list_exo].applymap(lambda x:round(x,2))\n",
+    "#notes[list_exo]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Les éléments avec notes et les éléments par compétences (sous_exo)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['Réponse',\n",
+       " 'Rédaction',\n",
+       " '1. Developper',\n",
+       " '2. Evaluer',\n",
+       " 'Comparaison',\n",
+       " 'Pythagore',\n",
+       " 'Thalès',\n",
+       " '1. Lecture',\n",
+       " '2. Max',\n",
+       " '3. Moyenne',\n",
+       " '4. Etendue',\n",
+       " '5. Médiane',\n",
+       " '1. Opérations',\n",
+       " '2. Équation',\n",
+       " '3. Probabilité',\n",
+       " '1. Tableur',\n",
+       " '2. Tableur',\n",
+       " '3. PGCD',\n",
+       " '4. Fraction']"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "item_avec_note = list_exo + [ds_name] + autres_notes\n",
+    "sous_exo = [i for i in notes.T.index if i not in item_avec_note]\n",
+    "sous_exo"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def toRepVal(val):\n",
+    "    if pd.isnull(val):\n",
+    "        return \"\\\\NoRep\"\n",
+    "    elif val == 0:\n",
+    "        return \"\\\\RepZ\"\n",
+    "    elif val == 1:\n",
+    "        return \"\\\\RepU\"\n",
+    "    elif val == 2:\n",
+    "        return \"\\\\RepD\"\n",
+    "    elif val == 3:\n",
+    "        return \"\\\\RepT\"\n",
+    "    else:\n",
+    "        return val"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "notes[item_avec_note] = notes[item_avec_note].fillna(\".\")\n",
+    "#notes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "eleves = notes.copy()\n",
+    "eleves[sous_exo] = notes[sous_exo].applymap(toRepVal)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "28"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(notes.T.index)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Preparation du fichier .tex"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 247,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "#eleves"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "bilan = texenv.get_template(\"tpl_bilan.tex\")\n",
+    "with open(\"./bilan\"+classe+\".tex\",\"w\") as f:\n",
+    "    f.write(bilan.render(eleves = eleves, barem = barem, ds_name = ds_name, latex_info = latex_info, nbr_questions = len(barem.T)))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Un peu de statistiques"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "count    30.000000\n",
+       "mean     19.300000\n",
+       "std       5.518933\n",
+       "min       9.000000\n",
+       "25%      14.875000\n",
+       "50%      20.250000\n",
+       "75%      22.875000\n",
+       "max      31.000000\n",
+       "Name: BB_16_01_23, dtype: float64"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "notes[ds_name].describe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 130,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.text.Text at 0x7fbb35389278>"
+      ]
+     },
+     "execution_count": 130,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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AaYlWAAAApiVaAQAAmJZoBQAAYFqiFQAAgGmJVgAAAKYlWgEAAJiWaAUAAGBaohUAAIBp\niVYAAACmJVoBAACYlmgFAABgWqIVAACAaYlWAAAApiVaAQAAmJZoBQAAYFqiFQAAgGmJVgAAAKYl\nWgEAAJiWaAUAAGBaohUAAIBpiVYAAACmJVoBAACYlmgFAABgWqIVAACAaYlWAAAApiVaAQAAmJZo\nBQAAYFqiFQAAgGmJVgAAAKYlWgEAAJiWaAUAAGBaohUAAIBpiVYAAACmJVoBAACYlmgFAABgWheO\nnHhVvSnJC5J8urufNHJeAAAA7D6j97T+XJLnDp4HAAAAu9TQaO3uDyY5MnIeAAAA7F5DDw8Gts6x\nY8dy222fHDLt22//VJInDpk2q2vUOnfs2LEka9mzZ2tfNx27Hh9bTn9rjRvzmPEmqzdm928nGrde\nJMnllz8me/bsGTb9VTDysTpxG/PANWW0rq/v2+khcJ4su3EOHDiQa645lOSKAVM/PGCaC5dcsnel\n1osjR/bu9BDOy4jbeNw697tJLhsw3XHrcXJ7Xvzii5Ns9foxasyjxpus3phHrhcLW739jbsfGrle\nHEz33uzfv3/AtMfZ6mU39rF6NW/jkVbp+QX3z5TReujQXTs9BM7D+vo+y26gw4ePZvEgOOLB6uCA\naS4cPnx0pdaLxe28euE64jYet84dHDjdkVZtzKt3f7F6t/HCVm9/Y++HRq0Xq3d/P+J5y9jH6tW7\njUfyvHN1nc+LDdvxlTdry38AAABwToZGa1W9LcnvJ9lfVbdX1T8ZOT8AAAB2l6GHB3f3t4+cPgAA\nALvbdhweDAAAAOdFtAIAADAt0QoAAMC0RCsAAADTEq0AAABMS7QCAAAwLdEKAADAtEQrAAAA0xKt\nAAAATEu0AgAAMC3RCgAAwLREKwAAANMSrQAAAExLtAIAADAt0QoAAMC0RCsAAADTEq0AAABMS7QC\nAAAwLdEKAADAtEQrAAAA0xKtAAAATEu0AgAAMC3RCgAAwLREKwAAANMSrQAAAExLtAIAADAt0QoA\nAMC0RCsAAADTEq0AAABMS7QCAAAwLdEKAADAtEQrAAAA0xKtAAAATEu0AgAAMC3RCgAAwLREKwAA\nANMSrQAAAExLtAIAADAt0QoAAMC0RCsAAADTEq0AAABMS7QCAAAwLdEKAADAtEQrAAAA0xKtAAAA\nTEu0AgAAMC3RCgAAwLREKwAAANMSrQAAAExLtAIAADAt0QoAAMC0RCsAAADTEq0AAABMS7QCAAAw\nLdEKAADAtEQrAAAA0xKtAAAATEu0AgAAMC3RCgAAwLREKwAAANMSrQAAAExLtAIAADAt0QoAAMC0\nRCsAAADTEq0AAABMS7QCAAAwLdEKAADAtEQrAAAA0xKtAAAATOvC0TOoqucl+YksAvlN3f0jo+cJ\nAADA7jB0T2tVXZDk9Umem+SJSb6tqh43cp4AAADsHqMPD746yZ9296e6++4kb0/yLYPnCQAAwC4x\n+vDgRyb58xPO35FFyJ7We97znnz2s/9vSwdx0UUX5VGPetSWTpP7OnJkbw4fPrrTw9i1br/9U0ku\nHjT1OwZN92Buv/3zg6Y9xrjbedxtfPBghmx7q3dbjJruyGmv2nRHTnvVppuM2v5Wb9tLVvH+fsTz\nlrGP1at3G4/keefqWl+/6pyvs7axsTFgKAtV9Q+TPKe7v2d5/iVJntrdrxg2UwAAAHaN0YcH35Hk\nq044f1mSvxg8TwAAAHaJ0YcH35Tkq6vq0Un+d5JvTfJtg+cJAADALjF0T2t3H0vy8iS/nuSPk7y9\nuz8xcp4AAADsHkPf0woAAAD3x+j3tAIAAMB5E60AAABMS7QCAAAwrdGfHnzWqup5SX4ii5B+U3f/\nyA4PiXNQVbcl+WySe5Lc3d1X7+iAOKOqelOSFyT5dHc/aXnZlyf5xSSPTnJbkn/U3Z/dsUFySqdZ\ndq9J8tIk/2f5a6/u7l/boSFyGlV1WZK3JPnKJMeSvKG7f9K2txpOsfx+prt/yva3GqrqoiS/k+RB\nWTz/fWd331hVlyd5e5IvT/LRJN/Z3V/YsYFyH2dYdj+X5BlZPP/cSPLd3f1HOzdSzqSqLkjy4SR3\ndPf157rtTbGndflHvD7Jc5M8Mcm3VdXjdnZUnKN7kjyzu58iWFfCz2WxvZ3oB5L8z+6uJL+Z5IZt\nHxVn41TLLkle291XLf95wjynLyR5ZXc/Ick1SV62fKyz7a2Gk5ffy094rmL7m1x3/1WSa7v7KUmu\nTPLNVfW3kvxIkh9bbn+fSfLPdnCYnMIZll2S/Ovlc8+rBOv0XpHk1hPOn9O2N0W0Jrk6yZ9296e6\n++4sqvtbdnhMnJu1zLM+sYnu/mCSIydd/C1J3rw8/eYkL9zWQXFWTrPsksU2yMS6+87uvmV5+miS\nTyS5LLa9lXCa5ffI5Y9tfyuguz+/PHlRFnvsNpJcm+SXlpe/Ocnf24GhsYlTLLt7ludteytgeaTK\ndUneeMLFfzfnsO3NEhmPTPLnJ5y/I/c+ELAaNpK8r6puqqqX7vRgOC9f0d2fThZPzpKs7/B4ODcv\nq6pbquqNVfWwnR4MZ7Y8LOrKJH+Q5FLb3mo5Yfl9aHmR7W8FVNUFVXVzkjuTvD/JnyX5THcfD6A7\nkvzNnRofp3fysuvum5Y/+jfLbe/HqupLdnCInNmPJ3lVFr2Qqnp4kiPnsu3NEq2nepXEF8iulm/s\n7m/I4lWUl1XV397pAcEDyE8neWx3X5nFA/prd3g8nEFV7U3yziSvWO6x83i3Qk6x/Gx/K6K771ke\nYnpZFkf5Pf4Uv2Z7nNDJy66qnpDkB7r78UmemuThSb5/J8fIqVXV87P4HI5bcm/zreW+/XfGbW+W\naL0jyVedcP6yJH+xQ2PhPCz3DqS7DyV5VxYPBqyWT1fVpUlSVV+Zez9UhMl196HuPn5n/4YsHsCZ\nUFVdmEXw/Hx3//LyYtveijjV8rP9rZ7u/lyS307ytCRftvxslcTzz+mdsOyed8IRKndn8XkPnnvO\n6elJrq+qTyb5L1kcFvwTSR52LtveLNF6U5KvrqpHV9WDknxrkl/Z4TFxlqrq4uUrz6mqhyZ5TpKP\n7+yoOAsnv8r1K0m+e3n6Hyf55ZOvwDS+aNktQ+e4vx/b38x+Nsmt3f26Ey6z7a2O+yw/299qqKpH\nHD90u6oekuTZWXwozG8ledHy12x/EzrNsvuT49teVa1l8VkAtr0Jdferu/uruvsxWTTeb3b3S3KO\n297axsYcR0Esv/Lmdbn3K2/+3Q4PibNUVVdksXd1I4s3x7/V8ptbVb0tyTOzOJzm00lek+TdSd6R\n5FFJbk/you7+zE6NkVM7zbK7Nov3192TxVemfO/xV6CZR1U9PYuvbfhYFveXG0leneQPk/zX2Pam\ndobl9+2x/U2vqr4uiw97uWD57xe7+98un8Mc/9qNm5O8ZLnnjkmcYdn9RpJHZPEi7i1J/sUJH9jE\nhKrqGUm+b/mVN+e07U0TrQAAAHCyWQ4PBgAAgPsQrQAAAExLtAIAADAt0QoAAMC0RCsAAADTEq0A\nAABMS7QCwP1UVbdV1R+ddNnBqnrCJtd7TVVdOHZ0ALDaRCsA3H8bSfZW1Xed4/Vek+RBA8YDALuG\nV3cBYGv8cJIfrqq3dfcXjl9YVY9N8p+SrCe5O8kPdvf7qur1WcTu71fVPUmeuTz/2iRfl+TBSX4r\nySu7e6OqXpPkxUn+cvl713b357brjwOAnWJPKwDcfxtJPpzkpiT/8qSfvTXJL3T3k5N8Z5JfqKqH\nd/fLk6wluaa7r1oG6GuTfKC7n5bkKUkuTfJPq+rLkvyrJE/p7quSfFOSo9vxhwHAThOtAHD/rS3/\n/6Ek319VD80iZC9IcmV3/+ck6e5PJLklydNOcd0kuT7Jq6rq5iQfTXJVkv1JPpfkT5O8par+eZJ9\n3X3PuD8HAObh8GAA2CLdfaCq3pvklcuL1rKI15Od6rLjXtjdt518YVU9LcnTkzwryUeq6rnd/fH7\nOWQAmJ49rQCwtW5M8rIk+5Lck+SWqvruJKmqxyV5UpI/WP7u55I87ITr/kqSG6rqguXvP7yqLq+q\nvUm+ort/t7t/OMnHk3ztNvwtALDj1jY2zvRiLwCwmar6ZJIXdPety/P/Pou9rV+XxQcn/Uzu/SCm\nG7r7/cvf+6Ek35Hk81l8ENM9SX40yd/JYm/sX2bxXtZPJfmlLD6caU+SjyT5nu7+6+35CwFg54hW\nAAAApuXwYAAAAKYlWgEAAJiWaAUAAGBaohUAAIBpiVYAAACmJVoBAACYlmgFAABgWv8flexJuP8d\npfQAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fbb353d1c50>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#notes_seules = notes[ds_name]\n",
+    "ax = notes[ds_name].hist(bins = barem[ds_name][0], range=(0,barem[ds_name][0]), figsize = (16,7), )\n",
+    "ax.set_xlabel(\"Notes\")\n",
+    "ax.set_ylabel(\"Effectif\")\n",
+    "#notes_seules.hist()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 246,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fbb2d7e3be0>"
+      ]
+     },
+     "execution_count": 246,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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xDIf91VU2t9NDYXYxnf3tdPS2kuJO45Mdx8jPLmJyKkTfsJfWniZ6BruwWe2k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fZQ+QpzQ+8ze3FSNVUtVFU2IYo5whEfPr8dq32ebCaN0ViwX4wFgi7ujXzPTnyL2ppWBvo+wh9w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sJyjOYN/AE3w4M36GgfpqS4ErlcTiDoxu93EY9HEQQZlRUNFBWVv1DmfVaEQj7mF+8eu9YL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p1hNX7PsL9yiKBbrquxnsGH4ht+tgPMDyxiJV9ioWPPMom3bxsiJTpjdwrKWf4x2D2E27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\nBOcGz2N5SpL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LycJIzyiufbhD/2PAg2KwoJYdfbL/JGbz0aRE6LrOVnqL5dAS5WoZo8FI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5CUGmK5zML6AqrS+HzPAkN1mtpJxVjYWNjDv15FEEzous6d6c+pKTU+nviY7WSMtZ1VwCia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\nRK5CYII=\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fbb2d4c8208>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Normalisation des notes de chaque exo\n",
+    "notes_exo_norm = notes[list_exo] / barem[list_exo].values[0,:]\n",
+    "#notes_exo_norm\n",
+    "ax = notes_exo_norm.T.plot(color = \"gray\", legend = False, figsize = (16, 7))\n",
+    "d_norm =  notes_exo_norm.describe()\n",
+    "d_norm.T[[\"min\", \"25%\", \"50%\", \"75%\", \"max\"]].plot(ax=ax, kind=\"area\", stacked = False, alpha=.1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 180,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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lDJIRitp8azLzNmB2iadcSHH1jPLKx1ERcUwT2fYZICO0vx937bsSnZl7KD6g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\nLhFKegAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7fbb2e77ceb8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ax = notes[list_exo].hist(figsize = (16,8))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 105,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Réponse</th>\n",
+       "      <th>Rédaction</th>\n",
+       "      <th>1. Developper</th>\n",
+       "      <th>2. Evaluer</th>\n",
+       "      <th>Comparaison</th>\n",
+       "      <th>Pythagore</th>\n",
+       "      <th>Thalès</th>\n",
+       "      <th>1. Lecture</th>\n",
+       "      <th>2. Max</th>\n",
+       "      <th>3. Moyenne</th>\n",
+       "      <th>4. Etendue</th>\n",
+       "      <th>5. Médiane</th>\n",
+       "      <th>1. Opérations</th>\n",
+       "      <th>2. Équation</th>\n",
+       "      <th>3. Probabilité</th>\n",
+       "      <th>1. Tableur</th>\n",
+       "      <th>2. Tableur</th>\n",
+       "      <th>3. PGCD</th>\n",
+       "      <th>4. Fraction</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>29.000000</td>\n",
+       "      <td>29.000000</td>\n",
+       "      <td>30.000000</td>\n",
+       "      <td>30.000000</td>\n",
+       "      <td>20.000000</td>\n",
+       "      <td>21.000000</td>\n",
+       "      <td>19.000000</td>\n",
+       "      <td>30.000000</td>\n",
+       "      <td>29.000000</td>\n",
+       "      <td>29.000000</td>\n",
+       "      <td>30.000000</td>\n",
+       "      <td>30.000000</td>\n",
+       "      <td>28.000000</td>\n",
+       "      <td>25.00000</td>\n",
+       "      <td>23.000000</td>\n",
+       "      <td>21.000000</td>\n",
+       "      <td>16.00000</td>\n",
+       "      <td>24.000000</td>\n",
+       "      <td>25.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>1.896552</td>\n",
+       "      <td>1.103448</td>\n",
+       "      <td>1.166667</td>\n",
+       "      <td>0.700000</td>\n",
+       "      <td>1.250000</td>\n",
+       "      <td>2.571429</td>\n",
+       "      <td>1.736842</td>\n",
+       "      <td>2.900000</td>\n",
+       "      <td>2.862069</td>\n",
+       "      <td>1.551724</td>\n",
+       "      <td>1.633333</td>\n",
+       "      <td>1.566667</td>\n",
+       "      <td>0.642857</td>\n",
+       "      <td>0.52000</td>\n",
+       "      <td>0.782609</td>\n",
+       "      <td>1.714286</td>\n",
+       "      <td>0.31250</td>\n",
+       "      <td>1.791667</td>\n",
+       "      <td>2.040000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>1.113066</td>\n",
+       "      <td>0.409253</td>\n",
+       "      <td>0.912871</td>\n",
+       "      <td>0.595963</td>\n",
+       "      <td>0.966546</td>\n",
+       "      <td>0.676123</td>\n",
+       "      <td>1.194529</td>\n",
+       "      <td>0.547723</td>\n",
+       "      <td>0.580895</td>\n",
+       "      <td>1.241721</td>\n",
+       "      <td>1.217214</td>\n",
+       "      <td>0.897634</td>\n",
+       "      <td>0.731021</td>\n",
+       "      <td>0.87178</td>\n",
+       "      <td>0.671262</td>\n",
+       "      <td>1.309307</td>\n",
+       "      <td>0.60208</td>\n",
+       "      <td>1.284664</td>\n",
+       "      <td>1.098484</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.00000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.00000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.00000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.00000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>0.500000</td>\n",
+       "      <td>0.00000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>0.00000</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>2.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.00000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>0.25000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>3.00000</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>2.00000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         Réponse  Rédaction  1. Developper  2. Evaluer  Comparaison  \\\n",
+       "count  29.000000  29.000000      30.000000   30.000000    20.000000   \n",
+       "mean    1.896552   1.103448       1.166667    0.700000     1.250000   \n",
+       "std     1.113066   0.409253       0.912871    0.595963     0.966546   \n",
+       "min     0.000000   1.000000       0.000000    0.000000     0.000000   \n",
+       "25%     1.000000   1.000000       0.250000    0.000000     1.000000   \n",
+       "50%     2.000000   1.000000       1.000000    1.000000     1.000000   \n",
+       "75%     3.000000   1.000000       2.000000    1.000000     2.000000   \n",
+       "max     3.000000   3.000000       3.000000    2.000000     3.000000   \n",
+       "\n",
+       "       Pythagore     Thalès  1. Lecture     2. Max  3. Moyenne  4. Etendue  \\\n",
+       "count  21.000000  19.000000   30.000000  29.000000   29.000000   30.000000   \n",
+       "mean    2.571429   1.736842    2.900000   2.862069    1.551724    1.633333   \n",
+       "std     0.676123   1.194529    0.547723   0.580895    1.241721    1.217214   \n",
+       "min     1.000000   0.000000    0.000000   0.000000    0.000000    0.000000   \n",
+       "25%     2.000000   0.500000    3.000000   3.000000    0.000000    0.250000   \n",
+       "50%     3.000000   2.000000    3.000000   3.000000    1.000000    2.000000   \n",
+       "75%     3.000000   3.000000    3.000000   3.000000    3.000000    3.000000   \n",
+       "max     3.000000   3.000000    3.000000   3.000000    3.000000    3.000000   \n",
+       "\n",
+       "       5. Médiane  1. Opérations  2. Équation  3. Probabilité  1. Tableur  \\\n",
+       "count   30.000000      28.000000     25.00000       23.000000   21.000000   \n",
+       "mean     1.566667       0.642857      0.52000        0.782609    1.714286   \n",
+       "std      0.897634       0.731021      0.87178        0.671262    1.309307   \n",
+       "min      0.000000       0.000000      0.00000        0.000000    0.000000   \n",
+       "25%      1.000000       0.000000      0.00000        0.000000    0.000000   \n",
+       "50%      2.000000       0.500000      0.00000        1.000000    2.000000   \n",
+       "75%      2.000000       1.000000      1.00000        1.000000    3.000000   \n",
+       "max      3.000000       2.000000      3.00000        2.000000    3.000000   \n",
+       "\n",
+       "       2. Tableur    3. PGCD  4. Fraction  \n",
+       "count    16.00000  24.000000    25.000000  \n",
+       "mean      0.31250   1.791667     2.040000  \n",
+       "std       0.60208   1.284664     1.098484  \n",
+       "min       0.00000   0.000000     0.000000  \n",
+       "25%       0.00000   0.000000     1.000000  \n",
+       "50%       0.00000   2.000000     2.000000  \n",
+       "75%       0.25000   3.000000     3.000000  \n",
+       "max       2.00000   3.000000     3.000000  "
+      ]
+     },
+     "execution_count": 105,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "notes_questions = notes[sous_exo]\n",
+    "notes_analysis = notes_questions.describe()\n",
+    "notes_analysis"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Réponse</th>\n",
+       "      <th>Rédaction</th>\n",
+       "      <th>1. Developper</th>\n",
+       "      <th>2. Evaluer</th>\n",
+       "      <th>Comparaison</th>\n",
+       "      <th>Pythagore</th>\n",
+       "      <th>Thalès</th>\n",
+       "      <th>1. Lecture</th>\n",
+       "      <th>2. Max</th>\n",
+       "      <th>3. Moyenne</th>\n",
+       "      <th>4. Etendue</th>\n",
+       "      <th>5. Médiane</th>\n",
+       "      <th>1. Opérations</th>\n",
+       "      <th>2. Équation</th>\n",
+       "      <th>3. Probabilité</th>\n",
+       "      <th>1. Tableur</th>\n",
+       "      <th>2. Tableur</th>\n",
+       "      <th>3. PGCD</th>\n",
+       "      <th>4. Fraction</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>29</td>\n",
+       "      <td>29</td>\n",
+       "      <td>30</td>\n",
+       "      <td>30</td>\n",
+       "      <td>20</td>\n",
+       "      <td>21</td>\n",
+       "      <td>19</td>\n",
+       "      <td>30</td>\n",
+       "      <td>29</td>\n",
+       "      <td>29</td>\n",
+       "      <td>30</td>\n",
+       "      <td>30</td>\n",
+       "      <td>28</td>\n",
+       "      <td>25</td>\n",
+       "      <td>23</td>\n",
+       "      <td>21</td>\n",
+       "      <td>16</td>\n",
+       "      <td>24</td>\n",
+       "      <td>25</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Réponse  Rédaction  1. Developper  2. Evaluer  Comparaison  Pythagore  \\\n",
+       "count       29         29             30          30           20         21   \n",
+       "\n",
+       "       Thalès  1. Lecture  2. Max  3. Moyenne  4. Etendue  5. Médiane  \\\n",
+       "count      19          30      29          29          30          30   \n",
+       "\n",
+       "       1. Opérations  2. Équation  3. Probabilité  1. Tableur  2. Tableur  \\\n",
+       "count             28           25              23          21          16   \n",
+       "\n",
+       "       3. PGCD  4. Fraction  \n",
+       "count       24           25  "
+      ]
+     },
+     "execution_count": 71,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# J'aimerai récupérer le nom des questions qui ont été le moins répondus\n",
+    "notes_analysis[:1]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": true
+   },
+   "source": [
+    "## Bilan à remplir"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "bilan = texenv.get_template(\"tpl_bilan.tex\")\n",
+    "with open(\"./fill_bilan.tex\",\"w\") as f:\n",
+    "    f.write(bilan.render(eleves = [(\"Nom\",, barem = barem, ds_name = ds_name, latex_info = latex_info, nbr_questions = len(barem.T)))"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.5.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/tools/skeleton/Competences.tex b/tools/skeleton/Competences.tex
new file mode 100644
index 0000000..0620f22
--- /dev/null
+++ b/tools/skeleton/Competences.tex
@@ -0,0 +1,82 @@
+\documentclass{classConn}
+
+
+% Title Page
+\title{}
+\author{}
+\date{}
+
+
+\begin{document}
+
+\begin{multicols}{2}
+    
+Nom - Prénom - Classe: 
+
+~\\[1cm]
+
+\textbf{Note:} \hfill {\Large /20}
+~\\[1cm]
+
+
+\textbf{Commentaires:} \\[4cm]
+
+\textbf{Compétences:}
+%\begin{competences}
+%    \competence Dessin en 3D
+%    \competence Lecture graphique
+%    \competence Lecture tableau de varation
+%    \competence Écriture mathématique
+%\end{competences}
+\vfill
+
+\hspace{-1cm}
+\begin{tabular}{|p{5cm}|*{3}{c|}}
+    \hline
+    Compétences & Non aquis & Cours d'aquisition & Aquis \\
+    \hline
+    <++> Compétences <++>
+    \hline
+\end{tabular}
+\vfill
+
+\columnbreak
+
+Nom - Prénom - Classe: 
+
+~\\[1cm]
+
+\textbf{Note:} \hfill {\Large /20}
+~\\[1cm]
+
+
+\textbf{Commentaires:} \\[4cm]
+
+\textbf{Compétences:}
+%\begin{competences}
+%    \competence Dessin en 3D
+%    \competence Lecture graphique
+%    \competence Lecture tableau de varation
+%    \competence Écriture mathématique
+%\end{competences}
+\vfill
+
+\hspace{-1cm}
+\begin{tabular}{|p{5cm}|*{3}{c|}}
+    \hline
+    Compétences & Non aquis & Cours d'aquisition & Aquis \\
+    \hline
+    <++> Compétences <++>
+    \hline
+\end{tabular}
+\vfill
+
+
+\end{multicols}
+
+\end{document}
+
+%%% Local Variables: 
+%%% mode: latex
+%%% TeX-master: "master"
+%%% End:
diff --git a/tools/skeleton/Conn.tex b/tools/skeleton/Conn.tex
new file mode 100644
index 0000000..95edf8f
--- /dev/null
+++ b/tools/skeleton/Conn.tex
@@ -0,0 +1,28 @@
+\documentclass{classConn}
+
+
+% Title Page
+\title{}
+\author{}
+\date{<++ date ++>}
+% \seconde \premiereS \PSTMG \TSTMG
+\classe{<++Une classe++>}
+
+
+\begin{document}
+
+\sujet
+
+\begin{Exo}
+   <++ Exercice ++> 
+\end{Exo}
+
+
+\sujet
+
+\end{document}
+
+%%% Local Variables: 
+%%% mode: latex
+%%% TeX-master: "master"
+%%% End:
diff --git a/tools/skeleton/Cours.tex b/tools/skeleton/Cours.tex
new file mode 100644
index 0000000..60af6e1
--- /dev/null
+++ b/tools/skeleton/Cours.tex
@@ -0,0 +1,20 @@
+\documentclass[a4paper,10pt, table]{classCours}
+
+% Title Page
+\titre{<++titre++>}
+% \seconde \premiereS \PSTMG \TSTMG
+\classe{<++classe++>}
+\date{<++date++>}
+
+\begin{document}
+\maketitle
+
+<++Cours++>
+
+\end{document}
+
+%%% Local Variables: 
+%%% mode: latex
+%%% TeX-master: "master"
+%%% End:
+
diff --git a/tools/skeleton/DS.tex b/tools/skeleton/DS.tex
new file mode 100644
index 0000000..ff548fa
--- /dev/null
+++ b/tools/skeleton/DS.tex
@@ -0,0 +1,30 @@
+\documentclass[a4paper,10pt, table]{/media/documents/Cours/Prof/Enseignements/2016-2017/tools/style/classDS}
+\usepackage{/media/documents/Cours/Prof/Enseignements/2016-2017/theme}
+
+% Title Page
+\titre{<++titre++>}
+% \seconde \premiereS \PSTMG \TSTMG
+\classe{<++classe++>}
+\date{<++ date | datetimeformat("%A %d %B %Y")++>}
+\duree{1 heure}
+%\sujet{%{{infos.subj%}}}
+% DS DSCorr DM DMCorr Other 
+\typedoc{<++doc++>}
+
+\begin{document}
+\maketitle
+
+Le barème est donné à titre indicatif, il pourra être modifié.
+
+\begin{questions}
+    \question
+
+\end{questions}
+
+\end{document}
+
+%%% Local Variables: 
+%%% mode: latex
+%%% TeX-master: "master"
+%%% End:
+
diff --git a/tools/skeleton/Exam.tex b/tools/skeleton/Exam.tex
new file mode 100644
index 0000000..0dc7938
--- /dev/null
+++ b/tools/skeleton/Exam.tex
@@ -0,0 +1,29 @@
+\documentclass[a4paper,10pt, table]{classExamen}
+
+% Title Page
+\titre{<++titre++>}
+% \seconde \premiereS \PSTMG \TSTMG
+\classe{<++Class++>}
+\date{<++date++>}
+\duree{<++duree++>}
+% DS DSCorr DM DMCorr Other 
+\typedoc{<++Type++>}
+
+\begin{document}
+\titlepage
+
+\begin{questions}
+    \question
+
+
+
+\end{questions}
+
+
+\end{document}
+
+%%% Local Variables: 
+%%% mode: latex
+%%% TeX-master: "master"
+%%% End:
+
diff --git a/tools/skeleton/Exo.tex b/tools/skeleton/Exo.tex
new file mode 100644
index 0000000..b452f89
--- /dev/null
+++ b/tools/skeleton/Exo.tex
@@ -0,0 +1,20 @@
+\documentclass[a4paper,12pt,landscape, twocolumn]{classExo}
+
+% Title Page
+\titre{<++Chapitre++> - Exercices}
+% \seconde \premiereS \PSTMG \TSTMG
+\classe{<++Classe++>}
+\date{<++Date++>}
+
+
+\begin{document}
+
+<++ Exo ++>
+
+\end{document}
+
+%%% Local Variables: 
+%%% mode: latex
+%%% TeX-master: "master"
+%%% End:
+
diff --git a/tools/skeleton/calcul_mental.tex b/tools/skeleton/calcul_mental.tex
new file mode 100755
index 0000000..fa024b3
--- /dev/null
+++ b/tools/skeleton/calcul_mental.tex
@@ -0,0 +1,50 @@
+\documentclass[a4paper,10pt,xcolor=table]{classPres}
+
+\author{}
+\title{}
+\date{}
+
+\begin{document}
+    
+\begin{frame}{Calcul mental}
+    \begin{center}
+        \LARGE 30 secondes par calcul
+    \end{center}
+\end{frame}
+
+\begin{frame}{Calcul 1}
+    \huge
+    \begin{eqnarray*}
+    \end{eqnarray*}
+    
+\end{frame}
+
+\begin{frame}{Calcul 2}
+    \huge
+    \begin{eqnarray*}
+    \end{eqnarray*}
+    
+\end{frame}
+
+\begin{frame}{Calcul 3}
+    \huge
+    \begin{eqnarray*}
+    \end{eqnarray*}
+    
+\end{frame}
+
+\begin{frame}{Calcul 4}
+    \huge
+    \begin{eqnarray*}
+    \end{eqnarray*}
+    
+\end{frame}
+
+\begin{frame}{Fin}
+    \begin{center}
+        \LARGE On retourne son papier.
+    \end{center}
+\end{frame}
+
+
+\end{document}
diff --git a/tools/skeleton/index.rst b/tools/skeleton/index.rst
new file mode 100644
index 0000000..d1c6262
--- /dev/null
+++ b/tools/skeleton/index.rst
@@ -0,0 +1,11 @@
+<++ Tittre ++>
+##############
+
+:date: 2017-06-08
+:modified: 2017-06-08
+:tags: <++ tags ++>
+:category: <++ classe ++>
+:authors: Bertrand Benjamin
+:summary: <++ resumé ++>
+
+<++ contenu ++>
diff --git a/tools/skeleton/presentation.tex b/tools/skeleton/presentation.tex
new file mode 100755
index 0000000..53b95b3
--- /dev/null
+++ b/tools/skeleton/presentation.tex
@@ -0,0 +1,15 @@
+\documentclass[a4paper,10pt,xcolor=table]{classPres}
+
+\author{}
+\title{}
+\date{}
+
+\begin{document}
+    
+\begin{frame}{<++Titre++>}
+    
+\end{frame}
+
+
+
+\end{document}
diff --git a/tools/skeleton/template_EPI.rst b/tools/skeleton/template_EPI.rst
new file mode 100644
index 0000000..78954f1
--- /dev/null
+++ b/tools/skeleton/template_EPI.rst
@@ -0,0 +1,29 @@
+
+=====
+
+Niveau:
+
+Thème:
+
+Discipline
+----------
+
+Socle de compétence (thèmes)
+----------------------------
+
+Objectifs
+---------
+
+Contenu d'enseignement
+----------------------
+
+Production
+----------
+
+Organisation
+------------
+
+
+
+Calendrier
+----------
diff --git a/tools/style/base.sty b/tools/style/base.sty
new file mode 100755
index 0000000..a88fb6b
--- /dev/null
+++ b/tools/style/base.sty
@@ -0,0 +1,69 @@
+\NeedsTeXFormat{LaTeX2e}
+
+\newcommand{\op@annee}{2017-2018}
+ 
+% extensions
+\RequirePackage[utf8x]{inputenc}
+\RequirePackage[french]{babel}
+\RequirePackage[T1]{fontenc}
+\RequirePackage{amssymb}
+\RequirePackage{amsmath}
+\RequirePackage{amsfonts}
+\PassOptionsToPackage{table,usenames,dvipsnames}{xcolor}
+%\RequirePackage{subfig}
+\RequirePackage{graphicx}
+\graphicspath{{./}{/home/lafrite/Cours/Prof/Enseignements/Clipart/}}
+
+\RequirePackage{gensymb}
+\RequirePackage{ifthen, calc}
+\RequirePackage{tabularx}
+\RequirePackage{enumitem}
+\setlist[itemize,1]{label=$\bullet$}
+
+% Marges des pages
+\RequirePackage{geometry}
+\geometry{left=10mm,right=10mm, top=10mm}
+
+% Symbole euro
+\RequirePackage{eurosym}
+
+% Faire des boites
+\RequirePackage{fancybox}
+
+% Espaces pour écrire les grands nombres
+\RequirePackage[np]{numprint}
+
+% Outils pour les tableaux et les fonctions
+\RequirePackage{tkz-tab}
+\RequirePackage{tkz-fct}
+
+% Pour les block scratch
+
+\RequirePackage{scratch}
+
+% Pour gérer les todo
+\RequirePackage[french, textsize=small]{todonotes}
+
+% Plusieurs colonnes
+\RequirePackage{multicol}
+
+% inteligent import (see https://codeyarns.com/2010/05/27/latex-import-subimport-for-document-organization/)
+\RequirePackage{import}
+
+% Lecture des fichiers csv et affichage des csv en table
+\RequirePackage{csvsimple}
+
+% Mes racourcis
+\RequirePackage{shortcuts}
+
+%Polices
+%% l'option nomath fait que la police du mode mathématique n'est pas affectée
+\RequirePackage[nomath]{kpfonts}
+\renewcommand*\familydefault{\sfdefault}
+\RequirePackage[T1]{fontenc}
+
+% Les tableaux
+\renewcommand{\arraystretch}{2}
+
+% Figure qui se fondent dans le texte
+\RequirePackage{wrapfig}
diff --git a/tools/style/classConn.cls b/tools/style/classConn.cls
new file mode 100644
index 0000000..fb1bcb6
--- /dev/null
+++ b/tools/style/classConn.cls
@@ -0,0 +1,66 @@
+\NeedsTeXFormat{LaTeX2e}
+ 
+\ProvidesClass{classConn}
+ 
+% classe de base
+ 
+\LoadClass[a5paper, 12pt]{article}
+ 
+% extensions
+ 
+\RequirePackage{base}
+\RequirePackage{none_beamer}
+\RequirePackage{colorscheme}
+% pour redéfinir \section
+\RequirePackage[explicit]{titlesec}
+
+% géométrie
+\RequirePackage{geometry}
+\geometry{left=10mm,right=10mm, top=10mm}
+ 
+% commandes personnelles
+
+% Les en-tête et les pieds de pages
+\RequirePackage{fancyhdr}
+\pagestyle{empty}
+%\renewcommand\headrulewidth{0pt}
+%\fancyhead[R]{}
+%\fancyfoot[C]{}
+
+% Description du devoir
+\newcommand{\op@entete}{}
+\newcommand{\op@soustitre}{}
+\newcommand{\op@classe}{}
+\newcommand{\op@titre}{Connaissance}
+
+\newcommand{\classe}[1]{\renewcommand{\op@classe}{#1}}
+\newcommand{\titre}[1]{\renewcommand{\op@titre}{#1}}
+
+\renewcommand{\op@soustitre}{\op@classe{} -- \@date{}}%
+\renewcommand{\op@entete}{\@date}        
+
+
+% Redéfinition de maketitle pour ne plus avoir la date
+\newcounter{sujet}
+\setcounter{sujet}{0}
+\newcommand{\sujet}{%
+    \clearpage
+    \setcounter{exo}{0}
+    \addtocounter{sujet}{1}
+    \noindent
+    \begin{minipage}{0.8\textwidth}
+        \noindent{\huge \color{title}\bfseries \op@titre}\par
+        \noindent{\color{line}\rule{\linewidth}{1ex}}\par
+        \noindent{\color{subtitle}\bfseries \op@soustitre}\par
+    \end{minipage}
+    \begin{minipage}{0.2\textwidth}
+        \begin{center}
+            \Huge\thesujet
+        \end{center}
+    \end{minipage}
+    \\[0.2cm]
+    Nom - Prénom:
+    \\[0.2cm]
+
+    \normalsize
+}
diff --git a/tools/style/classCours.cls b/tools/style/classCours.cls
new file mode 100644
index 0000000..8223a7c
--- /dev/null
+++ b/tools/style/classCours.cls
@@ -0,0 +1,79 @@
+\NeedsTeXFormat{LaTeX2e}
+ 
+\ProvidesClass{classCours}
+ 
+% classe de base
+ 
+\LoadClassWithOptions{article}
+ 
+% extensions
+ 
+\RequirePackage{base}
+\RequirePackage{none_beamer}
+\RequirePackage{colorscheme}
+
+% géométrie
+\RequirePackage{geometry}
+\geometry{left=20mm,right=20mm, top=15mm, bottom=20mm}
+
+%\RequirePackage{arev}
+\RequirePackage{kpfonts}
+\renewcommand*\familydefault{\sfdefault}
+\RequirePackage[T1]{fontenc}
+
+% commandes personnelles
+
+% Les en-tête et les pieds de pages
+\RequirePackage{fancyhdr}
+\pagestyle{fancy}
+\fancyhf{}
+
+\renewcommand{\headrulewidth}{0pt}
+%\setlength{\headheight}{15.2pt}
+\setlength{\headsep}{5pt}
+
+\newcommand{\op@boiteentete}{\makebox[0pt][l]{\hspace*{-3ex}%
+    \color{bgentete}\rule[-0.8ex]{\linewidth+6ex}{3ex}%
+    }}
+
+\fancyhead[L]{%
+    \op@boiteentete%
+    \small\op@typedoc \op@titre%
+    }
+\fancyhead[R]{\small\scshape\op@entete}
+\fancyfoot[R]{\color{footer}\thepage}
+\fancyfoot[L]{\color{footer}\scriptsize\op@classe{} -- \op@annee}
+
+\fancypagestyle{plain}{% 
+    \fancyhf{}
+    \fancyfoot[R]{\color{footer}\thepage}
+    \fancyfoot[L]{\color{footer}\scriptsize\op@classe{} -- \op@annee}
+    % \fancyfoot[R]{\thepage}
+    % \fancyfoot[L]{\scriptsize\op@classe{} -- \op@annee}
+    }
+
+
+% Description du Cours
+\newcommand{\op@entete}{}
+\newcommand{\op@soustitre}{}
+\newcommand{\op@classe}{}
+\newcommand{\op@typedoc}{}
+\newcommand{\op@typedoctmp}{}
+\newcommand{\op@titre}{}
+
+\newcommand{\classe}[1]{\renewcommand{\op@classe}{#1}}
+\newcommand{\titre}[1]{\renewcommand{\op@titre}{#1}}
+
+\renewcommand{\op@typedoc}{Cours: }
+\renewcommand{\op@soustitre}{\op@classe{} -- \@date{}}%
+\renewcommand{\op@entete}{\@date}        
+
+
+% Redéfinition de maketitle pour ne plus avoir la date
+\renewcommand{\maketitle}{%
+		\thispagestyle{plain}
+		\noindent{\huge \color{title}\bfseries \op@typedoc \op@titre}\par
+		\noindent{\color{line}\rule{\linewidth}{1ex}}\par
+		\noindent{\color{subtitle}\bfseries \op@soustitre}\par
+		\vspace{2.5\baselineskip}
+}
diff --git a/tools/style/classPres.cls b/tools/style/classPres.cls
new file mode 100755
index 0000000..8230da2
--- /dev/null
+++ b/tools/style/classPres.cls
@@ -0,0 +1,21 @@
+\NeedsTeXFormat{LaTeX2e}
+ 
+\ProvidesClass{classPres}
+ 
+% Classe de base - Beamer
+\pdfminorversion=4
+\LoadClassWithOptions{beamer}
+
+\usetheme{Singapore}
+\usepackage[defaultsans]{droidsans}
+\usepackage[T1]{fontenc}
+
+% extensions
+ 
+\RequirePackage{base}
+\RequirePackage{colorscheme}
+\geometry{left=10mm,right=10mm, top=0mm}
+
+
+% Les tableaux
+\renewcommand{\arraystretch}{1.5}
diff --git a/tools/style/classReport.cls b/tools/style/classReport.cls
new file mode 100644
index 0000000..4ae7ee9
--- /dev/null
+++ b/tools/style/classReport.cls
@@ -0,0 +1,55 @@
+\NeedsTeXFormat{LaTeX2e}
+ 
+\ProvidesClass{classReport}
+
+% classe de base
+ 
+%\LoadClass[a4paper,12pt, landscape, twocolumn]{article}
+\LoadClass[a5paper,12pt]{article}
+ 
+% extensions
+ 
+\RequirePackage{base}
+\RequirePackage{colorscheme}
+
+%\RequirePackage{xcolor,colortbl}
+
+\pagestyle{empty}
+
+\RequirePackage{geometry}
+%\geometry{landscape}
+\geometry{left=5mm,right=5mm,top=10mm, bottom= 10mm}
+
+% Séparation au milieu
+\setlength{\columnsep}{5pt}		% default=10pt
+\setlength{\columnseprule}{0pt}		% default=0pt (no line)
+
+
+% Décorations
+\newcommand{\op@classe}{}
+\newcommand{\op@titre}{}
+\newcommand{\classe}[1]{\renewcommand{\op@classe}{#1}}
+\newcommand{\titre}[1]{\renewcommand{\op@titre}{#1}}
+\newcommand{\op@soustitre}{\op@classe{} \hfill \@date{}}%
+
+\renewcommand{\maketitle}{%
+		\noindent{\huge \color{title}\bfseries Bilan \op@titre}\par
+		\noindent{\color{line}\rule{\linewidth}{1ex}}\par
+		\noindent{\color{subtitle}\bfseries \op@soustitre}\par
+		\vspace{1.5\baselineskip}
+}
+
+% Les couleurs de la réussite
+% \newcommand{\NoRep}{/}
+% \newcommand{\RepZ}{\cellcolor{black!05}}
+% \newcommand{\RepU}{\cellcolor{black!30}}
+% \newcommand{\RepD}{\cellcolor{black!60}}
+% \newcommand{\RepT}{\cellcolor{black}}
+\usepackage{tikzsymbols}
+
+%\newcommand{\RepT}{\color{black!10}\Changey[2][black!70]{0.8}\color{text}}
+\newcommand{\RepT}{\Smiley[2][black!70]}
+\newcommand{\RepD}{\Sey[2][black!40]}
+\newcommand{\RepU}{\Neutrey[2][black!10]}
+\newcommand{\RepZ}{\Sadey[2]}
+\newcommand{\NoRep}{(??)}
diff --git a/tools/style/colorscheme.sty b/tools/style/colorscheme.sty
new file mode 100755
index 0000000..1951b9a
--- /dev/null
+++ b/tools/style/colorscheme.sty
@@ -0,0 +1,51 @@
+\NeedsTeXFormat{LaTeX2e}
+ 
+
+% Couleurs,
+\RequirePackage{xcolor}
+\RequirePackage{colortbl}
+
+% Couleurs éléments
+
+% \definecolor{coulpied}{couleur3}
+% \definecolor{coulnumexos}{couleur5}
+% \definecolor{coulrule}{couleur5}
+% \definecolor{coulsection}{couleur1}
+% \definecolor{coultable1}{couleur4}
+% \definecolor{coultable2}{couleur3}
+% \definecolor{coultheo}{couleur4}
+% \definecolor{couldef}{couleur3}
+
+% Solarized theme
+\definecolor{base03}{HTML}{002b36}
+\definecolor{base02}{HTML}{073642}
+\definecolor{base01}{HTML}{586e75}
+\definecolor{base00}{HTML}{657b83}
+\definecolor{base0}{HTML}{839496}
+\definecolor{base1}{HTML}{93a1a1}
+\definecolor{base2}{HTML}{eee8d5}
+\definecolor{base3}{HTML}{FDF6E3}
+\definecolor{yellow}{HTML}{B58900}
+\definecolor{orange}{HTML}{cb4b16}
+\definecolor{red}{HTML}{DC322F}
+\definecolor{magenta}{HTML}{d33682}
+\definecolor{violet}{HTML}{6c71c4}
+\definecolor{blue}{HTML}{268bd2}
+\definecolor{cyan}{HTML}{2aa198}
+\definecolor{green}{HTML}{859900}
+
+% My theme
+\colorlet{text}{base03}
+\colorlet{footer}{base02}
+\colorlet{bgentete}{base2}
+
+\colorlet{title}{blue}
+\colorlet{subtitle}{base02}
+\colorlet{line}{base1}
+\colorlet{comments}{base01}
+\colorlet{exercise}{blue}
+\colorlet{note}{red}
+
+
+\colorlet{highlightbg}{base2}
+\colorlet{tabular}{base3}
diff --git a/tools/style/myXsim.sty b/tools/style/myXsim.sty
new file mode 100644
index 0000000..73627e3
--- /dev/null
+++ b/tools/style/myXsim.sty
@@ -0,0 +1,95 @@
+\NeedsTeXFormat{LaTeX2e}
+% extensions
+ 
+\RequirePackage{colorscheme}
+\RequirePackage{base}
+\RequirePackage{myhdr}
+
+\RequirePackage{geometry}
+%\geometry{landscape}
+\geometry{left=15mm,right=15mm, bottom= 15mm, top=15mm}
+
+%\firstpageheader{\op@boiteentete\small\scshape\op@entete}{}{\small\op@typedoc \op@titre} % Header de la première page
+ 
+
+%\setlength{\oddsidemargin}{0in}		% default=0in
+%\setlength{\textwidth}{9in}		% default=9in
+
+\setlength{\columnsep}{30pt}		% default=10pt
+\setlength{\columnseprule}{1pt}		% default=0pt (no line)
+
+%\setlength{\textheight}{5.85in}		% default=5.15in
+%\setlength{\topmargin}{-0.40in}		% default=0.20in
+%\setlength{\headsep}{0.35in}		% default=0.35in
+
+
+%\renewcommand{\op@entete}{\op@classe}        
+
+
+\RequirePackage{xsim}
+
+\xsimsetup{
+    path={exercises}
+}
+
+\DeclareExerciseTranslations{total}{
+    French = total ,
+}
+
+\DeclareExerciseEnvironmentTemplate{exo}{%
+    \subsection*
+    {%
+        \color{exercise}{\XSIMmixedcase{\GetExerciseName}}\nobreakspace
+        \GetExerciseProperty{counter}%
+        \hspace{0.5cm} \color{line}\hrulefill \hspace{0.5cm} 
+        \color{exercise}
+        \IfInsideSolutionF
+        {%
+            \GetExercisePropertyT{subtitle}
+            {{\PropertyValue}}%
+        }%
+        \noindent
+    }
+}{}
+\xsimsetup{exercise/template=exo}
+
+\DeclareExerciseTableTemplate{DNB}{%
+    \XSIMputright\ExerciseTableCode{%
+        \hline
+        \XSIMifblankTF{\ExerciseType}
+        {}
+        {\XSIMmixedcase{\GetExerciseParameter{exercise-name}}}
+        &
+        \XSIMmixedcase{\XSIMtranslate{points}} \\
+        \hline
+    }%
+    \ForEachUsedExerciseByType{%
+        \XSIMifeqTF{#1}{\ExerciseTableType{#1}}
+        {%
+            \XSIMifblankTF{\ExerciseType}
+            {%
+                \XSIMputright\ExerciseTableCode{%
+                    \XSIMmixedcase{\ExerciseParameterGet{#1}{exercise-name} }%
+                }%
+            }
+            {}%
+            \XSIMputright\ExerciseTableCode
+            {#3 & \XSIMifblankTF{#5}{\printgoal{0}}{\printgoal{#5}}\\ }%
+        }
+        {}%
+    }
+    \XSIMputright\ExerciseTableCode{%
+        \hline
+        \XSIMmixedcase{\XSIMtranslate{total}} &
+        \XSIMifblankTF{\ExerciseType}
+        {\TotalExerciseGoal{points}{}{}}
+        {\TotalExerciseTypeGoal{\ExerciseType}{points}{}{}} \\
+        \hline
+    }%
+    \XSIMexpandcode{%
+        \noexpand\begin{tabular}{|\XSIMifblankTF{\ExerciseType}{l}{c}|c|}
+            \noexpand\ExerciseTableCode
+        \noexpand\end{tabular}%
+    }%
+}
+
diff --git a/tools/style/myhdr.sty b/tools/style/myhdr.sty
new file mode 100644
index 0000000..448b839
--- /dev/null
+++ b/tools/style/myhdr.sty
@@ -0,0 +1,94 @@
+\NeedsTeXFormat{LaTeX2e}
+% extensions
+ 
+\RequirePackage{colorscheme}
+\RequirePackage{lastpage}
+
+\RequirePackage{fancyhdr}
+
+
+\newcommand{\op@entete}{}
+\newcommand{\op@typedoctmp}{}
+\newcommand{\op@tribe}{}
+\newcommand{\op@duree}{}
+\newcommand{\op@sujet}{}
+\newcommand{\op@subtitle}{\op@tribe{} -- \@date{}}
+
+\newcommand{\tribe}[1]{\renewcommand{\op@tribe}{#1}}
+\newcommand{\duree}[1]{\renewcommand{\op@duree}{#1}}
+\newcommand{\sujet}[1]{\renewcommand{\op@sujet}{Sujet #1}}
+
+%% Redéfinition de maketitle 
+\renewcommand{\maketitle}{%
+    \noindent{\huge \color{title}\bfseries \@title}\par
+    \noindent{\color{line}\rule{\linewidth}{1ex}}\par
+    \noindent{\color{subtitle}\bfseries \op@subtitle \hfill \large\op@sujet}\par
+    %\vspace{2.5\baselineskip}
+    \thispagestyle{plain}
+}
+
+%%% Page de garde
+\renewcommand{\titlepage}{%
+    \pagestyle{plain}
+    \begin{center}
+        \Huge  \@title \\
+        \vfill
+        \Huge \op@tribe \@date \\[1cm]
+
+        \vfill
+        \fbox{
+            \parbox{0.7\textwidth}{\large Épreuve de :
+                \begin{center}
+                    \Huge MATHÉMATIQUES
+                \end{center}
+                \Large Durée de l'épreuve: \op@duree
+                \\[1cm]
+            }
+        }
+        \vfill
+
+            ~\\[1cm]
+            \normalsize
+            Ce sujet comporte \pageref{LastPage}\, pages, numérotées de 1 / \pageref{LastPage}\; à \pageref{LastPage}/ \pageref{LastPage}\\
+            Dès qu'il vous est remis, assurez-vous qu'il est complet.
+            ~\\[0.5cm]
+
+            L'utilisation de la calculatrice est autorisée.\\
+            L'échange de calculatrice entre les élèves est strictement interdit.\\
+            L'usage du dictionnaire n'est pas autorisé. \\[1cm]
+
+            \textbf{10 points} sont réservés à l'orthographe et à la présentation.
+
+            \gradingtable[type=exercise,template=DNB]
+
+        \vfill
+    \end{center}
+    \clearpage
+}
+
+% Header et Footer
+\pagestyle{fancy}
+
+%\setlength{\headheight}{10pt}
+%\fancyheadoffset{\textwidth}
+
+\renewcommand{\headrulewidth}{0pt}
+\renewcommand{\footrulewidth}{0pt}
+
+\newcommand{\op@boiteentete}{\makebox[0pt][l]{\hspace*{-3ex}%
+    \color{bgentete}\rule[-0.8ex]{\textwidth-5ex}{3ex}%
+    }}
+\lhead{\scriptsize\op@boiteentete \@title}
+\chead{}
+\rhead{\scriptsize\@date}
+\lfoot{\scriptsize\op@boiteentete \op@subtitle}
+\cfoot{}
+\rfoot{\scriptsize\thepage\ / \pageref{LastPage}}
+\fancypagestyle{plain}{ %
+    \fancyhf{} % remove everything
+    \renewcommand{\headrulewidth}{0pt} % remove lines as well
+    \renewcommand{\footrulewidth}{0pt}
+    \lfoot{\scriptsize\op@boiteentete \op@subtitle}
+    \cfoot{}
+    \rfoot{\scriptsize\thepage\ / \pageref{LastPage}}
+}
diff --git a/tools/style/none_beamer.sty b/tools/style/none_beamer.sty
new file mode 100755
index 0000000..4baa28a
--- /dev/null
+++ b/tools/style/none_beamer.sty
@@ -0,0 +1,8 @@
+\NeedsTeXFormat{LaTeX2e}
+ 
+% Les listes
+\RequirePackage{enumerate}
+\RequirePackage{enumitem}
+\setlist[itemize,1]{label=$\bullet$}
+
+
diff --git a/tools/style/shortcuts.sty b/tools/style/shortcuts.sty
new file mode 100755
index 0000000..93b58c3
--- /dev/null
+++ b/tools/style/shortcuts.sty
@@ -0,0 +1,299 @@
+\NeedsTeXFormat{LaTeX2e}
+
+%%%%%%%%%%%%%%%%%
+%  Raccourcis  %
+%%%%%%%%%%%%%%%%%
+
+%  Ensembles 
+\newcommand{\N}{\mathbb{N}}
+\newcommand{\Z}{\mathbb{Z}}
+%\newcommand{\D}{\mathbb{D}}
+\newcommand{\Q}{\mathbb{Q}}
+\newcommand{\R}{\mathbb{R}}
+\newcommand{\C}{\mathbb{C}}
+
+% intervalles ouvert ouvert
+\newcommand{\intOO}[2]{\left]{#1}\,{;}\,{#2}\right[}
+% intervalles ouvert fermé 
+\newcommand{\intOF}[2]{\left]{#1}\,{;}\,{#2}\right]}
+% intervalles fermé ouvert
+\newcommand{\intFO}[2]{\left[{#1}\,{;}\,{#2}\right[}
+% intervalles fermé fermé
+\newcommand{\intFF}[2]{\left[{#1}\,{;}\,{#2}\right]}
+
+
+%% Vecteurs
+% représentation d'un vecteur
+\renewcommand{\vec}[1]{\overrightarrow{#1}}
+% Norme d'un vecteur
+\newcommand{\norme}[1]{||\vec{#1}||}
+% Produit scalaire 
+\newcommand{\scal}[2]{\vec{#1} \cdot \vec{#2}}
+\newcommand{\vectCoord}[2]{%
+    {\renewcommand{\arraystretch}{1}%
+    \left(\begin{array}{c} #1 \\ #2 \end{array}  \right)%
+    }%
+}
+
+%% Proba
+\newcommand{\coefBino}[2]{\vectCoord{#1}{#2}}
+
+%% Logique
+\renewcommand{\equiv}{\Leftrightarrow}
+
+%% Calculatrice
+\usepackage{listings}
+\newcommand{\calc}[1]{\Ovalbox{\lstinline|#1|}}
+%\newcommand{\calc}[1]{\verb!#1!}
+
+%% Autres
+\newcommand{\TODO}[1]{\textcolor{red}{note(#1)}}
+
+%% Poser des opérations
+% \RequirePackage[letterspace=500]{microtype}
+% \newcommand{\poseOP}[3]{%
+%     \textls{
+%     $\begin{array}{cr}
+%         & #1 \\[-0.3cm]
+%         #2 & #3 \\
+%         \hline
+%         &
+%     \end{array}$}
+% }
+
+% Icones
+\newcommand{\icon}[2][scale=0.4]{%
+\includegraphics[#1]{icons/#2.png}%
+}
+
+% Icones des compétences
+\newcommand{\iconScale}{0.3}
+\newcommand{\Cher}[1][scale=\iconScale]{%
+    \icon[#1]{card-pick}
+}
+\newcommand{\Mod}[1][scale=\iconScale]{%
+    \icon[#1]{processor}
+}
+\newcommand{\Rep}[1][scale=\iconScale]{%
+    \icon[#1]{chart}
+}
+\newcommand{\Rai}[1][scale=\iconScale]{%
+    \icon[#1]{brain}
+    %\icon[#1]{gears}
+}
+\newcommand{\Cal}[1][scale=\iconScale]{%
+    \icon[#1]{computing}
+}
+\newcommand{\Com}[1][scale=\iconScale]{%
+    \icon[#1]{conversation}
+}
+\newcommand{\Con}[1][scale=\iconScale]{%
+    \icon[#1]{book-cover}
+}
+
+% Pour l'évaluation par compétence
+\usepackage{tikzsymbols}
+\usetikzlibrary{babel}
+
+\RequirePackage{xstring}
+\newcommand{\RepLevel}[1]{%
+    \IfEqCase{#1}{%
+        {.}{\Xey[2]}%
+        {0}{\Changey[2]{-1}}%
+        {1}{\Changey[2][black!20]{0}}%
+        {2}{\Changey[2][black!40]{1}}%
+        {3}{\Cooley[2][black!60]}%
+    }[\PackageError{Rep}{Undefinded type of answer: #1}{}]%
+}
+\newcommand{\RepT}{\Cooley[2][black!70]}
+\newcommand{\RepD}{\Changey[2][black!40]{1}}
+\newcommand{\RepU}{\Changey[2][black!10]{0}}
+\newcommand{\RepZ}{\Changey[2]{-1}}
+\newcommand{\NoRep}{\Xey[2]}
+
+\newcommand{\EmptySignalBar}{%
+    \draw (0, 0) rectangle ++(0.8, 1);
+    \draw (1, 0) rectangle ++(0.8, 2);
+    \draw (2, 0) rectangle ++(0.8, 3);
+    \draw (3, 0) rectangle ++(0.8, 4);
+}
+\newcommand{\filledSignalBar}[1]{%
+    \IfEqCase{#1}{%
+        {}{%
+        }
+        {e}{%
+            \EmptySignalBar
+        }
+        {3}{%
+            \EmptySignalBar
+            \filldraw[fill=green] (0, 0) rectangle ++(0.8, 1);
+            \filldraw[fill=green] (1, 0) rectangle ++(0.8, 2);
+            \filldraw[fill=green] (2, 0) rectangle ++(0.8, 3);
+            \filldraw[fill=green] (3, 0) rectangle ++(0.8, 4);
+        }
+        {2}{%
+            \EmptySignalBar
+            \filldraw[fill=green] (0, 0) rectangle ++(0.8, 1);
+            \filldraw[fill=green] (1, 0) rectangle ++(0.8, 2);
+            \filldraw[fill=green] (2, 0) rectangle ++(0.8, 3);
+        }
+        {1}{%
+            \EmptySignalBar
+            \filldraw[fill=yellow] (0, 0) rectangle ++(0.8, 1);
+            \filldraw[fill=yellow] (1, 0) rectangle ++(0.8, 2);
+        }
+        {0}{%
+            \EmptySignalBar
+            \filldraw[fill=red] (0, 0) rectangle ++(0.8, 1);
+        }
+    }[\PackageError{Assesment}{Undefinded type of answer: #1}{}]%
+}
+
+\newcommand{\SignalBar}[1]{%
+    \begin{tikzpicture}[scale=0.15]
+        \filledSignalBar{#1}
+    \end{tikzpicture}
+}
+
+\newcommand{\Assesment}[1]{%
+    \SignalBar{#1}
+    \IfEqCase{#1}{%
+        {3}{%
+            Très bonne maîtrise%
+        }%
+        {2}{%
+            Maîtrise satisfaisante
+        }%
+        {1}{%
+            Maîtrise fragile%
+        }%
+        {0}{%
+            Maîtrise insufisante%
+        }%
+    }[\PackageError{Assesment}{Undefinded type of answer: #1}{}]%
+}
+
+\newcommand{\competencesStatement}{%
+    \begin{multicols}{3}
+        \noindent
+        Nom:  \dotfill \\[0.5cm]
+        Prénom:  \dotfill \\
+        \vfill\none
+        \columnbreak
+        \noindent
+        \Cher Chercher \hfill \SignalBar{e}\\
+        \Mod Modélser \hfill \SignalBar{e}\\
+        \Rep Représenter \hfill \SignalBar{e}\\
+        \vfill\none
+        \columnbreak
+        \noindent
+        \Rai Raisonner \hfill \SignalBar{e}\\
+        \Cal Calculer \hfill \SignalBar{e}\\
+        \Com Communiquer \hfill \SignalBar{e}\\
+    \end{multicols}
+}
+
+
+% ##########################
+% Tikz shortcuts
+% ##########################
+
+% Les dessins
+\RequirePackage{tikz}
+
+%% le cercle trigo
+\newcommand{\cercleTrigo}%
+{%
+    \draw[->, very thick] (-1.2,0) -- (1.3, 0);
+    \draw[->, very thick] (0,-1.2) -- (0,1.3);
+    \draw[very thick] (0,0) circle (1);
+    \draw (0,0) node[below left] {$O$};
+    \draw (1,0) node[below right] {$I$};
+    \draw (0,1) node[above left] {$J$};
+}
+
+%% Le repère orthonormé avec la grille
+%%% \repere{xmin}{xmax}{ymin}{ymax}
+\newcommand{\repere}[4]%
+{%
+        \draw[very thin, gray] (#1,#3) grid (#2,#4);
+        \draw[->, very thick] (#1,0) -- (#2,0);
+        \draw[->, very thick] (0,#3) -- (0,#4);
+        \draw (0,0) node[below right, scale=0.7 ] {$O$};
+        \draw (0,1) node {-} node[left] {$J$};
+        \draw (1,0) node[rotate=90] {-} node[below] {$I$};
+    }
+\newcommand{\repereNoGrid}[4]%
+{%
+        \draw[->, very thick] (#1,0) -- (#2,0);
+        \draw[->, very thick] (0,#3) -- (0,#4);
+    }
+
+%% Diagramme boite
+%%% \boxplot{Vertical Center}{min}{Q1}{Me}{Q3}{Max}
+\newcommand{\boxplot}[6]%
+{%
+    \filldraw[color=highlightbg, draw=text] (#3, {#1 - 0.5}) rectangle (#5, {#1 + 0.5});
+    \draw (#2, {#1 - 0.5}) -- (#2, {#1 + 0.5}) node[above] {$Min$};
+    \draw (#3, {#1 - 0.5}) -- (#3, {#1 + 0.5}) node[above] {$Q_1$};
+    \draw (#4, {#1 - 0.5}) -- (#4, {#1 + 0.5}) node[above] {$Me$};
+    \draw (#5, {#1 - 0.5}) -- (#5, {#1 + 0.5}) node[above] {$Q_3$};
+    \draw (#6, {#1 - 0.5}) -- (#6, {#1 + 0.5}) node[above] {$Max$};
+
+    \draw (#2, #1) -- (#3, #1);
+    \draw (#5, #1) -- (#6, #1);
+
+    %\draw ({(#2 +#3)/2}, #1) node[above] {25\%};
+    %\draw ({(#3 +#4)/2}, #1) node[above] {25\%};
+    %\draw ({(#4 +#5)/2}, #1) node[above] {25\%};
+    %\draw ({(#5 +#6)/2}, #1) node[above] {25\%};
+
+}
+\newcommand{\boxplotNoNames}[6]%
+{%
+    \filldraw[color=highlightbg, draw=text] (#3, {#1 - 0.5}) rectangle (#5, {#1 + 0.5});
+    \draw (#2, {#1 - 0.5}) -- (#2, {#1 + 0.5});
+    \draw (#3, {#1 - 0.5}) -- (#3, {#1 + 0.5});
+    \draw (#4, {#1 - 0.5}) -- (#4, {#1 + 0.5});
+    \draw (#5, {#1 - 0.5}) -- (#5, {#1 + 0.5});
+    \draw (#6, {#1 - 0.5}) -- (#6, {#1 + 0.5});
+
+    \draw (#2, #1) -- (#3, #1);
+    \draw (#5, #1) -- (#6, #1);
+}
+
+
+\usetikzlibrary{quotes,arrows.meta}
+
+\tikzset{
+    % drawing parallelepipoid
+    annotated cuboid/.pic={
+        \tikzset{%
+            every edge quotes/.append style={midway, auto},
+            /cuboid/.cd,
+            #1
+        }
+        \draw [every edge/.append style={pic actions, densely dashed, opacity=.5}, pic actions]
+        (0,0,0) coordinate (o) -- ++(-\cubescale*\cubex,0,0) coordinate (a) -- ++(0,-\cubescale*\cubey,0) coordinate (b) edge coordinate [pos=1] (g) ++(0,0,-\cubescale*\cubez)  -- ++(\cubescale*\cubex,0,0) coordinate (c) -- cycle
+        (o) -- ++(0,0,-\cubescale*\cubez) coordinate (d) -- ++(0,-\cubescale*\cubey,0) coordinate (e) edge (g) -- (c) -- cycle
+        (o) -- (a) -- ++(0,0,-\cubescale*\cubez) coordinate (f) edge (g) -- (d) -- cycle;
+        \path [every edge/.append style={pic actions, |-|}]
+        (b) +(0,-5pt) coordinate (b1) edge ["\cubex \cubeunits"'] (b1 -| c)
+        (b) +(-5pt,0) coordinate (b2) edge ["\cubey \cubeunits"] (b2 |- a)
+        (c) +(3.5pt,-3.5pt) coordinate (c2) edge ["\cubez \cubeunits"'] ([xshift=3.5pt,yshift=-3.5pt]e)
+        ;
+    },
+    /cuboid/.search also={/tikz},
+    /cuboid/.cd,
+    width/.store in=\cubex,
+    height/.store in=\cubey,
+    depth/.store in=\cubez,
+    units/.store in=\cubeunits,
+    scale/.store in=\cubescale,
+    width=10,
+    height=10,
+    depth=10,
+    units=cm,
+    scale=.1,
+}
+