Partage de document

module2/exo1/Test.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Titre : Tutorial "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## code"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "4"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "2+2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "10\n"
+     ]
+    }
+   ],
+   "source": [
+    "x=10\n",
+    "print(x)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "20\n"
+     ]
+    }
+   ],
+   "source": [
+    "x = x + 10\n",
+    "print(x)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Exemple de completion"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "###  Générer un ensemble de nombres aléatoires"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "mu, sigma = 100, 15"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Bibliothèque Numpy chargé et Jupyter fait de la completion sur les objets  ou ombre d'une manière aléatoire"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x = np.random.normal (loc=mu, scale=sigma, size=10000)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### sauvegarder dans une variable avec x = ci-dessus et matplotlib ci-dessous"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### visualiser l'histogramme  par % et intégrer dans le document par inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%matplotlib inline\n",
+    "plt.hist(x)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### commandes diverses avec %lsmagic, commandes intégrer dans python"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/json": {
+       "cell": {
+        "!": "OSMagics",
+        "HTML": "Other",
+        "SVG": "Other",
+        "bash": "Other",
+        "capture": "ExecutionMagics",
+        "debug": "ExecutionMagics",
+        "file": "Other",
+        "html": "DisplayMagics",
+        "javascript": "DisplayMagics",
+        "js": "DisplayMagics",
+        "latex": "DisplayMagics",
+        "markdown": "DisplayMagics",
+        "perl": "Other",
+        "prun": "ExecutionMagics",
+        "pypy": "Other",
+        "python": "Other",
+        "python2": "Other",
+        "python3": "Other",
+        "ruby": "Other",
+        "script": "ScriptMagics",
+        "sh": "Other",
+        "svg": "DisplayMagics",
+        "sx": "OSMagics",
+        "system": "OSMagics",
+        "time": "ExecutionMagics",
+        "timeit": "ExecutionMagics",
+        "writefile": "OSMagics"
+       },
+       "line": {
+        "alias": "OSMagics",
+        "alias_magic": "BasicMagics",
+        "autoawait": "AsyncMagics",
+        "autocall": "AutoMagics",
+        "automagic": "AutoMagics",
+        "autosave": "KernelMagics",
+        "bookmark": "OSMagics",
+        "cat": "Other",
+        "cd": "OSMagics",
+        "clear": "KernelMagics",
+        "colors": "BasicMagics",
+        "conda": "PackagingMagics",
+        "config": "ConfigMagics",
+        "connect_info": "KernelMagics",
+        "cp": "Other",
+        "debug": "ExecutionMagics",
+        "dhist": "OSMagics",
+        "dirs": "OSMagics",
+        "doctest_mode": "BasicMagics",
+        "ed": "Other",
+        "edit": "KernelMagics",
+        "env": "OSMagics",
+        "gui": "BasicMagics",
+        "hist": "Other",
+        "history": "HistoryMagics",
+        "killbgscripts": "ScriptMagics",
+        "ldir": "Other",
+        "less": "KernelMagics",
+        "lf": "Other",
+        "lk": "Other",
+        "ll": "Other",
+        "load": "CodeMagics",
+        "load_ext": "ExtensionMagics",
+        "loadpy": "CodeMagics",
+        "logoff": "LoggingMagics",
+        "logon": "LoggingMagics",
+        "logstart": "LoggingMagics",
+        "logstate": "LoggingMagics",
+        "logstop": "LoggingMagics",
+        "ls": "Other",
+        "lsmagic": "BasicMagics",
+        "lx": "Other",
+        "macro": "ExecutionMagics",
+        "magic": "BasicMagics",
+        "man": "KernelMagics",
+        "matplotlib": "PylabMagics",
+        "mkdir": "Other",
+        "more": "KernelMagics",
+        "mv": "Other",
+        "notebook": "BasicMagics",
+        "page": "BasicMagics",
+        "pastebin": "CodeMagics",
+        "pdb": "ExecutionMagics",
+        "pdef": "NamespaceMagics",
+        "pdoc": "NamespaceMagics",
+        "pfile": "NamespaceMagics",
+        "pinfo": "NamespaceMagics",
+        "pinfo2": "NamespaceMagics",
+        "pip": "PackagingMagics",
+        "popd": "OSMagics",
+        "pprint": "BasicMagics",
+        "precision": "BasicMagics",
+        "prun": "ExecutionMagics",
+        "psearch": "NamespaceMagics",
+        "psource": "NamespaceMagics",
+        "pushd": "OSMagics",
+        "pwd": "OSMagics",
+        "pycat": "OSMagics",
+        "pylab": "PylabMagics",
+        "qtconsole": "KernelMagics",
+        "quickref": "BasicMagics",
+        "recall": "HistoryMagics",
+        "rehashx": "OSMagics",
+        "reload_ext": "ExtensionMagics",
+        "rep": "Other",
+        "rerun": "HistoryMagics",
+        "reset": "NamespaceMagics",
+        "reset_selective": "NamespaceMagics",
+        "rm": "Other",
+        "rmdir": "Other",
+        "run": "ExecutionMagics",
+        "save": "CodeMagics",
+        "sc": "OSMagics",
+        "set_env": "OSMagics",
+        "store": "StoreMagics",
+        "sx": "OSMagics",
+        "system": "OSMagics",
+        "tb": "ExecutionMagics",
+        "time": "ExecutionMagics",
+        "timeit": "ExecutionMagics",
+        "unalias": "OSMagics",
+        "unload_ext": "ExtensionMagics",
+        "who": "NamespaceMagics",
+        "who_ls": "NamespaceMagics",
+        "whos": "NamespaceMagics",
+        "xdel": "NamespaceMagics",
+        "xmode": "BasicMagics"
+       }
+      },
+      "text/plain": [
+       "Available line magics:\n",
+       "%alias  %alias_magic  %autoawait  %autocall  %automagic  %autosave  %bookmark  %cat  %cd  %clear  %colors  %conda  %config  %connect_info  %cp  %debug  %dhist  %dirs  %doctest_mode  %ed  %edit  %env  %gui  %hist  %history  %killbgscripts  %ldir  %less  %lf  %lk  %ll  %load  %load_ext  %loadpy  %logoff  %logon  %logstart  %logstate  %logstop  %ls  %lsmagic  %lx  %macro  %magic  %man  %matplotlib  %mkdir  %more  %mv  %notebook  %page  %pastebin  %pdb  %pdef  %pdoc  %pfile  %pinfo  %pinfo2  %pip  %popd  %pprint  %precision  %prun  %psearch  %psource  %pushd  %pwd  %pycat  %pylab  %qtconsole  %quickref  %recall  %rehashx  %reload_ext  %rep  %rerun  %reset  %reset_selective  %rm  %rmdir  %run  %save  %sc  %set_env  %store  %sx  %system  %tb  %time  %timeit  %unalias  %unload_ext  %who  %who_ls  %whos  %xdel  %xmode\n",
+       "\n",
+       "Available cell magics:\n",
+       "%%!  %%HTML  %%SVG  %%bash  %%capture  %%debug  %%file  %%html  %%javascript  %%js  %%latex  %%markdown  %%perl  %%prun  %%pypy  %%python  %%python2  %%python3  %%ruby  %%script  %%sh  %%svg  %%sx  %%system  %%time  %%timeit  %%writefile\n",
+       "\n",
+       "Automagic is ON, % prefix IS NOT needed for line magics."
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "%lsmagic"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### demander à Jupyter d'utiliser des fragments de code R"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%load_ext rpy2.ipython"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%%R\n",
+    "plot(cars)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### partager  avec commit push pour gitlab et github"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "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": "3.6.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}