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module2/exo1/toy_notebook_fr.ipynb

@@ -10,7 +10,9 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {},
+   "metadata": {
+    "hideCode": true
+   },
    "outputs": [
     {
      "data": {
@@ -30,7 +32,10 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {},
+   "metadata": {
+    "hideCode": true,
+    "hideOutput": true
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -82,17 +87,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "array([ 71.58479787, 129.24346877, 113.22449086, ...,  99.02181597,\n",
-       "        93.23619228, 104.60198482])"
+       "array([124.96136552,  75.9640558 ,  91.08229044, ..., 101.52625046,\n",
+       "       108.22074815,  93.11540881])"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -103,7 +108,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -112,7 +117,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -121,12 +126,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -152,7 +157,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -161,7 +166,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -176,16 +181,10 @@
     "%%R\n",
     "plot(cars)"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
+  "celltoolbar": "Hide code",
   "kernelspec": {
    "display_name": "Python 3",
    "language": "python",