2022-2023/2gt1/221214_DS2/Ds2.ipynb

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       "/*\n",
       " * @copyright 2016 Sean Connelly (@voidqk), http://syntheti.cc\n",
       " * @license MIT\n",
       " * @preserve Project Home: https://github.com/voidqk/polybooljs\n",
       " */\n",
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       "/*!\n",
       " * The buffer module from node.js, for the browser.\n",
       " *\n",
       " * @author   Feross Aboukhadijeh <https://feross.org>\n",
       " * @license  MIT\n",
       " */\n",
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       "/*!\n",
       " * Determine if an object is a Buffer\n",
       " *\n",
       " * @author   Feross Aboukhadijeh <https://feross.org>\n",
       " * @license  MIT\n",
       " */\n",
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       "/*!\n",
       " * pad-left <https://github.com/jonschlinkert/pad-left>\n",
       " *\n",
       " * Copyright (c) 2014-2015, Jon Schlinkert.\n",
       " * Licensed under the MIT license.\n",
       " */\n",
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       "/*!\n",
       " * repeat-string <https://github.com/jonschlinkert/repeat-string>\n",
       " *\n",
       " * Copyright (c) 2014-2015, Jon Schlinkert.\n",
       " * Licensed under the MIT License.\n",
       " */\n",
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       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.display import Markdown as md\n",
    "from IPython.display import display, HTML\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import ipywidgets as widgets\n",
    "from pathlib import Path\n",
    "from datetime import datetime\n",
    "from recopytex import flat_df_students, pp_q_scores\n",
    "from datetime import datetime\n",
    "\n",
    "\n",
    "import chart_studio.plotly as py\n",
    "import plotly.graph_objects as go\n",
    "import plotly.figure_factory as ff\n",
    "import plotly.express as px\n",
    "\n",
    "\n",
    "from plotly.offline import iplot, init_notebook_mode\n",
    "init_notebook_mode()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "05307eef",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-09-27T11:48:08.209887Z",
     "iopub.status.busy": "2022-09-27T11:48:08.209511Z",
     "iopub.status.idle": "2022-09-27T11:48:08.210992Z",
     "shell.execute_reply": "2022-09-27T11:48:08.211278Z"
    },
    "papermill": {
     "duration": 0.081194,
     "end_time": "2022-09-27T11:48:08.211363",
     "exception": false,
     "start_time": "2022-09-27T11:48:08.130169",
     "status": "completed"
    },
    "tags": [
     "injected-parameters"
    ]
   },
   "outputs": [],
   "source": [
    "# Parameters\n",
    "tribe = \"2gt1\"\n",
    "assessment = \"Ds2 - QCM\"\n",
    "date = \"14/12/22\"\n",
    "scores_file = \"../221214_DS2.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "2a41f502",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-09-27T11:48:08.528130Z",
     "iopub.status.busy": "2022-09-27T11:48:08.527692Z",
     "iopub.status.idle": "2022-09-27T11:48:08.530503Z",
     "shell.execute_reply": "2022-09-27T11:48:08.530107Z"
    },
    "extensions": {
     "jupyter_dashboards": {
      "version": 1,
      "views": {
       "grid_default": {},
       "report_default": {
        "hidden": false
       }
      }
     }
    },
    "papermill": {
     "duration": 0.086523,
     "end_time": "2022-09-27T11:48:08.530574",
     "exception": false,
     "start_time": "2022-09-27T11:48:08.444051",
     "status": "completed"
    },
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "# Ds2 - QCM (14/12/22) pour 2gt1"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "if date is None:\n",
    "    display(md(f\"# {assessment} pour {tribe}\"))\n",
    "else:\n",
    "    display(md(f\"# {assessment} ({date}) pour {tribe}\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "24ff9733",
   "metadata": {
    "papermill": {
     "duration": 0.166951,
     "end_time": "2022-09-27T11:48:19.360034",
     "exception": false,
     "start_time": "2022-09-27T11:48:19.193083",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Nom', 'Note', 'Image_f', 'Image_g', 'antecedents', 'calculer_proba_5',\n",
      "       'calculer_proba_fille_betedeville', 'calculer_proba_garcon',\n",
      "       'comparaison_fonction', 'def_equalite', 'egalite', 'equation',\n",
      "       'inequation', 'mult_vecteurs', 'nombre_issues', 'somme_3_vecteurs',\n",
      "       'somme_debut_different', 'somme_debut_different_hors',\n",
      "       'somme_meme_debut', 'tracer_somme_complexe', 'tracer_somme_simple',\n",
      "       'translation'],\n",
      "      dtype='object')\n",
      "Nom                                  object\n",
      "Note                                float64\n",
      "Image_f                               int64\n",
      "Image_g                               int64\n",
      "antecedents                         float64\n",
      "calculer_proba_5                      int64\n",
      "calculer_proba_fille_betedeville      int64\n",
      "calculer_proba_garcon                 int64\n",
      "comparaison_fonction                  int64\n",
      "def_equalite                        float64\n",
      "egalite                             float64\n",
      "equation                              int64\n",
      "inequation                            int64\n",
      "mult_vecteurs                       float64\n",
      "nombre_issues                         int64\n",
      "somme_3_vecteurs                    float64\n",
      "somme_debut_different               float64\n",
      "somme_debut_different_hors          float64\n",
      "somme_meme_debut                    float64\n",
      "tracer_somme_complexe                 int64\n",
      "tracer_somme_simple                   int64\n",
      "translation                           int64\n",
      "dtype: object\n"
     ]
    }
   ],
   "source": [
    "df = pd.read_csv(scores_file, delimiter=\";\")\n",
    "df.drop(columns=[\"Copie\", \"A:Nom\"], inplace=True)\n",
    "print(df.columns)\n",
    "print(df.dtypes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "77b62a99",
   "metadata": {},
   "outputs": [],
   "source": [
    "questions_col = ['Image_f', 'Image_g', 'antecedents', 'calculer_proba_5',\n",
    "       'calculer_proba_fille_betedeville', 'calculer_proba_garcon',\n",
    "       'comparaison_fonction', 'def_equalite', 'egalite', 'equation',\n",
    "       'inequation', 'mult_vecteurs', 'nombre_issues', 'somme_3_vecteurs',\n",
    "       'somme_debut_different', 'somme_debut_different_hors',\n",
    "       'somme_meme_debut', 'tracer_somme_complexe', 'tracer_somme_simple',\n",
    "       'translation']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "b3e44bfa",
   "metadata": {},
   "outputs": [
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       "config": {
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       "data": [
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         "marker": {
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          "pattern": {
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         "name": "",
         "nbinsx": 40,
         "offsetgroup": "",
         "orientation": "v",
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         "xaxis": "x",
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       ],
       "layout": {
        "barmode": "relative",
        "legend": {
         "tracegroupgap": 0
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        "margin": {
         "t": 60
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        "template": {
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       "      <td>10.0</td>\n",
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       "      <td>14.0</td>\n",
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       "      <th>19</th>\n",
       "      <td>KICHENASSAMY Sanjay</td>\n",
       "      <td>10.0</td>\n",
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       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>LE VEUZIT Adrien</td>\n",
       "      <td>18.0</td>\n",
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       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>LETIF Ilef</td>\n",
       "      <td>11.5</td>\n",
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       "      <th>22</th>\n",
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       "      <td>11.5</td>\n",
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       "      <th>23</th>\n",
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       "      <td>14.0</td>\n",
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       "      <th>24</th>\n",
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       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>TROPHARDY Eline</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Nom  Note\n",
       "0          ACHOUR Ilyes   8.0\n",
       "1         BELARBI Islem   8.5\n",
       "2     BEN ELALLID Hajar   5.0\n",
       "3           BISWAS Lina  14.0\n",
       "4        BOULAABA Rayan  16.5\n",
       "5           BREZUN Ines  13.5\n",
       "6           BUGNON Enzo  10.0\n",
       "7    CALLEWAERT Idaline   9.5\n",
       "8        CATTIN Clément  17.0\n",
       "9     CHRISTMANN Nathan   6.5\n",
       "10     DECOSTER Clément  18.5\n",
       "11       DUPONT Jessica  15.0\n",
       "12        GASAN Jéssica  16.5\n",
       "13      GEORGET Raphaël  19.5\n",
       "14         HABBAZ Hajar  14.5\n",
       "15    JACQUEMIER Samuel  17.0\n",
       "16    JACQUIER Juliette  10.0\n",
       "17        JOVIC Atanase  12.5\n",
       "18         KASSI Cheïma  14.0\n",
       "19  KICHENASSAMY Sanjay  10.0\n",
       "20     LE VEUZIT Adrien  18.0\n",
       "21           LETIF Ilef  11.5\n",
       "22         MANJALI Hiba  11.5\n",
       "23          MUTTONI Lou  14.0\n",
       "24           NEIVA Hugo  17.5\n",
       "25         OLLIET Gioia   9.5\n",
       "26         PERNOT Gabin  13.0\n",
       "27          RIZZI Elisa  14.5\n",
       "28         ROSTANT Emma   7.5\n",
       "29         SIBABA Moaad   8.0\n",
       "30        SOUJOL Damien  12.0\n",
       "31         THORAL Fanny   6.5\n",
       "32      TOURRETTE Elise  12.5\n",
       "33      TROPHARDY Eline  18.0"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[[\"Nom\",\"Note\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "2b06575d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Nom</th>\n",
       "      <th>Note</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BEN ELALLID Hajar</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>THORAL Fanny</td>\n",
       "      <td>6.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>CHRISTMANN Nathan</td>\n",
       "      <td>6.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>ROSTANT Emma</td>\n",
       "      <td>7.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ACHOUR Ilyes</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>SIBABA Moaad</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BELARBI Islem</td>\n",
       "      <td>8.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>OLLIET Gioia</td>\n",
       "      <td>9.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>CALLEWAERT Idaline</td>\n",
       "      <td>9.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>KICHENASSAMY Sanjay</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>JACQUIER Juliette</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>BUGNON Enzo</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>MANJALI Hiba</td>\n",
       "      <td>11.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>LETIF Ilef</td>\n",
       "      <td>11.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>SOUJOL Damien</td>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>TOURRETTE Elise</td>\n",
       "      <td>12.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>JOVIC Atanase</td>\n",
       "      <td>12.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>PERNOT Gabin</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>BREZUN Ines</td>\n",
       "      <td>13.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BISWAS Lina</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>KASSI Cheïma</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>MUTTONI Lou</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>HABBAZ Hajar</td>\n",
       "      <td>14.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>RIZZI Elisa</td>\n",
       "      <td>14.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>DUPONT Jessica</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>BOULAABA Rayan</td>\n",
       "      <td>16.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>GASAN Jéssica</td>\n",
       "      <td>16.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>CATTIN Clément</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>JACQUEMIER Samuel</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>NEIVA Hugo</td>\n",
       "      <td>17.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>LE VEUZIT Adrien</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>TROPHARDY Eline</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>DECOSTER Clément</td>\n",
       "      <td>18.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>GEORGET Raphaël</td>\n",
       "      <td>19.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Nom  Note\n",
       "2     BEN ELALLID Hajar   5.0\n",
       "31         THORAL Fanny   6.5\n",
       "9     CHRISTMANN Nathan   6.5\n",
       "28         ROSTANT Emma   7.5\n",
       "0          ACHOUR Ilyes   8.0\n",
       "29         SIBABA Moaad   8.0\n",
       "1         BELARBI Islem   8.5\n",
       "25         OLLIET Gioia   9.5\n",
       "7    CALLEWAERT Idaline   9.5\n",
       "19  KICHENASSAMY Sanjay  10.0\n",
       "16    JACQUIER Juliette  10.0\n",
       "6           BUGNON Enzo  10.0\n",
       "22         MANJALI Hiba  11.5\n",
       "21           LETIF Ilef  11.5\n",
       "30        SOUJOL Damien  12.0\n",
       "32      TOURRETTE Elise  12.5\n",
       "17        JOVIC Atanase  12.5\n",
       "26         PERNOT Gabin  13.0\n",
       "5           BREZUN Ines  13.5\n",
       "3           BISWAS Lina  14.0\n",
       "18         KASSI Cheïma  14.0\n",
       "23          MUTTONI Lou  14.0\n",
       "14         HABBAZ Hajar  14.5\n",
       "27          RIZZI Elisa  14.5\n",
       "11       DUPONT Jessica  15.0\n",
       "4        BOULAABA Rayan  16.5\n",
       "12        GASAN Jéssica  16.5\n",
       "8        CATTIN Clément  17.0\n",
       "15    JACQUEMIER Samuel  17.0\n",
       "24           NEIVA Hugo  17.5\n",
       "20     LE VEUZIT Adrien  18.0\n",
       "33      TROPHARDY Eline  18.0\n",
       "10     DECOSTER Clément  18.5\n",
       "13      GEORGET Raphaël  19.5"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[[\"Nom\",\"Note\"]].sort_values(by=\"Note\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2c5a98dc",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6ecdc892",
   "metadata": {},
   "outputs": [],
   "source": []
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  {
   "cell_type": "raw",
   "id": "9324eea9",
   "metadata": {},
   "source": []
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  {
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   "execution_count": 59,
   "id": "7086e285",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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