From e614f56abaf1f3896242435b1c873e73b11c678c Mon Sep 17 00:00:00 2001
From: cb1e5ba91280d02583d0604166e71c1c
 <cb1e5ba91280d02583d0604166e71c1c@app-learninglab.inria.fr>
Date: Mon, 6 Apr 2020 12:27:24 +0000
Subject: [PATCH] no commit message

---
 module3/exo3/exercice.ipynb | 787 +++++++++++++++++-------------------
 1 file changed, 379 insertions(+), 408 deletions(-)

diff --git a/module3/exo3/exercice.ipynb b/module3/exo3/exercice.ipynb
index 2e9ab90..dae251c 100644
--- a/module3/exo3/exercice.ipynb
+++ b/module3/exo3/exercice.ipynb
@@ -9,7 +9,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 139,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -30,12 +30,12 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Nous récupérons les données les plus récentes sur le site en pointant sur un fichier au format .csv, si cette récupération est possible nous enregistrons une copie de ce fichier. Si pour une raison quelconque nous n'arrivons pas a faire ce téléchargement, nous travaillons sur le dernières données téléchargé."
+    "Nous récupérons les données les plus récentes sur le site en pointant sur un fichier au format .csv, si cette récupération est possible nous enregistrons une copie de ce fichier. Si pour une raison quelconque nous n'arrivons pas à faire ce téléchargement, nous travaillons sur les dernières données téléchargé."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 140,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -317,7 +317,7 @@
        "[756 rows x 10 columns]"
       ]
      },
-     "execution_count": 140,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -344,12 +344,12 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Nous voyons que les noms des colonnes ne sont pas très représentatives, nous modifions  les noms des colonnes"
+    "Nous voyons que les noms des colonnes ne sont pas très représentatives, nous modifions  les noms des colonnes. Les données vide sont représentés par la valeur -99.99, nous remplaçons cette valeur par une valeur plus adéquate NaN dans une autre DataFrame"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 141,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -360,19 +360,7 @@
       "       '      [ppm]', '    [ppm]', '       [ppm]', '    [ppm].1'],\n",
       "      dtype='object')\n"
      ]
-    }
-   ],
-   "source": [
-    "raw_data_1 = raw_data.copy()\n",
-    "print(raw_data.columns)\n",
-    "raw_data_1.columns = ['Yr','Mn','Date 1','Date 2','s1','s2','s3','s4','s5','s6']"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 169,
-   "metadata": {},
-   "outputs": [
+    },
     {
      "data": {
       "text/html": [
@@ -512,232 +500,161 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>23</th>\n",
-       "      <td>1959</td>\n",
-       "      <td>12</td>\n",
-       "      <td>21899</td>\n",
-       "      <td>1959.9562</td>\n",
-       "      <td>315.58</td>\n",
-       "      <td>316.35</td>\n",
-       "      <td>315.72</td>\n",
-       "      <td>316.47</td>\n",
-       "      <td>315.58</td>\n",
-       "      <td>316.35</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>24</th>\n",
-       "      <td>1960</td>\n",
-       "      <td>1</td>\n",
-       "      <td>21930</td>\n",
-       "      <td>1960.0410</td>\n",
-       "      <td>316.43</td>\n",
-       "      <td>316.39</td>\n",
-       "      <td>316.61</td>\n",
-       "      <td>316.56</td>\n",
-       "      <td>316.43</td>\n",
-       "      <td>316.39</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>25</th>\n",
-       "      <td>1960</td>\n",
-       "      <td>2</td>\n",
-       "      <td>21961</td>\n",
-       "      <td>1960.1257</td>\n",
-       "      <td>316.98</td>\n",
-       "      <td>316.35</td>\n",
-       "      <td>317.27</td>\n",
-       "      <td>316.64</td>\n",
-       "      <td>316.98</td>\n",
-       "      <td>316.35</td>\n",
+       "      <th>749</th>\n",
+       "      <td>2020</td>\n",
+       "      <td>6</td>\n",
+       "      <td>43997</td>\n",
+       "      <td>2020.4563</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>26</th>\n",
-       "      <td>1960</td>\n",
-       "      <td>3</td>\n",
-       "      <td>21990</td>\n",
-       "      <td>1960.2049</td>\n",
-       "      <td>317.58</td>\n",
-       "      <td>316.28</td>\n",
-       "      <td>318.03</td>\n",
-       "      <td>316.71</td>\n",
-       "      <td>317.58</td>\n",
-       "      <td>316.28</td>\n",
+       "      <th>750</th>\n",
+       "      <td>2020</td>\n",
+       "      <td>7</td>\n",
+       "      <td>44027</td>\n",
+       "      <td>2020.5383</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>27</th>\n",
-       "      <td>1960</td>\n",
-       "      <td>4</td>\n",
-       "      <td>22021</td>\n",
-       "      <td>1960.2896</td>\n",
-       "      <td>319.03</td>\n",
-       "      <td>316.70</td>\n",
-       "      <td>319.14</td>\n",
-       "      <td>316.79</td>\n",
-       "      <td>319.03</td>\n",
-       "      <td>316.70</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>28</th>\n",
-       "      <td>1960</td>\n",
-       "      <td>5</td>\n",
-       "      <td>22051</td>\n",
-       "      <td>1960.3716</td>\n",
-       "      <td>320.04</td>\n",
-       "      <td>317.22</td>\n",
-       "      <td>319.67</td>\n",
-       "      <td>316.86</td>\n",
-       "      <td>320.04</td>\n",
-       "      <td>317.22</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>29</th>\n",
-       "      <td>1960</td>\n",
-       "      <td>6</td>\n",
-       "      <td>22082</td>\n",
-       "      <td>1960.4563</td>\n",
-       "      <td>319.59</td>\n",
-       "      <td>317.48</td>\n",
-       "      <td>319.01</td>\n",
-       "      <td>316.93</td>\n",
-       "      <td>319.59</td>\n",
-       "      <td>317.48</td>\n",
+       "      <th>751</th>\n",
+       "      <td>2020</td>\n",
+       "      <td>8</td>\n",
+       "      <td>44058</td>\n",
+       "      <td>2020.6230</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>752</th>\n",
+       "      <td>2020</td>\n",
+       "      <td>9</td>\n",
+       "      <td>44089</td>\n",
+       "      <td>2020.7077</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>753</th>\n",
+       "      <td>2020</td>\n",
+       "      <td>10</td>\n",
+       "      <td>44119</td>\n",
+       "      <td>2020.7896</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>754</th>\n",
+       "      <td>2020</td>\n",
+       "      <td>11</td>\n",
+       "      <td>44150</td>\n",
+       "      <td>2020.8743</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>755</th>\n",
+       "      <td>2020</td>\n",
+       "      <td>12</td>\n",
+       "      <td>44180</td>\n",
+       "      <td>2020.9563</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>30 rows × 10 columns</p>\n",
+       "<p>756 rows × 10 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "      Yr  Mn  Date 1     Date 2      s1      s2      s3      s4      s5  \\\n",
-       "0   1958   1   21200  1958.0411  -99.99  -99.99  -99.99  -99.99  -99.99   \n",
-       "1   1958   2   21231  1958.1260  -99.99  -99.99  -99.99  -99.99  -99.99   \n",
-       "2   1958   3   21259  1958.2027  315.70  314.44  316.19  314.91  315.70   \n",
-       "3   1958   4   21290  1958.2877  317.45  315.16  317.30  314.99  317.45   \n",
-       "4   1958   5   21320  1958.3699  317.51  314.71  317.86  315.06  317.51   \n",
-       "5   1958   6   21351  1958.4548  -99.99  -99.99  317.24  315.14  317.24   \n",
-       "6   1958   7   21381  1958.5370  315.86  315.19  315.86  315.22  315.86   \n",
-       "..   ...  ..     ...        ...     ...     ...     ...     ...     ...   \n",
-       "23  1959  12   21899  1959.9562  315.58  316.35  315.72  316.47  315.58   \n",
-       "24  1960   1   21930  1960.0410  316.43  316.39  316.61  316.56  316.43   \n",
-       "25  1960   2   21961  1960.1257  316.98  316.35  317.27  316.64  316.98   \n",
-       "26  1960   3   21990  1960.2049  317.58  316.28  318.03  316.71  317.58   \n",
-       "27  1960   4   22021  1960.2896  319.03  316.70  319.14  316.79  319.03   \n",
-       "28  1960   5   22051  1960.3716  320.04  317.22  319.67  316.86  320.04   \n",
-       "29  1960   6   22082  1960.4563  319.59  317.48  319.01  316.93  319.59   \n",
+       "       Yr  Mn  Date 1     Date 2      s1      s2      s3      s4      s5  \\\n",
+       "0    1958   1   21200  1958.0411  -99.99  -99.99  -99.99  -99.99  -99.99   \n",
+       "1    1958   2   21231  1958.1260  -99.99  -99.99  -99.99  -99.99  -99.99   \n",
+       "2    1958   3   21259  1958.2027  315.70  314.44  316.19  314.91  315.70   \n",
+       "3    1958   4   21290  1958.2877  317.45  315.16  317.30  314.99  317.45   \n",
+       "4    1958   5   21320  1958.3699  317.51  314.71  317.86  315.06  317.51   \n",
+       "5    1958   6   21351  1958.4548  -99.99  -99.99  317.24  315.14  317.24   \n",
+       "6    1958   7   21381  1958.5370  315.86  315.19  315.86  315.22  315.86   \n",
+       "..    ...  ..     ...        ...     ...     ...     ...     ...     ...   \n",
+       "749  2020   6   43997  2020.4563  -99.99  -99.99  -99.99  -99.99  -99.99   \n",
+       "750  2020   7   44027  2020.5383  -99.99  -99.99  -99.99  -99.99  -99.99   \n",
+       "751  2020   8   44058  2020.6230  -99.99  -99.99  -99.99  -99.99  -99.99   \n",
+       "752  2020   9   44089  2020.7077  -99.99  -99.99  -99.99  -99.99  -99.99   \n",
+       "753  2020  10   44119  2020.7896  -99.99  -99.99  -99.99  -99.99  -99.99   \n",
+       "754  2020  11   44150  2020.8743  -99.99  -99.99  -99.99  -99.99  -99.99   \n",
+       "755  2020  12   44180  2020.9563  -99.99  -99.99  -99.99  -99.99  -99.99   \n",
        "\n",
-       "        s6  \n",
-       "0   -99.99  \n",
-       "1   -99.99  \n",
-       "2   314.44  \n",
-       "3   315.16  \n",
-       "4   314.71  \n",
-       "5   315.14  \n",
-       "6   315.19  \n",
-       "..     ...  \n",
-       "23  316.35  \n",
-       "24  316.39  \n",
-       "25  316.35  \n",
-       "26  316.28  \n",
-       "27  316.70  \n",
-       "28  317.22  \n",
-       "29  317.48  \n",
+       "         s6  \n",
+       "0    -99.99  \n",
+       "1    -99.99  \n",
+       "2    314.44  \n",
+       "3    315.16  \n",
+       "4    314.71  \n",
+       "5    315.14  \n",
+       "6    315.19  \n",
+       "..      ...  \n",
+       "749  -99.99  \n",
+       "750  -99.99  \n",
+       "751  -99.99  \n",
+       "752  -99.99  \n",
+       "753  -99.99  \n",
+       "754  -99.99  \n",
+       "755  -99.99  \n",
        "\n",
-       "[30 rows x 10 columns]"
+       "[756 rows x 10 columns]"
       ]
      },
-     "execution_count": 169,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "raw_data_1.head(30)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Les données vide sont représentés par la valeur -99.99, nous remplaçons cette valeur par une valeur plus adéquate NaN dans une autre DataFrame"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 143,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "date = datetime.date.today()\n",
-    "data = raw_data_1.copy()\n",
-    "data = data.drop(data[(data.Yr == date.year) & (data.Mn > date.month)].index)\n",
-    "data = data.replace(-99.99,np.NaN);\n",
-    "d = data[(data.Yr == date.year)].index\n",
-    "i,k = d[0], d[-1]\n",
-    "\n",
-    "while k>=i:\n",
-    "    if data.loc[k].isnull().any():\n",
-    "        data = data.drop(k)\n",
-    "    else:\n",
-    "        break\n",
-    "    k = k - 1\n",
-    "    \n",
-    "annee, mois  = data.Yr[0], data.Mn[0]\n",
-    "d = data[(data.Yr == annee)].index\n",
-    "i,k = d[0], d[-1]\n",
-    "\n",
-    "while i<=k:\n",
-    "    if data.loc[i].isnull().any():\n",
-    "        data = data.drop(i)\n",
-    "    else:\n",
-    "        break\n",
-    "    i = i + 1\n",
-    "InteractiveShell.ast_node_interactivity = \"all\"     \n",
-    "data.head(3)\n",
-    "data.tail(3)\n",
-    "InteractiveShell.ast_node_interactivity = \"last_expr\"  "
+    "raw_data_1 = raw_data.copy()\n",
+    "print(raw_data.columns)\n",
+    "raw_data_1.columns = ['Yr','Mn','Date 1','Date 2','s1','s2','s3','s4','s5','s6']\n",
+    "raw_data_1"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "On visualise les lignes dont une donnée colonne est manquante."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 174,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Yr        False\n",
-       "Mn        False\n",
-       "Date 1    False\n",
-       "Date 2    False\n",
-       "s1         True\n",
-       "s2         True\n",
-       "s3        False\n",
-       "s4        False\n",
-       "s5        False\n",
-       "s6        False\n",
-       "dtype: bool"
-      ]
-     },
-     "execution_count": 174,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "#data[data.isnull().any(columns = 's1')]\n",
-    "data.isnull().any()"
+    "On supprime les lignes du début et de fin de la DataFrame qui n'ont pas de valeurs"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 145,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -839,6 +756,19 @@
        "      <td>315.86</td>\n",
        "      <td>315.19</td>\n",
        "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>1958</td>\n",
+       "      <td>8</td>\n",
+       "      <td>21412</td>\n",
+       "      <td>1958.6219</td>\n",
+       "      <td>314.93</td>\n",
+       "      <td>316.19</td>\n",
+       "      <td>314.00</td>\n",
+       "      <td>315.29</td>\n",
+       "      <td>314.93</td>\n",
+       "      <td>316.19</td>\n",
+       "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
@@ -849,29 +779,232 @@
        "3  1958   4   21290  1958.2877  317.45  315.16  317.30  314.99  317.45  315.16\n",
        "4  1958   5   21320  1958.3699  317.51  314.71  317.86  315.06  317.51  314.71\n",
        "5  1958   6   21351  1958.4548     NaN     NaN  317.24  315.14  317.24  315.14\n",
-       "6  1958   7   21381  1958.5370  315.86  315.19  315.86  315.22  315.86  315.19"
+       "6  1958   7   21381  1958.5370  315.86  315.19  315.86  315.22  315.86  315.19\n",
+       "7  1958   8   21412  1958.6219  314.93  316.19  314.00  315.29  314.93  316.19"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "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>Yr</th>\n",
+       "      <th>Mn</th>\n",
+       "      <th>Date 1</th>\n",
+       "      <th>Date 2</th>\n",
+       "      <th>s1</th>\n",
+       "      <th>s2</th>\n",
+       "      <th>s3</th>\n",
+       "      <th>s4</th>\n",
+       "      <th>s5</th>\n",
+       "      <th>s6</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>739</th>\n",
+       "      <td>2019</td>\n",
+       "      <td>8</td>\n",
+       "      <td>43692</td>\n",
+       "      <td>2019.6219</td>\n",
+       "      <td>410.08</td>\n",
+       "      <td>411.62</td>\n",
+       "      <td>410.23</td>\n",
+       "      <td>411.81</td>\n",
+       "      <td>410.08</td>\n",
+       "      <td>411.62</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>740</th>\n",
+       "      <td>2019</td>\n",
+       "      <td>9</td>\n",
+       "      <td>43723</td>\n",
+       "      <td>2019.7068</td>\n",
+       "      <td>408.55</td>\n",
+       "      <td>412.06</td>\n",
+       "      <td>408.52</td>\n",
+       "      <td>412.05</td>\n",
+       "      <td>408.55</td>\n",
+       "      <td>412.06</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>741</th>\n",
+       "      <td>2019</td>\n",
+       "      <td>10</td>\n",
+       "      <td>43753</td>\n",
+       "      <td>2019.7890</td>\n",
+       "      <td>408.43</td>\n",
+       "      <td>412.07</td>\n",
+       "      <td>408.67</td>\n",
+       "      <td>412.29</td>\n",
+       "      <td>408.43</td>\n",
+       "      <td>412.07</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>742</th>\n",
+       "      <td>2019</td>\n",
+       "      <td>11</td>\n",
+       "      <td>43784</td>\n",
+       "      <td>2019.8740</td>\n",
+       "      <td>410.28</td>\n",
+       "      <td>412.56</td>\n",
+       "      <td>410.29</td>\n",
+       "      <td>412.54</td>\n",
+       "      <td>410.28</td>\n",
+       "      <td>412.56</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>743</th>\n",
+       "      <td>2019</td>\n",
+       "      <td>12</td>\n",
+       "      <td>43814</td>\n",
+       "      <td>2019.9562</td>\n",
+       "      <td>411.85</td>\n",
+       "      <td>412.78</td>\n",
+       "      <td>411.88</td>\n",
+       "      <td>412.79</td>\n",
+       "      <td>411.85</td>\n",
+       "      <td>412.78</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>744</th>\n",
+       "      <td>2020</td>\n",
+       "      <td>1</td>\n",
+       "      <td>43845</td>\n",
+       "      <td>2020.0410</td>\n",
+       "      <td>413.37</td>\n",
+       "      <td>413.33</td>\n",
+       "      <td>413.11</td>\n",
+       "      <td>413.05</td>\n",
+       "      <td>413.37</td>\n",
+       "      <td>413.33</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Yr  Mn  Date 1     Date 2      s1      s2      s3      s4      s5  \\\n",
+       "739  2019   8   43692  2019.6219  410.08  411.62  410.23  411.81  410.08   \n",
+       "740  2019   9   43723  2019.7068  408.55  412.06  408.52  412.05  408.55   \n",
+       "741  2019  10   43753  2019.7890  408.43  412.07  408.67  412.29  408.43   \n",
+       "742  2019  11   43784  2019.8740  410.28  412.56  410.29  412.54  410.28   \n",
+       "743  2019  12   43814  2019.9562  411.85  412.78  411.88  412.79  411.85   \n",
+       "744  2020   1   43845  2020.0410  413.37  413.33  413.11  413.05  413.37   \n",
+       "\n",
+       "         s6  \n",
+       "739  411.62  \n",
+       "740  412.06  \n",
+       "741  412.07  \n",
+       "742  412.56  \n",
+       "743  412.78  \n",
+       "744  413.33  "
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data = raw_data_1.copy()\n",
+    "date = datetime.date.today()\n",
+    "\n",
+    "data = data.drop(data[(data.Yr == date.year) & (data.Mn > date.month)].index)\n",
+    "data = data.replace(-99.99,np.NaN);\n",
+    "d = data[(data.Yr == date.year)].index\n",
+    "i,k = d[0], d[-1]\n",
+    "\n",
+    "while k>=i:\n",
+    "    if data.loc[k].isnull().any():\n",
+    "        data = data.drop(k)\n",
+    "    else:\n",
+    "        break\n",
+    "    k = k - 1\n",
+    "    \n",
+    "annee, mois  = data.Yr[0], data.Mn[0]\n",
+    "d = data[(data.Yr == annee)].index\n",
+    "i,k = d[0], d[-1]\n",
+    "\n",
+    "while i<=k:\n",
+    "    if data.loc[i].isnull().any():\n",
+    "        data = data.drop(i)\n",
+    "    else:\n",
+    "        break\n",
+    "    i = i + 1\n",
+    "InteractiveShell.ast_node_interactivity = \"all\"     \n",
+    "data.head(6)\n",
+    "data.tail(6)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "On visualise les colonnes dont au moins une donnée est manquante."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Yr        False\n",
+       "Mn        False\n",
+       "Date 1    False\n",
+       "Date 2    False\n",
+       "s1         True\n",
+       "s2         True\n",
+       "s3        False\n",
+       "s4        False\n",
+       "s5        False\n",
+       "s6        False\n",
+       "dtype: bool"
       ]
      },
-     "execution_count": 145,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "data.head()"
+    "#data[data.isnull().any(columns = 's1')]\n",
+    "data.isnull().any()"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "On ajoute un index 'périod' à la DataFrame, cet index représente la période de mesure. \n",
-    "Cette date est mise dans au format compréhensible par pandas. On visualise toutes les lignes qui seront supprimées."
+    "La colonne s5 represente la concentration en CO2, aucune de ces données sont manquantes. On ajoute un index 'périod' à la DataFrame, cet index représente la période de mesure. Cette date est mise dans au format compréhensible par pandas. On visualise toutes les lignes qui seront supprimées."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 146,
+   "execution_count": 13,
    "metadata": {
     "scrolled": true
    },
@@ -968,6 +1101,20 @@
        "      <td>314.71</td>\n",
        "    </tr>\n",
        "    <tr>\n",
+       "      <th>1958-06-01</th>\n",
+       "      <td>5</td>\n",
+       "      <td>1958</td>\n",
+       "      <td>6</td>\n",
+       "      <td>21351</td>\n",
+       "      <td>1958.4548</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>317.24</td>\n",
+       "      <td>315.14</td>\n",
+       "      <td>317.24</td>\n",
+       "      <td>315.14</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>1958-07-01</th>\n",
        "      <td>6</td>\n",
        "      <td>1958</td>\n",
@@ -981,160 +1128,6 @@
        "      <td>315.86</td>\n",
        "      <td>315.19</td>\n",
        "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1958-08-01</th>\n",
-       "      <td>7</td>\n",
-       "      <td>1958</td>\n",
-       "      <td>8</td>\n",
-       "      <td>21412</td>\n",
-       "      <td>1958.6219</td>\n",
-       "      <td>314.93</td>\n",
-       "      <td>316.19</td>\n",
-       "      <td>314.00</td>\n",
-       "      <td>315.29</td>\n",
-       "      <td>314.93</td>\n",
-       "      <td>316.19</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1958-09-01</th>\n",
-       "      <td>8</td>\n",
-       "      <td>1958</td>\n",
-       "      <td>9</td>\n",
-       "      <td>21443</td>\n",
-       "      <td>1958.7068</td>\n",
-       "      <td>313.21</td>\n",
-       "      <td>316.08</td>\n",
-       "      <td>312.46</td>\n",
-       "      <td>315.35</td>\n",
-       "      <td>313.21</td>\n",
-       "      <td>316.08</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1958-11-01</th>\n",
-       "      <td>10</td>\n",
-       "      <td>1958</td>\n",
-       "      <td>11</td>\n",
-       "      <td>21504</td>\n",
-       "      <td>1958.8740</td>\n",
-       "      <td>313.33</td>\n",
-       "      <td>315.20</td>\n",
-       "      <td>313.62</td>\n",
-       "      <td>315.46</td>\n",
-       "      <td>313.33</td>\n",
-       "      <td>315.20</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1958-12-01</th>\n",
-       "      <td>11</td>\n",
-       "      <td>1958</td>\n",
-       "      <td>12</td>\n",
-       "      <td>21534</td>\n",
-       "      <td>1958.9562</td>\n",
-       "      <td>314.67</td>\n",
-       "      <td>315.43</td>\n",
-       "      <td>314.77</td>\n",
-       "      <td>315.51</td>\n",
-       "      <td>314.67</td>\n",
-       "      <td>315.43</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1959-01-01</th>\n",
-       "      <td>12</td>\n",
-       "      <td>1959</td>\n",
-       "      <td>1</td>\n",
-       "      <td>21565</td>\n",
-       "      <td>1959.0411</td>\n",
-       "      <td>315.58</td>\n",
-       "      <td>315.54</td>\n",
-       "      <td>315.62</td>\n",
-       "      <td>315.57</td>\n",
-       "      <td>315.58</td>\n",
-       "      <td>315.54</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1959-02-01</th>\n",
-       "      <td>13</td>\n",
-       "      <td>1959</td>\n",
-       "      <td>2</td>\n",
-       "      <td>21596</td>\n",
-       "      <td>1959.1260</td>\n",
-       "      <td>316.49</td>\n",
-       "      <td>315.86</td>\n",
-       "      <td>316.27</td>\n",
-       "      <td>315.63</td>\n",
-       "      <td>316.49</td>\n",
-       "      <td>315.86</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1959-03-01</th>\n",
-       "      <td>14</td>\n",
-       "      <td>1959</td>\n",
-       "      <td>3</td>\n",
-       "      <td>21624</td>\n",
-       "      <td>1959.2027</td>\n",
-       "      <td>316.65</td>\n",
-       "      <td>315.38</td>\n",
-       "      <td>316.98</td>\n",
-       "      <td>315.69</td>\n",
-       "      <td>316.65</td>\n",
-       "      <td>315.38</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1959-04-01</th>\n",
-       "      <td>15</td>\n",
-       "      <td>1959</td>\n",
-       "      <td>4</td>\n",
-       "      <td>21655</td>\n",
-       "      <td>1959.2877</td>\n",
-       "      <td>317.72</td>\n",
-       "      <td>315.42</td>\n",
-       "      <td>318.09</td>\n",
-       "      <td>315.77</td>\n",
-       "      <td>317.72</td>\n",
-       "      <td>315.42</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1959-05-01</th>\n",
-       "      <td>16</td>\n",
-       "      <td>1959</td>\n",
-       "      <td>5</td>\n",
-       "      <td>21685</td>\n",
-       "      <td>1959.3699</td>\n",
-       "      <td>318.29</td>\n",
-       "      <td>315.49</td>\n",
-       "      <td>318.65</td>\n",
-       "      <td>315.85</td>\n",
-       "      <td>318.29</td>\n",
-       "      <td>315.49</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1959-06-01</th>\n",
-       "      <td>17</td>\n",
-       "      <td>1959</td>\n",
-       "      <td>6</td>\n",
-       "      <td>21716</td>\n",
-       "      <td>1959.4548</td>\n",
-       "      <td>318.15</td>\n",
-       "      <td>316.03</td>\n",
-       "      <td>318.04</td>\n",
-       "      <td>315.94</td>\n",
-       "      <td>318.15</td>\n",
-       "      <td>316.03</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1959-07-01</th>\n",
-       "      <td>18</td>\n",
-       "      <td>1959</td>\n",
-       "      <td>7</td>\n",
-       "      <td>21746</td>\n",
-       "      <td>1959.5370</td>\n",
-       "      <td>316.54</td>\n",
-       "      <td>315.86</td>\n",
-       "      <td>316.67</td>\n",
-       "      <td>316.03</td>\n",
-       "      <td>316.54</td>\n",
-       "      <td>315.86</td>\n",
-       "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
@@ -1145,53 +1138,31 @@
        "1958-03-01      2  1958   3   21259  1958.2027  315.70  314.44  316.19   \n",
        "1958-04-01      3  1958   4   21290  1958.2877  317.45  315.16  317.30   \n",
        "1958-05-01      4  1958   5   21320  1958.3699  317.51  314.71  317.86   \n",
+       "1958-06-01      5  1958   6   21351  1958.4548     NaN     NaN  317.24   \n",
        "1958-07-01      6  1958   7   21381  1958.5370  315.86  315.19  315.86   \n",
-       "1958-08-01      7  1958   8   21412  1958.6219  314.93  316.19  314.00   \n",
-       "1958-09-01      8  1958   9   21443  1958.7068  313.21  316.08  312.46   \n",
-       "1958-11-01     10  1958  11   21504  1958.8740  313.33  315.20  313.62   \n",
-       "1958-12-01     11  1958  12   21534  1958.9562  314.67  315.43  314.77   \n",
-       "1959-01-01     12  1959   1   21565  1959.0411  315.58  315.54  315.62   \n",
-       "1959-02-01     13  1959   2   21596  1959.1260  316.49  315.86  316.27   \n",
-       "1959-03-01     14  1959   3   21624  1959.2027  316.65  315.38  316.98   \n",
-       "1959-04-01     15  1959   4   21655  1959.2877  317.72  315.42  318.09   \n",
-       "1959-05-01     16  1959   5   21685  1959.3699  318.29  315.49  318.65   \n",
-       "1959-06-01     17  1959   6   21716  1959.4548  318.15  316.03  318.04   \n",
-       "1959-07-01     18  1959   7   21746  1959.5370  316.54  315.86  316.67   \n",
        "\n",
        "                s4      s5      s6  \n",
        "period                              \n",
        "1958-03-01  314.91  315.70  314.44  \n",
        "1958-04-01  314.99  317.45  315.16  \n",
        "1958-05-01  315.06  317.51  314.71  \n",
-       "1958-07-01  315.22  315.86  315.19  \n",
-       "1958-08-01  315.29  314.93  316.19  \n",
-       "1958-09-01  315.35  313.21  316.08  \n",
-       "1958-11-01  315.46  313.33  315.20  \n",
-       "1958-12-01  315.51  314.67  315.43  \n",
-       "1959-01-01  315.57  315.58  315.54  \n",
-       "1959-02-01  315.63  316.49  315.86  \n",
-       "1959-03-01  315.69  316.65  315.38  \n",
-       "1959-04-01  315.77  317.72  315.42  \n",
-       "1959-05-01  315.85  318.29  315.49  \n",
-       "1959-06-01  315.94  318.15  316.03  \n",
-       "1959-07-01  316.03  316.54  315.86  "
+       "1958-06-01  315.14  317.24  315.14  \n",
+       "1958-07-01  315.22  315.86  315.19  "
       ]
      },
-     "execution_count": 146,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "df = data.dropna().copy()\n",
+    "df = data.copy()                                 # data.dropna().copy()\n",
     "df = df.reset_index().copy()\n",
-    "#print(data.shape)\n",
     "period = [datetime.date(y,m,1) for y,m in zip(df['Yr'],df['Mn'])]\n",
     "period = pd.Series(period,name = 'period')\n",
-    "#print(period.shape)\n",
     "df = pd.concat([df,period],axis=1)\n",
     "df = df.set_index('period') \n",
-    "df[0:15]"
+    "df.head()"
    ]
   },
   {
@@ -1203,12 +1174,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 147,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 1080x720 with 1 Axes>"
       ]
@@ -1220,8 +1191,8 @@
     }
    ],
    "source": [
-    "df['s1'].plot(title = 'concentration de CO2',);\n",
-    "df['s1'].plot(figsize=(15, 10),).grid(linestyle='--', linewidth=1);"
+    "df['s5'].plot(title = 'Concentration de CO2',);\n",
+    "df['s5'].plot(figsize=(15, 10),).grid(linestyle='--', linewidth=1);"
    ]
   },
   {
-- 
2.18.1