Voir les lignes avec des données manquantes

module3/exo3/exercice.ipynb

@@ -9,18 +9,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
     "import pandas as pd\n",
     "import numpy as np\n",
-    "import matplotlib.pyplot as plt"
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -483,14 +484,90 @@
        "52          53  1821   54.0    NaN"
       ]
      },
-     "execution_count": 2,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "df = pd.read_csv('https://raw.githubusercontent.com/vincentarelbundock/Rdatasets/master/csv/HistData/Wheat.csv')\n",
-    "df"
+    "data = pd.read_csv('https://raw.githubusercontent.com/vincentarelbundock/Rdatasets/master/csv/HistData/Wheat.csv')\n",
+    "data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "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>Unnamed: 0</th>\n",
+       "      <th>Year</th>\n",
+       "      <th>Wheat</th>\n",
+       "      <th>Wages</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>51</td>\n",
+       "      <td>1815</td>\n",
+       "      <td>78.0</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>51</th>\n",
+       "      <td>52</td>\n",
+       "      <td>1820</td>\n",
+       "      <td>54.0</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>52</th>\n",
+       "      <td>53</td>\n",
+       "      <td>1821</td>\n",
+       "      <td>54.0</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    Unnamed: 0  Year  Wheat  Wages\n",
+       "50          51  1815   78.0    NaN\n",
+       "51          52  1820   54.0    NaN\n",
+       "52          53  1821   54.0    NaN"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Voir les lignes avec des données manquantes\n",
+    "\n",
+    "data[data.isnull().any(axis = 1)]"
    ]
   },
   {