task finished

module3/exo1/influenza-like-illness-analysis.ipynb

@@ -9,10 +9,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 9,
+   "metadata": {},
    "outputs": [],
    "source": [
     "%matplotlib inline\n",
@@ -28,15 +26,29 @@
     "The data on the incidence of influenza-like illness are available from the Web site of the [Réseau Sentinelles](http://www.sentiweb.fr/). We download them as a file in CSV format, in which each line corresponds to a week in the observation period. Only the complete dataset, starting in 1984 and ending with a recent week, is available for download."
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "I modified this computational document such that it uses a local copy of the data. If the local file does not exist, download the data and put them into the local file. And then read the local CSV file."
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 13,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\""
+    "import os\n",
+    "import urllib.request\n",
+    "\n",
+    "local_file_for_this_task = \"local_data.csv\"\n",
+    "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\"\n",
+    "\n",
+    "if not os.path.exists(local_file_for_this_task):\n",
+    "    urllib.request.urlretrieve(data_url, local_file_for_this_task)\n",
+    "else:\n",
+    "    pass"
    ]
   },
   {
@@ -63,11 +75,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'pd' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-4-7c69161e8105>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mraw_data\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlocal_file_for_this_task\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mskiprows\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mraw_data\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mNameError\u001b[0m: name 'pd' is not defined"
+     ]
+    }
+   ],
    "source": [
-    "raw_data = pd.read_csv(data_url, skiprows=1)\n",
+    "raw_data = pd.read_csv(local_file_for_this_task, skiprows=1)\n",
     "raw_data"
    ]
   },
@@ -365,7 +389,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.1"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,