M294 Fix

Mission294Solutions.ipynb

@@ -680,7 +680,7 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>top</th>\n",
-       "      <td>2016-03-09 11:54:38</td>\n",
+       "      <td>2016-03-08 10:40:35</td>\n",
        "      <td>Ford_Fiesta</td>\n",
        "      <td>privat</td>\n",
        "      <td>Angebot</td>\n",
@@ -893,7 +893,7 @@
        "               date_crawled         name  seller offer_type  price ab_test  \\\n",
        "count                 50000        50000   50000      50000  50000   50000   \n",
        "unique                48213        38754       2          2   2357       2   \n",
-       "top     2016-03-09 11:54:38  Ford_Fiesta  privat    Angebot     $0    test   \n",
+       "top     2016-03-08 10:40:35  Ford_Fiesta  privat    Angebot     $0    test   \n",
        "freq                      3           78   49999      49999   1421   25756   \n",
        "mean                    NaN          NaN     NaN        NaN    NaN     NaN   \n",
        "std                     NaN          NaN     NaN        NaN    NaN     NaN   \n",
@@ -1328,7 +1328,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
@@ -1401,7 +1401,7 @@
        "4  2016-04-01 14:38:50  2016-04-01 00:00:00  2016-04-01 14:38:50"
       ]
      },
-     "execution_count": 28,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1412,7 +1412,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -1455,7 +1455,7 @@
        "Name: date_crawled, dtype: float64"
       ]
      },
-     "execution_count": 30,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1470,7 +1470,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
@@ -1513,7 +1513,7 @@
        "Name: date_crawled, dtype: float64"
       ]
      },
-     "execution_count": 29,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1535,7 +1535,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 150,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -1578,7 +1578,7 @@
        "Name: last_seen, dtype: float64"
       ]
      },
-     "execution_count": 150,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1602,7 +1602,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -1679,7 +1679,7 @@
        "Name: ad_created, Length: 76, dtype: float64"
       ]
      },
-     "execution_count": 33,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1702,7 +1702,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
@@ -1719,7 +1719,7 @@
        "Name: registration_year, dtype: float64"
       ]
      },
-     "execution_count": 34,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1753,16 +1753,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "0.038793369710697002"
+       "0.038793369710697"
       ]
      },
-     "execution_count": 35,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1780,7 +1780,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
@@ -1799,7 +1799,7 @@
        "Name: registration_year, dtype: float64"
       ]
      },
-     "execution_count": 47,
+     "execution_count": 22,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1827,7 +1827,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
@@ -1876,7 +1876,7 @@
        "Name: brand, dtype: float64"
       ]
      },
-     "execution_count": 48,
+     "execution_count": 23,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1896,7 +1896,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
@@ -1915,7 +1915,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [
     {
@@ -1929,7 +1929,7 @@
        " 'volkswagen': 5402}"
       ]
      },
-     "execution_count": 39,
+     "execution_count": 33,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1965,7 +1965,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [
     {
@@ -1989,7 +1989,7 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>mean_mileage</th>\n",
+       "      <th>mean_price</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
@@ -2022,23 +2022,23 @@
        "</div>"
       ],
       "text/plain": [
-       "               mean_mileage\n",
-       "audi                   9336\n",
-       "bmw                    8332\n",
-       "ford                   3749\n",
-       "mercedes_benz          8628\n",
-       "opel                   2975\n",
-       "volkswagen             5402"
+       "               mean_price\n",
+       "audi                 9336\n",
+       "bmw                  8332\n",
+       "ford                 3749\n",
+       "mercedes_benz        8628\n",
+       "opel                 2975\n",
+       "volkswagen           5402"
       ]
      },
-     "execution_count": 66,
+     "execution_count": 37,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "bmp_series = pd.Series(brand_mean_prices)\n",
-    "pd.DataFrame(bmp_series, columns=[\"mean_mileage\"])"
+    "pd.DataFrame(bmp_series, columns=[\"mean_price\"])"
    ]
   },
   {
@@ -2245,7 +2245,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.6.7"
   }
  },
  "nbformat": 4,

Mission348Solutions.ipynb

@@ -2309,8 +2309,7 @@
     "mapping = {'Record ID': 'id', 'CESSATION YEAR': 'cease_date', 'Reason for ceasing employment': 'separationtype', 'Gender. What is your Gender?': 'gender', 'CurrentAge. Current Age': 'age',\n",
     "       'Employment Type. Employment Type': 'employment_status',\n",
     "       'Classification. Classification': 'position',\n",
-    "       'LengthofServiceOverall. Overall Length of Service at Institute (in years)': 'institute_service',\n",
-    "       'LengthofServiceCurrent. Length of Service at current workplace (in years)': 'role_service'}\n",
+    "       'LengthofServiceOverall. Overall Length of Service at Institute (in years)': 'institute_service'}\n",
     "tafe_survey_updated = tafe_survey_updated.rename(mapping, axis = 1)\n",
     "\n",
     "# Check that the specified column names were updated correctly\n",