chore: cleanup

SL/aufgaben/workshop2/notebooks/ws2_feature_engineering.ipynb

@@ -1891,7 +1891,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 37,
    "id": "864d7618",
    "metadata": {
     "scrolled": true
@@ -1908,6 +1908,27 @@
       "YearBuilt > 2018               0\n",
       "Koordinaten ausserhalb Melbourne: 0\n"
      ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "BuildingArea\n",
+       "120.0    119\n",
+       "100.0     96\n",
+       "110.0     96\n",
+       "130.0     90\n",
+       "115.0     87\n",
+       "150.0     82\n",
+       "112.0     74\n",
+       "140.0     72\n",
+       "90.0      72\n",
+       "104.0     70\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -1929,7 +1950,11 @@
     "df[['Lattitude', 'Longtitude']].describe()\n",
     "weird = df[(df['Lattitude'] > -37) | (df['Lattitude'] < -39) |\n",
     "           (df['Longtitude'] < 144) | (df['Longtitude'] > 146)]\n",
-    "print(f'Koordinaten ausserhalb Melbourne: {len(weird)}')"
+    "print(f'Koordinaten ausserhalb Melbourne: {len(weird)}')\n",
+    "\n",
+    "# spikes\n",
+    "df['Landsize'].value_counts().head(10)\n",
+    "df['BuildingArea'].value_counts().head(10)"
    ]
   },
   {