Use pd.cut() for income_cat

02_end_to_end_machine_learning_project.ipynb

@@ -338,10 +338,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Divide by 1.5 to limit the number of income categories\n",
-    "housing[\"income_cat\"] = np.ceil(housing[\"median_income\"] / 1.5)\n",
-    "# Label those above 5 as 5\n",
-    "housing[\"income_cat\"].where(housing[\"income_cat\"] < 5, 5.0, inplace=True)"
+    "housing[\"income_cat\"] = pd.cut(housing[\"median_income\"],\n",
+    "                               bins=[0., 1.5, 3.0, 4.5, 6., np.inf],\n",
+    "                               labels=[1, 2, 3, 4, 5])"
    ]
   },
   {