From d7f6780a9deb705ff3fe14a537b2d2f8f8b9e002 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Luis=20Fern=C3=A1ndez=20Garc=C3=ADa?=
 <luisfgarcia97@gmail.com>
Date: Thu, 6 Nov 2025 17:29:31 +0100
Subject: [PATCH] lab solved

---
 lab-hypothesis-testing.ipynb | 2181 +++++++++++++++++++++++++++++++++-
 1 file changed, 2166 insertions(+), 15 deletions(-)

diff --git a/lab-hypothesis-testing.ipynb b/lab-hypothesis-testing.ipynb
index 0cc26d5..fbadbd5 100644
--- a/lab-hypothesis-testing.ipynb
+++ b/lab-hypothesis-testing.ipynb
@@ -51,11 +51,782 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
      "data": {
+      "application/vnd.microsoft.datawrangler.viewer.v0+json": {
+       "columns": [
+        {
+         "name": "index",
+         "rawType": "int64",
+         "type": "integer"
+        },
+        {
+         "name": "Name",
+         "rawType": "object",
+         "type": "unknown"
+        },
+        {
+         "name": "Type 1",
+         "rawType": "object",
+         "type": "string"
+        },
+        {
+         "name": "Type 2",
+         "rawType": "object",
+         "type": "unknown"
+        },
+        {
+         "name": "HP",
+         "rawType": "int64",
+         "type": "integer"
+        },
+        {
+         "name": "Attack",
+         "rawType": "int64",
+         "type": "integer"
+        },
+        {
+         "name": "Defense",
+         "rawType": "int64",
+         "type": "integer"
+        },
+        {
+         "name": "Sp. Atk",
+         "rawType": "int64",
+         "type": "integer"
+        },
+        {
+         "name": "Sp. Def",
+         "rawType": "int64",
+         "type": "integer"
+        },
+        {
+         "name": "Speed",
+         "rawType": "int64",
+         "type": "integer"
+        },
+        {
+         "name": "Generation",
+         "rawType": "int64",
+         "type": "integer"
+        },
+        {
+         "name": "Legendary",
+         "rawType": "bool",
+         "type": "boolean"
+        }
+       ],
+       "ref": "5b3a692d-85ba-46de-a9c4-115d6a60d8fc",
+       "rows": [
+        [
+         "0",
+         "Bulbasaur",
+         "Grass",
+         "Poison",
+         "45",
+         "49",
+         "49",
+         "65",
+         "65",
+         "45",
+         "1",
+         "False"
+        ],
+        [
+         "1",
+         "Ivysaur",
+         "Grass",
+         "Poison",
+         "60",
+         "62",
+         "63",
+         "80",
+         "80",
+         "60",
+         "1",
+         "False"
+        ],
+        [
+         "2",
+         "Venusaur",
+         "Grass",
+         "Poison",
+         "80",
+         "82",
+         "83",
+         "100",
+         "100",
+         "80",
+         "1",
+         "False"
+        ],
+        [
+         "3",
+         "Mega Venusaur",
+         "Grass",
+         "Poison",
+         "80",
+         "100",
+         "123",
+         "122",
+         "120",
+         "80",
+         "1",
+         "False"
+        ],
+        [
+         "4",
+         "Charmander",
+         "Fire",
+         null,
+         "39",
+         "52",
+         "43",
+         "60",
+         "50",
+         "65",
+         "1",
+         "False"
+        ],
+        [
+         "5",
+         "Charmeleon",
+         "Fire",
+         null,
+         "58",
+         "64",
+         "58",
+         "80",
+         "65",
+         "80",
+         "1",
+         "False"
+        ],
+        [
+         "6",
+         "Charizard",
+         "Fire",
+         "Flying",
+         "78",
+         "84",
+         "78",
+         "109",
+         "85",
+         "100",
+         "1",
+         "False"
+        ],
+        [
+         "7",
+         "Mega Charizard X",
+         "Fire",
+         "Dragon",
+         "78",
+         "130",
+         "111",
+         "130",
+         "85",
+         "100",
+         "1",
+         "False"
+        ],
+        [
+         "8",
+         "Mega Charizard Y",
+         "Fire",
+         "Flying",
+         "78",
+         "104",
+         "78",
+         "159",
+         "115",
+         "100",
+         "1",
+         "False"
+        ],
+        [
+         "9",
+         "Squirtle",
+         "Water",
+         null,
+         "44",
+         "48",
+         "65",
+         "50",
+         "64",
+         "43",
+         "1",
+         "False"
+        ],
+        [
+         "10",
+         "Wartortle",
+         "Water",
+         null,
+         "59",
+         "63",
+         "80",
+         "65",
+         "80",
+         "58",
+         "1",
+         "False"
+        ],
+        [
+         "11",
+         "Blastoise",
+         "Water",
+         null,
+         "79",
+         "83",
+         "100",
+         "85",
+         "105",
+         "78",
+         "1",
+         "False"
+        ],
+        [
+         "12",
+         "Mega Blastoise",
+         "Water",
+         null,
+         "79",
+         "103",
+         "120",
+         "135",
+         "115",
+         "78",
+         "1",
+         "False"
+        ],
+        [
+         "13",
+         "Caterpie",
+         "Bug",
+         null,
+         "45",
+         "30",
+         "35",
+         "20",
+         "20",
+         "45",
+         "1",
+         "False"
+        ],
+        [
+         "14",
+         "Metapod",
+         "Bug",
+         null,
+         "50",
+         "20",
+         "55",
+         "25",
+         "25",
+         "30",
+         "1",
+         "False"
+        ],
+        [
+         "15",
+         "Butterfree",
+         "Bug",
+         "Flying",
+         "60",
+         "45",
+         "50",
+         "90",
+         "80",
+         "70",
+         "1",
+         "False"
+        ],
+        [
+         "16",
+         "Weedle",
+         "Bug",
+         "Poison",
+         "40",
+         "35",
+         "30",
+         "20",
+         "20",
+         "50",
+         "1",
+         "False"
+        ],
+        [
+         "17",
+         "Kakuna",
+         "Bug",
+         "Poison",
+         "45",
+         "25",
+         "50",
+         "25",
+         "25",
+         "35",
+         "1",
+         "False"
+        ],
+        [
+         "18",
+         "Beedrill",
+         "Bug",
+         "Poison",
+         "65",
+         "90",
+         "40",
+         "45",
+         "80",
+         "75",
+         "1",
+         "False"
+        ],
+        [
+         "19",
+         "Mega Beedrill",
+         "Bug",
+         "Poison",
+         "65",
+         "150",
+         "40",
+         "15",
+         "80",
+         "145",
+         "1",
+         "False"
+        ],
+        [
+         "20",
+         "Pidgey",
+         "Normal",
+         "Flying",
+         "40",
+         "45",
+         "40",
+         "35",
+         "35",
+         "56",
+         "1",
+         "False"
+        ],
+        [
+         "21",
+         "Pidgeotto",
+         "Normal",
+         "Flying",
+         "63",
+         "60",
+         "55",
+         "50",
+         "50",
+         "71",
+         "1",
+         "False"
+        ],
+        [
+         "22",
+         "Pidgeot",
+         "Normal",
+         "Flying",
+         "83",
+         "80",
+         "75",
+         "70",
+         "70",
+         "101",
+         "1",
+         "False"
+        ],
+        [
+         "23",
+         "Mega Pidgeot",
+         "Normal",
+         "Flying",
+         "83",
+         "80",
+         "80",
+         "135",
+         "80",
+         "121",
+         "1",
+         "False"
+        ],
+        [
+         "24",
+         "Rattata",
+         "Normal",
+         null,
+         "30",
+         "56",
+         "35",
+         "25",
+         "35",
+         "72",
+         "1",
+         "False"
+        ],
+        [
+         "25",
+         "Raticate",
+         "Normal",
+         null,
+         "55",
+         "81",
+         "60",
+         "50",
+         "70",
+         "97",
+         "1",
+         "False"
+        ],
+        [
+         "26",
+         "Spearow",
+         "Normal",
+         "Flying",
+         "40",
+         "60",
+         "30",
+         "31",
+         "31",
+         "70",
+         "1",
+         "False"
+        ],
+        [
+         "27",
+         "Fearow",
+         "Normal",
+         "Flying",
+         "65",
+         "90",
+         "65",
+         "61",
+         "61",
+         "100",
+         "1",
+         "False"
+        ],
+        [
+         "28",
+         "Ekans",
+         "Poison",
+         null,
+         "35",
+         "60",
+         "44",
+         "40",
+         "54",
+         "55",
+         "1",
+         "False"
+        ],
+        [
+         "29",
+         "Arbok",
+         "Poison",
+         null,
+         "60",
+         "85",
+         "69",
+         "65",
+         "79",
+         "80",
+         "1",
+         "False"
+        ],
+        [
+         "30",
+         "Pikachu",
+         "Electric",
+         null,
+         "35",
+         "55",
+         "40",
+         "50",
+         "50",
+         "90",
+         "1",
+         "False"
+        ],
+        [
+         "31",
+         "Raichu",
+         "Electric",
+         null,
+         "60",
+         "90",
+         "55",
+         "90",
+         "80",
+         "110",
+         "1",
+         "False"
+        ],
+        [
+         "32",
+         "Sandshrew",
+         "Ground",
+         null,
+         "50",
+         "75",
+         "85",
+         "20",
+         "30",
+         "40",
+         "1",
+         "False"
+        ],
+        [
+         "33",
+         "Sandslash",
+         "Ground",
+         null,
+         "75",
+         "100",
+         "110",
+         "45",
+         "55",
+         "65",
+         "1",
+         "False"
+        ],
+        [
+         "34",
+         "Nidoran♀",
+         "Poison",
+         null,
+         "55",
+         "47",
+         "52",
+         "40",
+         "40",
+         "41",
+         "1",
+         "False"
+        ],
+        [
+         "35",
+         "Nidorina",
+         "Poison",
+         null,
+         "70",
+         "62",
+         "67",
+         "55",
+         "55",
+         "56",
+         "1",
+         "False"
+        ],
+        [
+         "36",
+         "Nidoqueen",
+         "Poison",
+         "Ground",
+         "90",
+         "92",
+         "87",
+         "75",
+         "85",
+         "76",
+         "1",
+         "False"
+        ],
+        [
+         "37",
+         "Nidoran♂",
+         "Poison",
+         null,
+         "46",
+         "57",
+         "40",
+         "40",
+         "40",
+         "50",
+         "1",
+         "False"
+        ],
+        [
+         "38",
+         "Nidorino",
+         "Poison",
+         null,
+         "61",
+         "72",
+         "57",
+         "55",
+         "55",
+         "65",
+         "1",
+         "False"
+        ],
+        [
+         "39",
+         "Nidoking",
+         "Poison",
+         "Ground",
+         "81",
+         "102",
+         "77",
+         "85",
+         "75",
+         "85",
+         "1",
+         "False"
+        ],
+        [
+         "40",
+         "Clefairy",
+         "Fairy",
+         null,
+         "70",
+         "45",
+         "48",
+         "60",
+         "65",
+         "35",
+         "1",
+         "False"
+        ],
+        [
+         "41",
+         "Clefable",
+         "Fairy",
+         null,
+         "95",
+         "70",
+         "73",
+         "95",
+         "90",
+         "60",
+         "1",
+         "False"
+        ],
+        [
+         "42",
+         "Vulpix",
+         "Fire",
+         null,
+         "38",
+         "41",
+         "40",
+         "50",
+         "65",
+         "65",
+         "1",
+         "False"
+        ],
+        [
+         "43",
+         "Ninetales",
+         "Fire",
+         null,
+         "73",
+         "76",
+         "75",
+         "81",
+         "100",
+         "100",
+         "1",
+         "False"
+        ],
+        [
+         "44",
+         "Jigglypuff",
+         "Normal",
+         "Fairy",
+         "115",
+         "45",
+         "20",
+         "45",
+         "25",
+         "20",
+         "1",
+         "False"
+        ],
+        [
+         "45",
+         "Wigglytuff",
+         "Normal",
+         "Fairy",
+         "140",
+         "70",
+         "45",
+         "85",
+         "50",
+         "45",
+         "1",
+         "False"
+        ],
+        [
+         "46",
+         "Zubat",
+         "Poison",
+         "Flying",
+         "40",
+         "45",
+         "35",
+         "30",
+         "40",
+         "55",
+         "1",
+         "False"
+        ],
+        [
+         "47",
+         "Golbat",
+         "Poison",
+         "Flying",
+         "75",
+         "80",
+         "70",
+         "65",
+         "75",
+         "90",
+         "1",
+         "False"
+        ],
+        [
+         "48",
+         "Oddish",
+         "Grass",
+         "Poison",
+         "45",
+         "50",
+         "55",
+         "75",
+         "65",
+         "30",
+         "1",
+         "False"
+        ],
+        [
+         "49",
+         "Gloom",
+         "Grass",
+         "Poison",
+         "60",
+         "65",
+         "70",
+         "85",
+         "75",
+         "40",
+         "1",
+         "False"
+        ]
+       ],
+       "shape": {
+        "columns": 11,
+        "rows": 800
+       }
+      },
       "text/html": [
        "<div>\n",
        "<style scoped>\n",
@@ -278,7 +1049,7 @@
        "[800 rows x 11 columns]"
       ]
      },
-     "execution_count": 3,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -295,13 +1066,47 @@
     "- We posit that Pokemons of type Dragon have, on average, more HP stats than Grass. Choose the propper test and, with 5% significance, comment your findings."
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "- H0: dragon_hp = grass_hp\n",
+    "- H1: dragon_hp != grass_hp"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
-    "#code here"
+    "dragon_hp = df[df['Type 1'] == 'Dragon']['HP']\n",
+    "grass_hp = df[df['Type 1'] == 'Grass']['HP']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.999200639025458\n"
+     ]
+    }
+   ],
+   "source": [
+    "_, p_value = st.ttest_ind(dragon_hp, grass_hp, equal_var=False, alternative= 'greater')\n",
+    "print(p_value)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Con un 5% de significancia podemos que decir que los Pokemon Dragon tienen mas HP promedio que los Pokemon Grass. (Al ser p < 0.05 rechazamos hipotesis nula y aceptamos alternativa)"
    ]
   },
   {
@@ -311,15 +1116,48 @@
     "- We posit that Legendary Pokemons have different stats (HP, Attack, Defense, Sp.Atk, Sp.Def, Speed) when comparing with Non-Legendary. Choose the propper test and, with 5% significance, comment your findings.\n"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "- H0: pokemon_legendary = pokemon_no_legendary\n",
+    "- H1: pokemon_legendary != pokemon_no_legendary"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
-    "#code here"
+    "legendary = df[df['Legendary'] == True][['HP', 'Attack', 'Defense', 'Sp. Atk', 'Sp. Def', 'Speed']]\n",
+    "no_legendary = df[df['Legendary'] == False][['HP', 'Attack', 'Defense', 'Sp. Atk', 'Sp. Def', 'Speed']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[1.00269117e-13 2.52037245e-16 4.82699849e-11 1.55146141e-21\n",
+      " 2.29493279e-15 1.04901631e-18]\n"
+     ]
+    }
+   ],
+   "source": [
+    "_, p_value = st.ttest_ind(legendary, no_legendary, equal_var=False, alternative= 'two-sided')\n",
+    "print(p_value)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -337,11 +1175,132 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
      "data": {
+      "application/vnd.microsoft.datawrangler.viewer.v0+json": {
+       "columns": [
+        {
+         "name": "index",
+         "rawType": "int64",
+         "type": "integer"
+        },
+        {
+         "name": "longitude",
+         "rawType": "float64",
+         "type": "float"
+        },
+        {
+         "name": "latitude",
+         "rawType": "float64",
+         "type": "float"
+        },
+        {
+         "name": "housing_median_age",
+         "rawType": "float64",
+         "type": "float"
+        },
+        {
+         "name": "total_rooms",
+         "rawType": "float64",
+         "type": "float"
+        },
+        {
+         "name": "total_bedrooms",
+         "rawType": "float64",
+         "type": "float"
+        },
+        {
+         "name": "population",
+         "rawType": "float64",
+         "type": "float"
+        },
+        {
+         "name": "households",
+         "rawType": "float64",
+         "type": "float"
+        },
+        {
+         "name": "median_income",
+         "rawType": "float64",
+         "type": "float"
+        },
+        {
+         "name": "median_house_value",
+         "rawType": "float64",
+         "type": "float"
+        }
+       ],
+       "ref": "e61f7b59-24c5-44c9-96bc-eb1201e73332",
+       "rows": [
+        [
+         "0",
+         "-114.31",
+         "34.19",
+         "15.0",
+         "5612.0",
+         "1283.0",
+         "1015.0",
+         "472.0",
+         "1.4936",
+         "66900.0"
+        ],
+        [
+         "1",
+         "-114.47",
+         "34.4",
+         "19.0",
+         "7650.0",
+         "1901.0",
+         "1129.0",
+         "463.0",
+         "1.82",
+         "80100.0"
+        ],
+        [
+         "2",
+         "-114.56",
+         "33.69",
+         "17.0",
+         "720.0",
+         "174.0",
+         "333.0",
+         "117.0",
+         "1.6509",
+         "85700.0"
+        ],
+        [
+         "3",
+         "-114.57",
+         "33.64",
+         "14.0",
+         "1501.0",
+         "337.0",
+         "515.0",
+         "226.0",
+         "3.1917",
+         "73400.0"
+        ],
+        [
+         "4",
+         "-114.57",
+         "33.57",
+         "20.0",
+         "1454.0",
+         "326.0",
+         "624.0",
+         "262.0",
+         "1.925",
+         "65500.0"
+        ]
+       ],
+       "shape": {
+        "columns": 9,
+        "rows": 5
+       }
+      },
       "text/html": [
        "<div>\n",
        "<style scoped>\n",
@@ -453,7 +1412,7 @@
        "4       624.0       262.0         1.9250             65500.0  "
       ]
      },
-     "execution_count": 5,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -476,24 +1435,1216 @@
     "\n",
     "Hint:\n",
     "- Write a function to calculate euclidean distance from each house (neighborhood) to the school and to the hospital.\n",
-    "- Divide your dataset into houses close and far from either a hospital or school.\n",
-    "- Choose the propper test and, with 5% significance, comment your findings.\n",
     " "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "def euclidean_distance(x1, y1, x2, y2):\n",
+    "    return np.sqrt((x2 - x1)**2 + (y2 - y1)**2)"
+   ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "school_coords = (-118, 34)\n",
+    "hospital_coords = (-122, 37)\n",
+    "\n",
+    "df[\"dist_school\"] = euclidean_distance(df[\"longitude\"], df[\"latitude\"], *school_coords)\n",
+    "df[\"dist_hospital\"] = euclidean_distance(df[\"longitude\"], df[\"latitude\"], *hospital_coords)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "- Divide your dataset into houses close and far from either a hospital or school."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df[\"close\"] = ((df[\"dist_school\"] < 0.5) | (df[\"dist_hospital\"] < 0.5))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "close = df[df[\"close\"] == True][\"median_house_value\"]\n",
+    "far = df[df[\"close\"] == False][\"median_house_value\"]\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "- Choose the propper test and, with 5% significance, comment your findings."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "ShapiroResult(statistic=np.float64(0.8809645503961219), pvalue=np.float64(3.6559147839921277e-19))"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "st.shapiro(close.sample(500, random_state=1))\n",
+    "st.shapiro(far.sample(500, random_state=1))\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Los datos no siguen una distribucion normal"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We posit that houses close to either a school or a hospital are more expensive.\n",
+    "\n",
+    "- H0: Los precios son iguales en independientemente de la distancia\n",
+    "- H1: Los precios son mayores si esta mas cerca de una escuela o un hospital"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "stat, p = st.mannwhitneyu(close, far, alternative=\"greater\")\n",
+    "print(p)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "El resultado es 0 por lo que rechazamos H0 y aceptamos H1, lo que significa que hay una diferencia en los precios relacionada a la distancia de las escuelas y hospitales."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.microsoft.datawrangler.viewer.v0+json": {
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+         "name": "index",
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+         "type": "float"
+        },
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+         "type": "float"
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+       "<div>\n",
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+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>longitude</th>\n",
+       "      <th>latitude</th>\n",
+       "      <th>housing_median_age</th>\n",
+       "      <th>total_rooms</th>\n",
+       "      <th>total_bedrooms</th>\n",
+       "      <th>population</th>\n",
+       "      <th>households</th>\n",
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+       "      <th>median_house_value</th>\n",
+       "      <th>dist_school</th>\n",
+       "      <th>dist_hospital</th>\n",
+       "      <th>close</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>-114.31</td>\n",
+       "      <td>34.19</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>5612.0</td>\n",
+       "      <td>1283.0</td>\n",
+       "      <td>1015.0</td>\n",
+       "      <td>472.0</td>\n",
+       "      <td>1.4936</td>\n",
+       "      <td>66900.0</td>\n",
+       "      <td>3.694888</td>\n",
+       "      <td>8.187319</td>\n",
+       "      <td>False</td>\n",
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+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>-114.47</td>\n",
+       "      <td>34.40</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>7650.0</td>\n",
+       "      <td>1901.0</td>\n",
+       "      <td>1129.0</td>\n",
+       "      <td>463.0</td>\n",
+       "      <td>1.8200</td>\n",
+       "      <td>80100.0</td>\n",
+       "      <td>3.552591</td>\n",
+       "      <td>7.966235</td>\n",
+       "      <td>False</td>\n",
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+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>-114.56</td>\n",
+       "      <td>33.69</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>720.0</td>\n",
+       "      <td>174.0</td>\n",
+       "      <td>333.0</td>\n",
+       "      <td>117.0</td>\n",
+       "      <td>1.6509</td>\n",
+       "      <td>85700.0</td>\n",
+       "      <td>3.453940</td>\n",
+       "      <td>8.143077</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>-114.57</td>\n",
+       "      <td>33.64</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>1501.0</td>\n",
+       "      <td>337.0</td>\n",
+       "      <td>515.0</td>\n",
+       "      <td>226.0</td>\n",
+       "      <td>3.1917</td>\n",
+       "      <td>73400.0</td>\n",
+       "      <td>3.448840</td>\n",
+       "      <td>8.154416</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>-114.57</td>\n",
+       "      <td>33.57</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>1454.0</td>\n",
+       "      <td>326.0</td>\n",
+       "      <td>624.0</td>\n",
+       "      <td>262.0</td>\n",
+       "      <td>1.9250</td>\n",
+       "      <td>65500.0</td>\n",
+       "      <td>3.456848</td>\n",
+       "      <td>8.183508</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16995</th>\n",
+       "      <td>-124.26</td>\n",
+       "      <td>40.58</td>\n",
+       "      <td>52.0</td>\n",
+       "      <td>2217.0</td>\n",
+       "      <td>394.0</td>\n",
+       "      <td>907.0</td>\n",
+       "      <td>369.0</td>\n",
+       "      <td>2.3571</td>\n",
+       "      <td>111400.0</td>\n",
+       "      <td>9.082070</td>\n",
+       "      <td>4.233675</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16996</th>\n",
+       "      <td>-124.27</td>\n",
+       "      <td>40.69</td>\n",
+       "      <td>36.0</td>\n",
+       "      <td>2349.0</td>\n",
+       "      <td>528.0</td>\n",
+       "      <td>1194.0</td>\n",
+       "      <td>465.0</td>\n",
+       "      <td>2.5179</td>\n",
+       "      <td>79000.0</td>\n",
+       "      <td>9.168915</td>\n",
+       "      <td>4.332320</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16997</th>\n",
+       "      <td>-124.30</td>\n",
+       "      <td>41.84</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>2677.0</td>\n",
+       "      <td>531.0</td>\n",
+       "      <td>1244.0</td>\n",
+       "      <td>456.0</td>\n",
+       "      <td>3.0313</td>\n",
+       "      <td>103600.0</td>\n",
+       "      <td>10.057614</td>\n",
+       "      <td>5.358694</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16998</th>\n",
+       "      <td>-124.30</td>\n",
+       "      <td>41.80</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>2672.0</td>\n",
+       "      <td>552.0</td>\n",
+       "      <td>1298.0</td>\n",
+       "      <td>478.0</td>\n",
+       "      <td>1.9797</td>\n",
+       "      <td>85800.0</td>\n",
+       "      <td>10.026465</td>\n",
+       "      <td>5.322593</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16999</th>\n",
+       "      <td>-124.35</td>\n",
+       "      <td>40.54</td>\n",
+       "      <td>52.0</td>\n",
+       "      <td>1820.0</td>\n",
+       "      <td>300.0</td>\n",
+       "      <td>806.0</td>\n",
+       "      <td>270.0</td>\n",
+       "      <td>3.0147</td>\n",
+       "      <td>94600.0</td>\n",
+       "      <td>9.115597</td>\n",
+       "      <td>4.249012</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>17000 rows × 12 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
+       "0        -114.31     34.19                15.0       5612.0          1283.0   \n",
+       "1        -114.47     34.40                19.0       7650.0          1901.0   \n",
+       "2        -114.56     33.69                17.0        720.0           174.0   \n",
+       "3        -114.57     33.64                14.0       1501.0           337.0   \n",
+       "4        -114.57     33.57                20.0       1454.0           326.0   \n",
+       "...          ...       ...                 ...          ...             ...   \n",
+       "16995    -124.26     40.58                52.0       2217.0           394.0   \n",
+       "16996    -124.27     40.69                36.0       2349.0           528.0   \n",
+       "16997    -124.30     41.84                17.0       2677.0           531.0   \n",
+       "16998    -124.30     41.80                19.0       2672.0           552.0   \n",
+       "16999    -124.35     40.54                52.0       1820.0           300.0   \n",
+       "\n",
+       "       population  households  median_income  median_house_value  dist_school  \\\n",
+       "0          1015.0       472.0         1.4936             66900.0     3.694888   \n",
+       "1          1129.0       463.0         1.8200             80100.0     3.552591   \n",
+       "2           333.0       117.0         1.6509             85700.0     3.453940   \n",
+       "3           515.0       226.0         3.1917             73400.0     3.448840   \n",
+       "4           624.0       262.0         1.9250             65500.0     3.456848   \n",
+       "...           ...         ...            ...                 ...          ...   \n",
+       "16995       907.0       369.0         2.3571            111400.0     9.082070   \n",
+       "16996      1194.0       465.0         2.5179             79000.0     9.168915   \n",
+       "16997      1244.0       456.0         3.0313            103600.0    10.057614   \n",
+       "16998      1298.0       478.0         1.9797             85800.0    10.026465   \n",
+       "16999       806.0       270.0         3.0147             94600.0     9.115597   \n",
+       "\n",
+       "       dist_hospital  close  \n",
+       "0           8.187319  False  \n",
+       "1           7.966235  False  \n",
+       "2           8.143077  False  \n",
+       "3           8.154416  False  \n",
+       "4           8.183508  False  \n",
+       "...              ...    ...  \n",
+       "16995       4.233675  False  \n",
+       "16996       4.332320  False  \n",
+       "16997       5.358694  False  \n",
+       "16998       5.322593  False  \n",
+       "16999       4.249012  False  \n",
+       "\n",
+       "[17000 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df"
+   ]
   }
  ],
  "metadata": {
@@ -512,7 +2663,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.9"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,