diff --git a/lab-hypothesis-testing.ipynb b/lab-hypothesis-testing.ipynb
index 0cc26d5..52ac4c7 100644
--- a/lab-hypothesis-testing.ipynb
+++ b/lab-hypothesis-testing.ipynb
@@ -38,7 +38,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -46,16 +46,789 @@
     "import pandas as pd\n",
     "import scipy.stats as st\n",
     "import numpy as np\n",
+    "from scipy import stats\n",
+    "from scipy.stats import ttest_ind\n",
     "\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 35,
    "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": "602ba2e1-a476-4f6f-8345-816ae8bb4e38",
+       "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 +1051,7 @@
        "[800 rows x 11 columns]"
       ]
      },
-     "execution_count": 3,
+     "execution_count": 35,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -297,11 +1070,54 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [],
    "source": [
-    "#code here"
+    "dragons = df[(df[\"Type 1\"] == \"Dragon\") | (df[\"Type 2\"] == \"Dragon\")][\"HP\"]\n",
+    "grass = df[(df[\"Type 1\"] == \"Grass\") | (df[\"Type 2\"] == \"Grass\")][\"HP\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "media_hp_dragon= dragons.mean()\n",
+    "media_hp_grass= grass.mean()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.00010181538122353851\n"
+     ]
+    }
+   ],
+   "source": [
+    "#Hipótesis: \n",
+    "# H0= media de vida de tipo dragon es igual  a la media de vida de tipo grass.\n",
+    "# H1= los dragon tienen más\n",
+    "# Usamosun Two Sample T-Test ya que son dos muestras independientes.\n",
+    "_, p_value = stats.ttest_ind(dragons, grass, equal_var=False)\n",
+    "print(p_value)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Como es menor que 0.05, descartamos H0 y aceptamos H1, osea que los de tipo dragón tienen más vida."
    ]
   },
   {
@@ -313,11 +1129,40 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 40,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "HP: t = 8.981370483625046, p = 1.0026911708035284e-13\n",
+      "Attack: t = 10.438133539322203, p = 2.520372449236646e-16\n",
+      "Defense: t = 7.637078164784618, p = 4.8269984949193316e-11\n",
+      "Sp. Atk: t = 13.417449984138461, p = 1.5514614112239812e-21\n",
+      "Sp. Def: t = 10.015696613114878, p = 2.2949327864052826e-15\n",
+      "Speed: t = 11.47504444631443, p = 1.049016311882451e-18\n"
+     ]
+    }
+   ],
    "source": [
-    "#code here"
+    "#Hipótesis: para cada estadística vamos a establecer que\n",
+    "#H0= las estadísticas no varían entre pokemon legendarios y el resto\n",
+    "#H1= las estadísticas son diferentes.\n",
+    "#Usamos el mismo test de antes porque comparamos dos  muestras independientes (legendarios y no legendarios)\n",
+    "legendary = df[df['Legendary'] == True]\n",
+    "non_legendary = df[df['Legendary'] == False]\n",
+    "stats = ['HP', 'Attack', 'Defense', 'Sp. Atk', 'Sp. Def', 'Speed']\n",
+    "for stat in stats:\n",
+    "    t_stat, p_val = ttest_ind(legendary[stat], non_legendary[stat], equal_var=False)\n",
+    "    print(f\"{stat}: t = {t_stat}, p = {p_val}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Como todos los p_values son mucho menores que 0.05, descartamos la hipotesis nula y aceptamos la alternativa, por lo que los pokemon legendarios tienen valores diferentes al resto."
    ]
   },
   {
@@ -337,11 +1182,132 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 41,
    "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": "ec75fc87-8d8a-42f2-954e-a301a75498d5",
+       "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",
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       "text/html": [
        "<div>\n",
        "<style scoped>\n",
@@ -453,7 +1419,7 @@
        "4       624.0       262.0         1.9250             65500.0  "
       ]
      },
-     "execution_count": 5,
+     "execution_count": 41,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -483,22 +1449,3324 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 42,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "#Empezamos con la función:\n",
+    "school = (-118, 34)\n",
+    "hospital = (-122, 37)\n",
+    "def distance(lon, lat, point):\n",
+    "    return np.sqrt((lon - point[0])**2 + (lat - point[1])**2)"
+   ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 43,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
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+       "      <th>longitude</th>\n",
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+       "      <th>total_rooms</th>\n",
+       "      <th>total_bedrooms</th>\n",
+       "      <th>population</th>\n",
+       "      <th>households</th>\n",
+       "      <th>median_income</th>\n",
+       "      <th>median_house_value</th>\n",
+       "      <th>dist_school</th>\n",
+       "      <th>dist_hospital</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",
+       "    </tr>\n",
+       "    <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",
+       "    </tr>\n",
+       "    <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",
+       "    </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",
+       "    </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",
+       "    </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",
+       "    </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",
+       "    </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",
+       "    </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",
+       "    </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",
+       "    </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",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>17000 rows × 11 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  \n",
+       "0           8.187319  \n",
+       "1           7.966235  \n",
+       "2           8.143077  \n",
+       "3           8.154416  \n",
+       "4           8.183508  \n",
+       "...              ...  \n",
+       "16995       4.233675  \n",
+       "16996       4.332320  \n",
+       "16997       5.358694  \n",
+       "16998       5.322593  \n",
+       "16999       4.249012  \n",
+       "\n",
+       "[17000 rows x 11 columns]"
+      ]
+     },
+     "execution_count": 43,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Creamos dos columnas nuevas con las distancias al hospital y al colegio\n",
+    "df['dist_school'] = distance(df['longitude'], df['latitude'], school)\n",
+    "df['dist_hospital'] = distance(df['longitude'], df['latitude'], hospital)\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "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"
+        },
+        {
+         "name": "dist_school",
+         "rawType": "float64",
+         "type": "float"
+        },
+        {
+         "name": "dist_hospital",
+         "rawType": "float64",
+         "type": "float"
+        },
+        {
+         "name": "min_dist",
+         "rawType": "float64",
+         "type": "float"
+        }
+       ],
+       "ref": "69838862-dd73-4aca-8f7e-ae44a09322b4",
+       "rows": [
+        [
+         "0",
+         "-114.31",
+         "34.19",
+         "15.0",
+         "5612.0",
+         "1283.0",
+         "1015.0",
+         "472.0",
+         "1.4936",
+         "66900.0",
+         "3.694888360965725",
+         "8.187319463658419",
+         "3.694888360965725"
+        ],
+        [
+         "1",
+         "-114.47",
+         "34.4",
+         "19.0",
+         "7650.0",
+         "1901.0",
+         "1129.0",
+         "463.0",
+         "1.82",
+         "80100.0",
+         "3.552590604052204",
+         "7.966234995278511",
+         "3.552590604052204"
+        ],
+        [
+         "2",
+         "-114.56",
+         "33.69",
+         "17.0",
+         "720.0",
+         "174.0",
+         "333.0",
+         "117.0",
+         "1.6509",
+         "85700.0",
+         "3.453939779440282",
+         "8.143076814079551",
+         "3.453939779440282"
+        ],
+        [
+         "3",
+         "-114.57",
+         "33.64",
+         "14.0",
+         "1501.0",
+         "337.0",
+         "515.0",
+         "226.0",
+         "3.1917",
+         "73400.0",
+         "3.448840384825028",
+         "8.154415981540316",
+         "3.448840384825028"
+        ],
+        [
+         "4",
+         "-114.57",
+         "33.57",
+         "20.0",
+         "1454.0",
+         "326.0",
+         "624.0",
+         "262.0",
+         "1.925",
+         "65500.0",
+         "3.4568482755249827",
+         "8.183507805336298",
+         "3.4568482755249827"
+        ],
+        [
+         "5",
+         "-114.58",
+         "33.63",
+         "29.0",
+         "1387.0",
+         "236.0",
+         "671.0",
+         "239.0",
+         "3.3438",
+         "74000.0",
+         "3.439956395072474",
+         "8.14943556327676",
+         "3.439956395072474"
+        ],
+        [
+         "6",
+         "-114.58",
+         "33.61",
+         "25.0",
+         "2907.0",
+         "680.0",
+         "1841.0",
+         "633.0",
+         "2.6768",
+         "82400.0",
+         "3.442165016381407",
+         "8.157726398942296",
+         "3.442165016381407"
+        ],
+        [
+         "7",
+         "-114.59",
+         "34.83",
+         "41.0",
+         "812.0",
+         "168.0",
+         "375.0",
+         "158.0",
+         "1.7083",
+         "48500.0",
+         "3.5095583767761966",
+         "7.721204569236587",
+         "3.5095583767761966"
+        ],
+        [
+         "8",
+         "-114.59",
+         "33.61",
+         "34.0",
+         "4789.0",
+         "1175.0",
+         "3134.0",
+         "1056.0",
+         "2.1782",
+         "58400.0",
+         "3.4322295960497713",
+         "8.148631786993443",
+         "3.4322295960497713"
+        ],
+        [
+         "9",
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+         "1497.0",
+         "309.0",
+         "787.0",
+         "271.0",
+         "2.1908",
+         "48100.0",
+         "3.499842853615007",
+         "7.711608133197647",
+         "3.499842853615007"
+        ],
+        [
+         "10",
+         "-114.6",
+         "33.62",
+         "16.0",
+         "3741.0",
+         "801.0",
+         "2434.0",
+         "824.0",
+         "2.6797",
+         "86500.0",
+         "3.4211693907200855",
+         "8.1353795240296",
+         "3.4211693907200855"
+        ],
+        [
+         "11",
+         "-114.6",
+         "33.6",
+         "21.0",
+         "1988.0",
+         "483.0",
+         "1182.0",
+         "437.0",
+         "1.625",
+         "62000.0",
+         "3.4234485537247434",
+         "8.143709228600938",
+         "3.4234485537247434"
+        ],
+        [
+         "12",
+         "-114.61",
+         "34.84",
+         "48.0",
+         "1291.0",
+         "248.0",
+         "580.0",
+         "211.0",
+         "2.1571",
+         "48600.0",
+         "3.4925205797532546",
+         "7.69920125727338",
+         "3.4925205797532546"
+        ],
+        [
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+         "-114.61",
+         "34.83",
+         "31.0",
+         "2478.0",
+         "464.0",
+         "1346.0",
+         "479.0",
+         "3.212",
+         "70400.0",
+         "3.4901289374462947",
+         "7.702012723957291",
+         "3.4901289374462947"
+        ],
+        [
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+         "-114.63",
+         "32.76",
+         "15.0",
+         "1448.0",
+         "378.0",
+         "949.0",
+         "300.0",
+         "0.8585",
+         "45000.0",
+         "3.5908912542710114",
+         "8.502617244119605",
+         "3.5908912542710114"
+        ],
+        [
+         "15",
+         "-114.65",
+         "34.89",
+         "17.0",
+         "2556.0",
+         "587.0",
+         "1005.0",
+         "401.0",
+         "1.6991",
+         "69100.0",
+         "3.466208303030844",
+         "7.6468686401689885",
+         "3.466208303030844"
+        ],
+        [
+         "16",
+         "-114.65",
+         "33.6",
+         "28.0",
+         "1678.0",
+         "322.0",
+         "666.0",
+         "256.0",
+         "2.9653",
+         "94900.0",
+         "3.3737960815674617",
+         "8.098302291221286",
+         "3.3737960815674617"
+        ],
+        [
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+         "21.0",
+         "44.0",
+         "33.0",
+         "64.0",
+         "27.0",
+         "0.8571",
+         "25000.0",
+         "3.5618253747200974",
+         "8.470336475016794",
+         "3.5618253747200974"
+        ],
+        [
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+         "775.0",
+         "320.0",
+         "1.2049",
+         "44000.0",
+         "3.569761896821694",
+         "8.48664833724127",
+         "3.569761896821694"
+        ],
+        [
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+         "17.0",
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+         "24.0",
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+         "27500.0",
+         "3.3309608223454066",
+         "7.950804990691192",
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+        ],
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+         "44400.0",
+         "3.3589432862136794",
+         "8.118035476640879",
+         "3.3589432862136794"
+        ],
+        [
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+         "33.43",
+         "24.0",
+         "796.0",
+         "243.0",
+         "227.0",
+         "139.0",
+         "0.8964",
+         "59200.0",
+         "3.3193071566216905",
+         "8.0992468785684",
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+        ],
+        [
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+         "34.55",
+         "20.0",
+         "350.0",
+         "95.0",
+         "119.0",
+         "58.0",
+         "1.625",
+         "50000.0",
+         "3.109035220128587",
+         "7.473024822653812",
+         "3.109035220128587"
+        ],
+        [
+         "23",
+         "-114.98",
+         "33.82",
+         "15.0",
+         "644.0",
+         "129.0",
+         "137.0",
+         "52.0",
+         "3.2097",
+         "71300.0",
+         "3.0253594827722496",
+         "7.706672433677192",
+         "3.0253594827722496"
+        ],
+        [
+         "24",
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+         "18.0",
+         "1706.0",
+         "397.0",
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+         "7.7963132312651435",
+         "2.818244134208386"
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+       ],
+       "shape": {
+        "columns": 12,
+        "rows": 17000
+       }
+      },
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<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",
+       "      <th>median_income</th>\n",
+       "      <th>median_house_value</th>\n",
+       "      <th>dist_school</th>\n",
+       "      <th>dist_hospital</th>\n",
+       "      <th>min_dist</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>3.694888</td>\n",
+       "    </tr>\n",
+       "    <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>3.552591</td>\n",
+       "    </tr>\n",
+       "    <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>3.453940</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>3.448840</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>3.456848</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>4.233675</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>4.332320</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>5.358694</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>5.322593</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>4.249012</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  min_dist  \n",
+       "0           8.187319  3.694888  \n",
+       "1           7.966235  3.552591  \n",
+       "2           8.143077  3.453940  \n",
+       "3           8.154416  3.448840  \n",
+       "4           8.183508  3.456848  \n",
+       "...              ...       ...  \n",
+       "16995       4.233675  4.233675  \n",
+       "16996       4.332320  4.332320  \n",
+       "16997       5.358694  5.358694  \n",
+       "16998       5.322593  5.322593  \n",
+       "16999       4.249012  4.249012  \n",
+       "\n",
+       "[17000 rows x 12 columns]"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#Calculamos las que están más cerca de ambas\n",
+    "df['min_dist'] = df[['dist_school', 'dist_hospital']].min(axis=1)\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {},
+   "outputs": [
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+         "20.0",
+         "1402.0",
+         "287.0",
+         "1104.0",
+         "317.0",
+         "1.9088",
+         "63700.0",
+         "2.6870429843975274",
+         "7.628905557155622",
+         "2.6870429843975274",
+         "far"
+        ],
+        [
+         "49",
+         "-115.51",
+         "32.68",
+         "11.0",
+         "2872.0",
+         "610.0",
+         "2644.0",
+         "581.0",
+         "2.625",
+         "72700.0",
+         "2.818244134208386",
+         "7.7963132312651435",
+         "2.818244134208386",
+         "far"
+        ]
+       ],
+       "shape": {
+        "columns": 13,
+        "rows": 17000
+       }
+      },
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<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",
+       "      <th>median_income</th>\n",
+       "      <th>median_house_value</th>\n",
+       "      <th>dist_school</th>\n",
+       "      <th>dist_hospital</th>\n",
+       "      <th>min_dist</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>3.694888</td>\n",
+       "      <td>far</td>\n",
+       "    </tr>\n",
+       "    <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>3.552591</td>\n",
+       "      <td>far</td>\n",
+       "    </tr>\n",
+       "    <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>3.453940</td>\n",
+       "      <td>far</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>3.448840</td>\n",
+       "      <td>far</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>3.456848</td>\n",
+       "      <td>far</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",
+       "      <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>4.233675</td>\n",
+       "      <td>far</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>4.332320</td>\n",
+       "      <td>far</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>5.358694</td>\n",
+       "      <td>far</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>5.322593</td>\n",
+       "      <td>far</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>4.249012</td>\n",
+       "      <td>far</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>17000 rows × 13 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  min_dist close  \n",
+       "0           8.187319  3.694888   far  \n",
+       "1           7.966235  3.552591   far  \n",
+       "2           8.143077  3.453940   far  \n",
+       "3           8.154416  3.448840   far  \n",
+       "4           8.183508  3.456848   far  \n",
+       "...              ...       ...   ...  \n",
+       "16995       4.233675  4.233675   far  \n",
+       "16996       4.332320  4.332320   far  \n",
+       "16997       5.358694  5.358694   far  \n",
+       "16998       5.322593  5.322593   far  \n",
+       "16999       4.249012  4.249012   far  \n",
+       "\n",
+       "[17000 rows x 13 columns]"
+      ]
+     },
+     "execution_count": 45,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Definimos \"close\" si la distancia está a menos de 0.5 y \"far\" para el resto\n",
+    "df['close'] = np.where(df['min_dist'] < 0.5, 'close', 'far')\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "t = 37.992330214201516, p = 1.5032478884296307e-301\n"
+     ]
+    }
+   ],
+   "source": [
+    "#Comparamos los valores, estableciendo la hipótesis: H0 = no varía el precio según la distancia H1= sí varía\n",
+    "close = df[df['close'] == 'close']['median_house_value']\n",
+    "far = df[df['close'] == 'far']['median_house_value']\n",
+    "t_stat, p_val = ttest_ind(close, far, equal_var=False, alternative='greater')\n",
+    "print(f\"t = {t_stat}, p = {p_val}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Como el p_value es mucho menor que 0-05, descartamos la hipótesis nula y aceptamos la alternativa, \n",
+    "osea que el precio de una casa sí depende de la distancia al hospital y al colegio."
+   ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "base",
    "language": "python",
    "name": "python3"
   },
@@ -512,7 +4780,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.9"
+   "version": "3.13.5"
   }
  },
  "nbformat": 4,