Group Assigment/Assigment #4.ipynb

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   "id": "be0b7864-5db3-4d9d-a3cb-0bff6a456ec0",
   "metadata": {},
   "source": [
    "# **LA County Median Household Income**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56d0589f-74ff-4ced-8328-6f7f75131908",
   "metadata": {},
   "source": [
    "## Jessica Melendez\n",
    "\n",
    "The purpose of this notebook is to see if there are any differences among zip codes as compared to cities from the last notebook I did. I will also be focusing this dataset to be more accurate by looking at 2019 inflation adjusted median household income. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "906d0d70-1bdb-48c7-8527-77891a0df8d8",
   "metadata": {},
   "source": [
    "Let's start with the libraries..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ba7cc0e3-112b-434c-a199-90ed478cb0b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "import geopandas as gpd\n",
    "\n",
    "import contextily as ctx\n",
    "\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b73759f0-62d7-492b-9eb1-ee95cd452886",
   "metadata": {},
   "source": [
    "## Importing Updated Data\n",
    "Again, this time we will be looking at data based on zip code versus name of city."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "01fe749d-d79e-41a5-9da6-92d0dbc08ca1",
   "metadata": {},
   "outputs": [],
   "source": [
    "LA_income = gpd.read_file('data/LAincome.geojson')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "579de214-6901-4c66-9079-0794b8da11d4",
   "metadata": {},
   "source": [
    "Great! Now, how big is the data set?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "788e3979-9084-4bbb-bafc-743987640752",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(303, 5)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "LA_income.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2588d12c-0c77-4c7d-bc7f-3c6e2ed8e879",
   "metadata": {},
   "source": [
    "303 rows and 5 columns... okay, definitely more than the last data set we imported!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e4f14c3-222f-48b9-9285-b311a309f092",
   "metadata": {},
   "source": [
    "Let's get a sample of where it starts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1ffde539-82f7-471b-ac3f-44bcf8188c77",
   "metadata": {},
   "outputs": [
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       "      <th>0</th>\n",
       "      <td>05000US06037</td>\n",
       "      <td>Los Angeles County, CA</td>\n",
       "      <td>68044.0</td>\n",
       "      <td>347.0</td>\n",
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       "      <th>1</th>\n",
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       "      <td>90001</td>\n",
       "      <td>43360.0</td>\n",
       "      <td>2437.0</td>\n",
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       "      <th>2</th>\n",
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       "      <td>90002</td>\n",
       "      <td>37285.0</td>\n",
       "      <td>1920.0</td>\n",
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       "      <th>3</th>\n",
       "      <td>86000US90003</td>\n",
       "      <td>90003</td>\n",
       "      <td>40598.0</td>\n",
       "      <td>1743.0</td>\n",
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       "      <th>4</th>\n",
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       "      <td>90004</td>\n",
       "      <td>49675.0</td>\n",
       "      <td>1784.0</td>\n",
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      "text/plain": [
       "          geoid                    name  B19013001  B19013001, Error  \\\n",
       "0  05000US06037  Los Angeles County, CA    68044.0             347.0   \n",
       "1  86000US90001                   90001    43360.0            2437.0   \n",
       "2  86000US90002                   90002    37285.0            1920.0   \n",
       "3  86000US90003                   90003    40598.0            1743.0   \n",
       "4  86000US90004                   90004    49675.0            1784.0   \n",
       "\n",
       "                                            geometry  \n",
       "0  MULTIPOLYGON (((-118.70339 34.16859, -118.7033...  \n",
       "1  MULTIPOLYGON (((-118.26519 33.98923, -118.2620...  \n",
       "2  MULTIPOLYGON (((-118.26516 33.94643, -118.2651...  \n",
       "3  MULTIPOLYGON (((-118.28320 33.98914, -118.2826...  \n",
       "4  MULTIPOLYGON (((-118.33858 34.08346, -118.3381...  "
      ]
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     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "LA_income.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5696b73d-7061-425e-bb47-c5a18478fc18",
   "metadata": {},
   "source": [
    "I see it starts with the 90001 Zip Code... South Central represent! 90003- I organized there at Fremont High School not too long ago..."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ff6d5b8-06c1-41c9-8a24-17c750f76fb3",
   "metadata": {},
   "source": [
    "Okay, so what the end look like?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "48c23f61-f30a-42fd-8b14-186d586c5666",
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   "outputs": [
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       "      <th>298</th>\n",
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       "      <td>93552</td>\n",
       "      <td>65728.0</td>\n",
       "      <td>2550.0</td>\n",
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       "      <td>51630.0</td>\n",
       "      <td>21791.0</td>\n",
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       "      <td>60743.0</td>\n",
       "      <td>7969.0</td>\n",
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       "            geoid   name  B19013001  B19013001, Error  \\\n",
       "298  86000US93552  93552    65728.0            2550.0   \n",
       "299  86000US93553  93553    51630.0           21791.0   \n",
       "300  86000US93560  93560    60743.0            7969.0   \n",
       "301  86000US93563  93563        NaN               NaN   \n",
       "302  86000US93591  93591    47453.0            3167.0   \n",
       "\n",
       "                                              geometry  \n",
       "298  MULTIPOLYGON (((-118.07917 34.51358, -118.0716...  \n",
       "299  MULTIPOLYGON (((-118.01330 34.35839, -118.0132...  \n",
       "300  MULTIPOLYGON (((-118.43128 34.88985, -118.4312...  \n",
       "301  MULTIPOLYGON (((-117.87587 34.45627, -117.8756...  \n",
       "302  MULTIPOLYGON (((-117.99174 34.66059, -117.9915...  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "LA_income.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a65c47a0-afe0-48e0-93dd-664c85e1949a",
   "metadata": {},
   "source": [
    "Looks like the Lancaster/Palmdale area"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d0330f41-4a14-4634-ad9d-8782b6ec1be4",
   "metadata": {},
   "source": [
    "let's look at a random sample now."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3e31bed3-d406-494c-9c53-bce7a4131845",
   "metadata": {},
   "outputs": [
    {
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       "      <td>91321</td>\n",
       "      <td>73187.0</td>\n",
       "      <td>5202.0</td>\n",
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       "            geoid   name  B19013001  B19013001, Error  \\\n",
       "204  86000US91321  91321    73187.0            5202.0   \n",
       "\n",
       "                                              geometry  \n",
       "204  MULTIPOLYGON (((-118.56958 34.38733, -118.5692...  "
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     "execution_count": 6,
     "metadata": {},
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   "source": [
    "LA_income.sample()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0aced40d-bb34-46fc-9b1b-27955df94997",
   "metadata": {},
   "source": [
    "Santa Monica! We all know where that's at"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3c93167-e0c1-4b1b-bcaf-fcf671160071",
   "metadata": {},
   "source": [
    "## Let's get to plotting this table to begin visualizing this data!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9254e984-83b8-462f-b9b6-69de9781e0f8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "LA_income.plot(figsize=(10,10))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9dd3bd74-9cbd-468b-ab21-81633b9daa46",
   "metadata": {},
   "source": [
    "Nice! That looks great! Looks like it goes a little beyond just LA County too!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "182a39e0-7cf2-4a71-aa49-35c9d28bb6aa",
   "metadata": {},
   "source": [
    "What data types are in this data set now?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "54bbb8d5-b48d-476a-b31b-900013c27cfc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'geopandas.geodataframe.GeoDataFrame'>\n",
      "RangeIndex: 303 entries, 0 to 302\n",
      "Data columns (total 5 columns):\n",
      " #   Column            Non-Null Count  Dtype   \n",
      "---  ------            --------------  -----   \n",
      " 0   geoid             303 non-null    object  \n",
      " 1   name              303 non-null    object  \n",
      " 2   B19013001         288 non-null    float64 \n",
      " 3   B19013001, Error  288 non-null    float64 \n",
      " 4   geometry          303 non-null    geometry\n",
      "dtypes: float64(2), geometry(1), object(2)\n",
      "memory usage: 12.0+ KB\n"
     ]
    }
   ],
   "source": [
    "LA_income.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e33dbcdf-a9e8-4b17-999a-f8720a6cec11",
   "metadata": {},
   "source": [
    "Look at that summarized data set! Let's look at the FIPS code again since we might continue incorporating county data from the census."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d1678b0d-a38e-4624-ae01-9e268db0a51b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    05000US06037\n",
       "1    86000US90001\n",
       "2    86000US90002\n",
       "3    86000US90003\n",
       "4    86000US90004\n",
       "Name: geoid, dtype: object"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "LA_income.geoid.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6bd90322-9401-4780-bf4e-e1a7ac42aa57",
   "metadata": {},
   "source": [
    "Again, this first row is for the entire county. We can do without it so let's drop the first row."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "252431f8-d215-4368-b18c-37b0d1534c19",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\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>geoid</th>\n",
       "      <th>name</th>\n",
       "      <th>B19013001</th>\n",
       "      <th>B19013001, Error</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>05000US06037</td>\n",
       "      <td>Los Angeles County, CA</td>\n",
       "      <td>68044.0</td>\n",
       "      <td>347.0</td>\n",
       "      <td>MULTIPOLYGON (((-118.70339 34.16859, -118.7033...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>86000US90001</td>\n",
       "      <td>90001</td>\n",
       "      <td>43360.0</td>\n",
       "      <td>2437.0</td>\n",
       "      <td>MULTIPOLYGON (((-118.26519 33.98923, -118.2620...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>86000US90002</td>\n",
       "      <td>90002</td>\n",
       "      <td>37285.0</td>\n",
       "      <td>1920.0</td>\n",
       "      <td>MULTIPOLYGON (((-118.26516 33.94643, -118.2651...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>86000US90003</td>\n",
       "      <td>90003</td>\n",
       "      <td>40598.0</td>\n",
       "      <td>1743.0</td>\n",
       "      <td>MULTIPOLYGON (((-118.28320 33.98914, -118.2826...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>86000US90004</td>\n",
       "      <td>90004</td>\n",
       "      <td>49675.0</td>\n",
       "      <td>1784.0</td>\n",
       "      <td>MULTIPOLYGON (((-118.33858 34.08346, -118.3381...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          geoid                    name  B19013001  B19013001, Error  \\\n",
       "0  05000US06037  Los Angeles County, CA    68044.0             347.0   \n",
       "1  86000US90001                   90001    43360.0            2437.0   \n",
       "2  86000US90002                   90002    37285.0            1920.0   \n",
       "3  86000US90003                   90003    40598.0            1743.0   \n",
       "4  86000US90004                   90004    49675.0            1784.0   \n",
       "\n",
       "                                            geometry  \n",
       "0  MULTIPOLYGON (((-118.70339 34.16859, -118.7033...  \n",
       "1  MULTIPOLYGON (((-118.26519 33.98923, -118.2620...  \n",
       "2  MULTIPOLYGON (((-118.26516 33.94643, -118.2651...  \n",
       "3  MULTIPOLYGON (((-118.28320 33.98914, -118.2826...  \n",
       "4  MULTIPOLYGON (((-118.33858 34.08346, -118.3381...  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "LA_income.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "418bf50a-6d5f-4358-9fd9-d8b4e4da8c3e",
   "metadata": {},
   "outputs": [],
   "source": [
    "LA_income = LA_income.drop([0])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71d20631-f052-4f1d-a805-fce8034bca0a",
   "metadata": {},
   "source": [
    "Okay, how does it look without it now"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "59a75bbe-8b43-45e8-9231-b627f6566871",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "\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>geoid</th>\n",
       "      <th>name</th>\n",
       "      <th>B19013001</th>\n",
       "      <th>B19013001, Error</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>86000US90001</td>\n",
       "      <td>90001</td>\n",
       "      <td>43360.0</td>\n",
       "      <td>2437.0</td>\n",
       "      <td>MULTIPOLYGON (((-118.26519 33.98923, -118.2620...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>86000US90002</td>\n",
       "      <td>90002</td>\n",
       "      <td>37285.0</td>\n",
       "      <td>1920.0</td>\n",
       "      <td>MULTIPOLYGON (((-118.26516 33.94643, -118.2651...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>86000US90003</td>\n",
       "      <td>90003</td>\n",
       "      <td>40598.0</td>\n",
       "      <td>1743.0</td>\n",
       "      <td>MULTIPOLYGON (((-118.28320 33.98914, -118.2826...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>86000US90004</td>\n",
       "      <td>90004</td>\n",
       "      <td>49675.0</td>\n",
       "      <td>1784.0</td>\n",
       "      <td>MULTIPOLYGON (((-118.33858 34.08346, -118.3381...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>86000US90005</td>\n",
       "      <td>90005</td>\n",
       "      <td>38491.0</td>\n",
       "      <td>2241.0</td>\n",
       "      <td>MULTIPOLYGON (((-118.29291 34.06360, -118.2923...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          geoid   name  B19013001  B19013001, Error  \\\n",
       "1  86000US90001  90001    43360.0            2437.0   \n",
       "2  86000US90002  90002    37285.0            1920.0   \n",
       "3  86000US90003  90003    40598.0            1743.0   \n",
       "4  86000US90004  90004    49675.0            1784.0   \n",
       "5  86000US90005  90005    38491.0            2241.0   \n",
       "\n",
       "                                            geometry  \n",
       "1  MULTIPOLYGON (((-118.26519 33.98923, -118.2620...  \n",
       "2  MULTIPOLYGON (((-118.26516 33.94643, -118.2651...  \n",
       "3  MULTIPOLYGON (((-118.28320 33.98914, -118.2826...  \n",
       "4  MULTIPOLYGON (((-118.33858 34.08346, -118.3381...  \n",
       "5  MULTIPOLYGON (((-118.29291 34.06360, -118.2923...  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "LA_income.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bdcc1188-1e41-4f09-828b-206c37efc3ee",
   "metadata": {},
   "source": [
    "Awesome! Seems like we're on the right track."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "03b64a36-23ee-4290-ab1e-14224bd2adc9",
   "metadata": {},
   "source": [
    "## Let's see what else we can do with this census data!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe41fa2d-c76d-451d-83f5-74a9862f3388",
   "metadata": {},
   "source": [
    "For starters, let's look at the list of columns we're working with."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "25f5ef99-a68d-467c-ba69-ec5e14a38b90",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['geoid', 'name', 'B19013001', 'B19013001, Error', 'geometry']"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(LA_income)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "00940404-95c7-486f-94b4-1e483d416276",
   "metadata": {},
   "source": [
    "Interesting! Again, only 5 columns so I'm realizing we may not be able to do what I had hoped for and calculate percentages by zip code since they all fall within the zip code column rather than being separated in different columns individually. It's okay. Its still a new data set but within the research we aim to look at. Let's keep working..."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b72175b1-fc3a-42f8-bd64-0e54a42ca696",
   "metadata": {},
   "source": [
    "Alright, let's sort through some of this data and keep only the columns we need."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "065a2fce-b679-46cf-bfe0-5eb9f5c6ca98",
   "metadata": {},
   "outputs": [],
   "source": [
    "columns_to_keep = ['geoid',\n",
    " 'name',\n",
    " 'B19013001',\n",
    " 'geometry']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e498a8a1-8284-46dd-aae7-707c1e50f2e1",
   "metadata": {},
   "source": [
    "Toodaloo B19013001, Error! We're sticking with the median household income adjusted for inflation to keep our data more accurate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "cbc1e27d-816e-4b12-be30-89289d6f4d39",
   "metadata": {},
   "outputs": [],
   "source": [
    "LA_income = LA_income[columns_to_keep]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9e100d7-4401-448d-9bd0-7d244e1a2391",
   "metadata": {},
   "source": [
    "Okay, so what's that look like now?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "55d8ad8a-eee5-4da7-b357-3138cd77c109",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>geoid</th>\n",
       "      <th>name</th>\n",
       "      <th>B19013001</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>86000US90001</td>\n",
       "      <td>90001</td>\n",
       "      <td>43360.0</td>\n",
       "      <td>MULTIPOLYGON (((-118.26519 33.98923, -118.2620...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>86000US90002</td>\n",
       "      <td>90002</td>\n",
       "      <td>37285.0</td>\n",
       "      <td>MULTIPOLYGON (((-118.26516 33.94643, -118.2651...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>86000US90003</td>\n",
       "      <td>90003</td>\n",
       "      <td>40598.0</td>\n",
       "      <td>MULTIPOLYGON (((-118.28320 33.98914, -118.2826...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>86000US90004</td>\n",
       "      <td>90004</td>\n",
       "      <td>49675.0</td>\n",
       "      <td>MULTIPOLYGON (((-118.33858 34.08346, -118.3381...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>86000US90005</td>\n",
       "      <td>90005</td>\n",
       "      <td>38491.0</td>\n",
       "      <td>MULTIPOLYGON (((-118.29291 34.06360, -118.2923...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          geoid   name  B19013001  \\\n",
       "1  86000US90001  90001    43360.0   \n",
       "2  86000US90002  90002    37285.0   \n",
       "3  86000US90003  90003    40598.0   \n",
       "4  86000US90004  90004    49675.0   \n",
       "5  86000US90005  90005    38491.0   \n",
       "\n",
       "                                            geometry  \n",
       "1  MULTIPOLYGON (((-118.26519 33.98923, -118.2620...  \n",
       "2  MULTIPOLYGON (((-118.26516 33.94643, -118.2651...  \n",
       "3  MULTIPOLYGON (((-118.28320 33.98914, -118.2826...  \n",
       "4  MULTIPOLYGON (((-118.33858 34.08346, -118.3381...  \n",
       "5  MULTIPOLYGON (((-118.29291 34.06360, -118.2923...  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "LA_income.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d2e0a60c-6e62-4ed1-a32b-b798cc489521",
   "metadata": {},
   "source": [
    "Hmmm... better but who understands what B19013001, means?! Let's simplify and rename the column!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "566291e7-08a8-4b40-964c-b8c249c3997c",
   "metadata": {},
   "outputs": [],
   "source": [
    "LA_income.columns = ['geoid',\n",
    " 'zipcode',\n",
    " 'mhhi_adj',\n",
    " 'geometry']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9f924f4-5bb2-4291-952c-8ddace3d47bb",
   "metadata": {},
   "source": [
    "Great! Let's see what that looks like as a table!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "c2ef6051-541b-4f1d-b467-2352914c8404",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>geoid</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>mhhi_adj</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>86000US90001</td>\n",
       "      <td>90001</td>\n",
       "      <td>43360.0</td>\n",
       "      <td>MULTIPOLYGON (((-118.26519 33.98923, -118.2620...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>86000US90002</td>\n",
       "      <td>90002</td>\n",
       "      <td>37285.0</td>\n",
       "      <td>MULTIPOLYGON (((-118.26516 33.94643, -118.2651...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>86000US90003</td>\n",
       "      <td>90003</td>\n",
       "      <td>40598.0</td>\n",
       "      <td>MULTIPOLYGON (((-118.28320 33.98914, -118.2826...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>86000US90004</td>\n",
       "      <td>90004</td>\n",
       "      <td>49675.0</td>\n",
       "      <td>MULTIPOLYGON (((-118.33858 34.08346, -118.3381...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>86000US90005</td>\n",
       "      <td>90005</td>\n",
       "      <td>38491.0</td>\n",
       "      <td>MULTIPOLYGON (((-118.29291 34.06360, -118.2923...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          geoid zipcode  mhhi_adj  \\\n",
       "1  86000US90001   90001   43360.0   \n",
       "2  86000US90002   90002   37285.0   \n",
       "3  86000US90003   90003   40598.0   \n",
       "4  86000US90004   90004   49675.0   \n",
       "5  86000US90005   90005   38491.0   \n",
       "\n",
       "                                            geometry  \n",
       "1  MULTIPOLYGON (((-118.26519 33.98923, -118.2620...  \n",
       "2  MULTIPOLYGON (((-118.26516 33.94643, -118.2651...  \n",
       "3  MULTIPOLYGON (((-118.28320 33.98914, -118.2826...  \n",
       "4  MULTIPOLYGON (((-118.33858 34.08346, -118.3381...  \n",
       "5  MULTIPOLYGON (((-118.29291 34.06360, -118.2923...  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "LA_income.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6a70b76-410e-4b98-b1e7-513e6223639b",
   "metadata": {},
   "source": [
    "## Moving on!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f6db932c-8b80-4c3f-8ed8-fa72cb6226ca",
   "metadata": {},
   "source": [
    "Let's see what a single column's data looks like"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "edb2f992-10c5-4971-af36-9f184d756f11",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1    43360.0\n",
       "2    37285.0\n",
       "3    40598.0\n",
       "4    49675.0\n",
       "5    38491.0\n",
       "Name: mhhi_adj, dtype: float64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "LA_income['mhhi_adj'].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "50223236-3633-4a16-8380-b5f54b8f2f7e",
   "metadata": {},
   "source": [
    "Okay, great! Now, let's look at our data again, what is the mean for median household income adjusted for inflation?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "3c123da1-0359-4d79-bc2a-ad8ecec23847",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "77149.96864111499"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "LA_income['mhhi_adj'].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "860d6dcf-9197-4e31-b003-2bcd07f896cf",
   "metadata": {},
   "source": [
    "Interesting! 77,149.97 is the mean median household income. I hope i can be making that some time soon! One can dream, right?"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ecf74174-a0b7-466a-92ef-a95ec6486104",
   "metadata": {},
   "source": [
    "Now, what does the median for median household income look like?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "e3bff35d-d2ba-4dde-8298-ca3d54734ea5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "71691.0"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "LA_income['mhhi_adj'].median()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3af5daba-a21f-4252-8fd1-39729e5aaa6f",
   "metadata": {},
   "source": [
    "So among our various zip codes, 71,691 is the median household income "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "382ffed5-8524-4a7c-8ce1-0d3db1ffad60",
   "metadata": {},
   "source": [
    "## Let's see those quant. skills again! Where are the stats at?!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "8f90bf4d-9fd5-4f11-a982-36d3ea81d4b1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count       287.000000\n",
       "mean      77149.968641\n",
       "std       30656.774414\n",
       "min       21635.000000\n",
       "25%       53896.500000\n",
       "50%       71691.000000\n",
       "75%       93281.500000\n",
       "max      209531.000000\n",
       "Name: mhhi_adj, dtype: float64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "LA_income['mhhi_adj'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "33804853-6e1a-44d9-85ac-e8bcddc8e37f",
   "metadata": {},
   "source": [
    "Wow! So at the very minimum across all the zip codes in this data set, the median household income for some areas is 21,635 while the maximum some areas report is 209,531. That's such a wide gap!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c12c2183-8672-43ce-a0ba-311a0b02bf60",
   "metadata": {},
   "source": [
    "## Let's see what that looks like on a histogram!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "e9d42c35-72a2-4a7f-881f-9f7e3ffbcea0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Frequency'>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "LA_income['mhhi_adj'].plot.hist(bins=50)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c3b725d-b05b-4001-bbaa-00fde38e1f47",
   "metadata": {},
   "source": [
    "Let's see, the gap is still pretty wide between the minimum amount of median household income reported and the 25th percentile. However, the distance between the maximums median household income and the maximum median household income is significantly larger. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a84dd871-e180-45e0-91d7-a983ab5bb2e6",
   "metadata": {},
   "source": [
    "Let's look at this data as it ascends upward."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "bedced8d-ba51-4ed9-8646-2f55d802e47c",
   "metadata": {},
   "outputs": [],
   "source": [
    "LA_income_sorted = LA_income.sort_values(by='mhhi_adj',ascending = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "63a7a307-0c9c-4fb6-b936-15643518e7ed",
   "metadata": {},
   "source": [
    "What's that look like on the table?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "77a4f2a8-837d-4db2-a7c9-f5df504cbeb8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "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>geoid</th>\n",
       "      <th>mhhi_adj</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>86000US90077</td>\n",
       "      <td>209531.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>86000US90272</td>\n",
       "      <td>192500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>86000US91011</td>\n",
       "      <td>175652.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>238</th>\n",
       "      <td>86000US91436</td>\n",
       "      <td>174085.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>86000US90274</td>\n",
       "      <td>169919.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>86000US91108</td>\n",
       "      <td>165765.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>86000US90094</td>\n",
       "      <td>155417.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>86000US90402</td>\n",
       "      <td>154583.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>86000US90266</td>\n",
       "      <td>153023.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>86000US90265</td>\n",
       "      <td>152378.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            geoid  mhhi_adj\n",
       "63   86000US90077  209531.0\n",
       "94   86000US90272  192500.0\n",
       "171  86000US91011  175652.0\n",
       "238  86000US91436  174085.0\n",
       "95   86000US90274  169919.0\n",
       "185  86000US91108  165765.0\n",
       "67   86000US90094  155417.0\n",
       "110  86000US90402  154583.0\n",
       "92   86000US90266  153023.0\n",
       "91   86000US90265  152378.0"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "LA_income_sorted[['geoid','mhhi_adj']].head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a9916fc-196a-4dd6-9890-e072803d8354",
   "metadata": {},
   "source": [
    "## Perfect! Let's see that plotted now!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "c4b7452c-5c87-45eb-a88b-7b023de31396",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "LA_income_sorted.head(10).plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4c385af-1a3c-4774-95d1-ba318161f0b1",
   "metadata": {},
   "source": [
    "Okay, seems like the corners of this data set seem to have the lowest median household income "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "82950b39-a5b1-4f6a-80ba-99be4db291af",
   "metadata": {},
   "source": [
    "Let's visualize that now!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "da562268-04e8-4b75-833c-36cf7d53584e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "LA_income_sorted.head(100).plot(figsize=(10,10),column='mhhi_adj',legend=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f407143d-8eca-4c28-86c3-c8cb5839aea3",
   "metadata": {},
   "source": [
    "Looks like those zip code closer to the coast and more central in this data set have some of the highest levels of median household income"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "adcc4cec-ac17-41e8-bb43-0053ce03fa53",
   "metadata": {},
   "source": [
    "## Let's plot that in percentiles!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd93556f-74bf-4a8c-94c1-3edf334cf8ef",
   "metadata": {},
   "source": [
    "Next time let's use another data set that might have more values in different columns that we can separate and compare"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "dc9a5504-1a04-4d6c-bf5a-7222e358ac88",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "LA_income.plot(figsize=(12,10),\n",
    "                 column='mhhi_adj',\n",
    "                 legend=True, \n",
    "                 scheme='quantiles')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "02d2c036-7a18-44d0-ab9b-65e0fead1951",
   "metadata": {},
   "source": [
    "Look at that! Seems like the zip codes with the lowest amounts of median household income are concentrated in the center of the map and central to the region. However, there are also two other areas at the far corners that seem to have low amounts of median household income. Looking at this map, I want to see what other methods I can learn or data sets I can use that tell us exactly what zip codes correlate with the percentiles being visualized in this map."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c0aa4c0e-0a7e-4c90-b5a4-01099fef136b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}