Galveston bay.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Hurricane Harvey Data Around Houston\n",
    "Galveston Bay citizens run their own water monitoring:\n",
    "<br>http://gulfcitizenscience.org/gbf_db"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Here's some support links on datetimes in pandas.\n",
    "http://strftime.org/\n",
    "<br>https://stackoverflow.com/questions/26763344/convert-pandas-column-to-datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Section 1: Galveston Bay Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\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>Date</th>\n",
       "      <th>Area</th>\n",
       "      <th>Air Temp (°C)</th>\n",
       "      <th>Water Temp (°C)</th>\n",
       "      <th>Dissolved Oxygen (mg/L)</th>\n",
       "      <th>pH</th>\n",
       "      <th>Salinity (ppt)</th>\n",
       "      <th>Enterococcus</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7/19/2018 10:03 am</td>\n",
       "      <td>Galveston Bay at Shoreacres Pier</td>\n",
       "      <td>27.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>5.6</td>\n",
       "      <td>8.0</td>\n",
       "      <td>14.10</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7/18/2018 8:30 am</td>\n",
       "      <td>Jones Bay at Bayou Vista</td>\n",
       "      <td>28.0</td>\n",
       "      <td>29.5</td>\n",
       "      <td>3.4</td>\n",
       "      <td>8.0</td>\n",
       "      <td>23.60</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7/18/2018 8:12 am</td>\n",
       "      <td>Jones Bay at Tiki Tom's RV Park</td>\n",
       "      <td>28.0</td>\n",
       "      <td>28.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>28.60</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7/17/2018 8:00 am</td>\n",
       "      <td>Clear Lake at Watergate Yachting Center</td>\n",
       "      <td>27.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>8.6</td>\n",
       "      <td>10.95</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Date                                     Area  Air Temp (°C)  \\\n",
       "0  7/19/2018 10:03 am         Galveston Bay at Shoreacres Pier           27.0   \n",
       "1   7/18/2018 8:30 am                 Jones Bay at Bayou Vista           28.0   \n",
       "2   7/18/2018 8:12 am          Jones Bay at Tiki Tom's RV Park           28.0   \n",
       "3   7/17/2018 8:00 am  Clear Lake at Watergate Yachting Center           27.0   \n",
       "\n",
       "   Water Temp (°C)  Dissolved Oxygen (mg/L)   pH  Salinity (ppt)  Enterococcus  \n",
       "0             28.0                      5.6  8.0           14.10           1.0  \n",
       "1             29.5                      3.4  8.0           23.60          20.0  \n",
       "2             28.5                      4.0  8.0           28.60          10.0  \n",
       "3             29.0                      3.8  8.6           10.95           1.0  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bay_data_germs = (pd.read_csv(\"Galveston Bay Foundation Data_20190516.csv\")\n",
    "                  .dropna(how='any') # only keep with enterococcus readings (also keeps highest-quality data)\n",
    "                  .reset_index(inplace = False, drop = True))\n",
    "bay_data_germs.head(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .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>Area</th>\n",
       "      <th>Air Temp (°C)</th>\n",
       "      <th>Water Temp (°C)</th>\n",
       "      <th>Dissolved Oxygen (mg/L)</th>\n",
       "      <th>pH</th>\n",
       "      <th>Salinity (ppt)</th>\n",
       "      <th>Enterococcus</th>\n",
       "      <th>Decimal_Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Galveston Bay at Shoreacres Pier</td>\n",
       "      <td>27.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>5.6</td>\n",
       "      <td>8.0</td>\n",
       "      <td>14.10</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2018.635388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Jones Bay at Bayou Vista</td>\n",
       "      <td>28.0</td>\n",
       "      <td>29.5</td>\n",
       "      <td>3.4</td>\n",
       "      <td>8.0</td>\n",
       "      <td>23.60</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2018.632648</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Jones Bay at Tiki Tom's RV Park</td>\n",
       "      <td>28.0</td>\n",
       "      <td>28.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>28.60</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2018.632648</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Clear Lake at Watergate Yachting Center</td>\n",
       "      <td>27.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>8.6</td>\n",
       "      <td>10.95</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2018.629909</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      Area  Air Temp (°C)  Water Temp (°C)  \\\n",
       "0         Galveston Bay at Shoreacres Pier           27.0             28.0   \n",
       "1                 Jones Bay at Bayou Vista           28.0             29.5   \n",
       "2          Jones Bay at Tiki Tom's RV Park           28.0             28.5   \n",
       "3  Clear Lake at Watergate Yachting Center           27.0             29.0   \n",
       "\n",
       "   Dissolved Oxygen (mg/L)   pH  Salinity (ppt)  Enterococcus  Decimal_Date  \n",
       "0                      5.6  8.0           14.10           1.0   2018.635388  \n",
       "1                      3.4  8.0           23.60          20.0   2018.632648  \n",
       "2                      4.0  8.0           28.60          10.0   2018.632648  \n",
       "3                      3.8  8.6           10.95           1.0   2018.629909  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bay_data_germs['Date'] =  pd.to_datetime(bay_data_germs['Date'])\n",
    "bay_data_germs['Year'] = bay_data_germs['Date'].dt.year\n",
    "bay_data_germs['Month'] = bay_data_germs['Date'].dt.month\n",
    "bay_data_germs['Day'] = bay_data_germs['Date'].dt.day\n",
    "bay_data_germs['Decimal_Date'] = (bay_data_germs['Year'] + \n",
    "                                  bay_data_germs['Month'] / 12 + \n",
    "                                  bay_data_germs['Day'] / 365)\n",
    "bay_data_germs = bay_data_germs[['Area', 'Air Temp (°C)', 'Water Temp (°C)', 'Dissolved Oxygen (mg/L)', \n",
    "                                 'pH', 'Salinity (ppt)', 'Enterococcus', 'Decimal_Date']]\n",
    "bay_data_germs.head(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "plt.plot(bay_data_germs.loc[(bay_data_germs['Decimal_Date'] >= 2017.0) & \n",
    "                            (bay_data_germs['Decimal_Date'] < 2018.0)]['Decimal_Date'],\n",
    "         bay_data_germs.loc[(bay_data_germs['Decimal_Date'] >= 2017.0) & \n",
    "                            (bay_data_germs['Decimal_Date'] < 2018.0)]['Enterococcus'], \n",
    "         label = 'Enterococcus',\n",
    "         linestyle = 'None', marker = '.')\n",
    "plt.plot([2017 + 8/12+30/265 for i in range(2)],\n",
    "         [0, np.max(bay_data_germs.loc[(bay_data_germs['Decimal_Date'] >= 2017.0) & \n",
    "                                       (bay_data_germs['Decimal_Date'] < 2018.0)]['Enterococcus'])],\n",
    "         label = 'Hurricane Harvey',\n",
    "         linestyle = '-', color = 'r')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Enterococcus')\n",
    "plt.title('Fecal Bacteria not apparently trending with hurricane Harvey')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "plt.plot(bay_data_germs['Decimal_Date'], \n",
    "         bay_data_germs['Enterococcus'], \n",
    "         label = 'Enterococcus',\n",
    "         linestyle = 'None', marker = '.')\n",
    "plt.plot([2017 + 8/12+30/265 for i in range(2)],\n",
    "         [0, np.max(bay_data_germs.loc[(bay_data_germs['Decimal_Date'] >= 2017.0) & \n",
    "                                       (bay_data_germs['Decimal_Date'] < 2018.0)]['Enterococcus'])],\n",
    "         label = 'Hurricane Harvey',\n",
    "         linestyle = '-', color = 'r')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Enterococcus')\n",
    "plt.title('Longer-Term Fecal Bacteria Trends: Increase First Half 2018')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "plt.plot(bay_data_germs.loc[(bay_data_germs['Decimal_Date'] >= 2017.0) & \n",
    "                            (bay_data_germs['Decimal_Date'] < 2018.0)]['Decimal_Date'],\n",
    "         bay_data_germs.loc[(bay_data_germs['Decimal_Date'] >= 2017.0) & \n",
    "                            (bay_data_germs['Decimal_Date'] < 2018.0)]['Salinity (ppt)'], \n",
    "         label = 'Salinity (ppt)',\n",
    "         linestyle = 'None', marker = '.')\n",
    "plt.plot([2017 + 8/12+30/265 for i in range(2)],\n",
    "         [0, np.max(bay_data_germs.loc[(bay_data_germs['Decimal_Date'] >= 2017.0) &\n",
    "                                       (bay_data_germs['Decimal_Date'] < 2018.0)]['Salinity (ppt)'])],\n",
    "         label = 'Hurricane Harvey',\n",
    "         linestyle = '-', color = 'r')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Salinity')\n",
    "plt.title('Hurricane Harvey reduced Galveston Bay salinity')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "plt.plot(bay_data_germs.loc[(bay_data_germs['Decimal_Date'] >= 2017.0) & \n",
    "                            (bay_data_germs['Decimal_Date'] < 2018.0)]['Decimal_Date'], \n",
    "         bay_data_germs.loc[(bay_data_germs['Decimal_Date'] >= 2017.0) & \n",
    "                            (bay_data_germs['Decimal_Date'] < 2018.0)]['pH'], \n",
    "         label = 'pH',\n",
    "         linestyle = 'None', marker = '.')\n",
    "plt.plot([2017 + 8/12+30/265 for i in range(2)],\n",
    "         [0, np.max(bay_data_germs.loc[(bay_data_germs['Decimal_Date'] >= 2017.0) &\n",
    "                                       (bay_data_germs['Decimal_Date'] < 2018.0)]['pH'])],\n",
    "         label = 'Hurricane Harvey',\n",
    "         linestyle = '-', color = 'r')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('pH')\n",
    "plt.title('pH')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "plt.plot(bay_data_germs.loc[(bay_data_germs['Decimal_Date'] >= 2017.0) & \n",
    "                            (bay_data_germs['Decimal_Date'] < 2018.0)]['Decimal_Date'], \n",
    "         bay_data_germs.loc[(bay_data_germs['Decimal_Date'] >= 2017.0) & \n",
    "                            (bay_data_germs['Decimal_Date'] < 2018.0)]['Dissolved Oxygen (mg/L)'], \n",
    "         label = 'Dissolved Oxygen',\n",
    "         linestyle = 'None', marker = '.')\n",
    "plt.plot([2017 + 8/12+30/265 for i in range(2)],\n",
    "         [0, np.max(bay_data_germs.loc[(bay_data_germs['Decimal_Date'] >= 2017.0) &\n",
    "                                       (bay_data_germs['Decimal_Date'] < 2018.0)]['Dissolved Oxygen (mg/L)'])],\n",
    "         label = 'Hurricane Harvey',\n",
    "         linestyle = '-', color = 'r')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Dissolved Oxygen (mg/L)')\n",
    "plt.title('Dissolved Oxygen High during Hurricane Harvey')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Dissolved oxygen trends with seasonal temperatures.\n",
    "<br>Gas solubility in liquid decreases with temperature increase (Henry's law)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Section 2: Add rainfall data from Houston Hobby Airport\n",
    "PRCP documentation\n",
    "<br>https://www1.ncdc.noaa.gov/pub/data/cdo/documentation/GHCND_documentation.pdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>STATION</th>\n",
       "      <th>NAME</th>\n",
       "      <th>DATE</th>\n",
       "      <th>PRCP</th>\n",
       "      <th>week_rolling_avg_PRCP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>USW00012918</td>\n",
       "      <td>HOUSTON WILLIAM P HOBBY AIRPORT, TX US</td>\n",
       "      <td>2008-01-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>USW00012918</td>\n",
       "      <td>HOUSTON WILLIAM P HOBBY AIRPORT, TX US</td>\n",
       "      <td>2008-01-02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>USW00012918</td>\n",
       "      <td>HOUSTON WILLIAM P HOBBY AIRPORT, TX US</td>\n",
       "      <td>2008-01-03</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       STATION                                    NAME        DATE  PRCP  \\\n",
       "0  USW00012918  HOUSTON WILLIAM P HOBBY AIRPORT, TX US  2008-01-01   0.0   \n",
       "1  USW00012918  HOUSTON WILLIAM P HOBBY AIRPORT, TX US  2008-01-02   0.0   \n",
       "2  USW00012918  HOUSTON WILLIAM P HOBBY AIRPORT, TX US  2008-01-03   0.0   \n",
       "\n",
       "   week_rolling_avg_PRCP  \n",
       "0                    0.0  \n",
       "1                    0.0  \n",
       "2                    0.0  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rain_data = pd.read_csv('hobby weather 1.csv')\n",
    "rain_data['week_rolling_avg_PRCP'] = rain_data['PRCP'].rolling(window = 7,\n",
    "                                                               min_periods = 1).mean()\n",
    " \n",
    "rain_data.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12.07"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.max(rain_data['PRCP'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>Decimal_Date</th>\n",
       "      <th>PRCP</th>\n",
       "      <th>week_rolling_avg_PRCP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2008.086073</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2008.088813</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2008.091553</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2008.094292</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Decimal_Date  PRCP  week_rolling_avg_PRCP\n",
       "0   2008.086073   0.0                    0.0\n",
       "1   2008.088813   0.0                    0.0\n",
       "2   2008.091553   0.0                    0.0\n",
       "3   2008.094292   0.0                    0.0"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rain_data = rain_data[['DATE', 'PRCP', 'week_rolling_avg_PRCP']]\n",
    "rain_data['DATE'] = pd.to_datetime(rain_data['DATE'])\n",
    "\n",
    "rain_data['Year'] = rain_data['DATE'].dt.year\n",
    "rain_data['Month'] = rain_data['DATE'].dt.month\n",
    "rain_data['Day'] = rain_data['DATE'].dt.day\n",
    "rain_data['Decimal_Date'] = rain_data['Year'] + rain_data['Month'] / 12 + rain_data['Day'] / 365\n",
    "rain_data = rain_data[['Decimal_Date', 'PRCP', 'week_rolling_avg_PRCP']]\n",
    "\n",
    "rain_data.head(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>Area</th>\n",
       "      <th>Air Temp (°C)</th>\n",
       "      <th>Water Temp (°C)</th>\n",
       "      <th>Dissolved Oxygen (mg/L)</th>\n",
       "      <th>pH</th>\n",
       "      <th>Salinity (ppt)</th>\n",
       "      <th>Enterococcus</th>\n",
       "      <th>Decimal_Date</th>\n",
       "      <th>PRCP</th>\n",
       "      <th>week_rolling_avg_PRCP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Galveston Bay at Shoreacres Pier</td>\n",
       "      <td>27.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>5.6</td>\n",
       "      <td>8.0</td>\n",
       "      <td>14.10</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2018.635388</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Jones Bay at Bayou Vista</td>\n",
       "      <td>28.0</td>\n",
       "      <td>29.5</td>\n",
       "      <td>3.4</td>\n",
       "      <td>8.0</td>\n",
       "      <td>23.60</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2018.632648</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Jones Bay at Tiki Tom's RV Park</td>\n",
       "      <td>28.0</td>\n",
       "      <td>28.5</td>\n",
       "      <td>4.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>28.60</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2018.632648</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Clear Lake at Watergate Yachting Center</td>\n",
       "      <td>27.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>8.6</td>\n",
       "      <td>10.95</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2018.629909</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      Area  Air Temp (°C)  Water Temp (°C)  \\\n",
       "0         Galveston Bay at Shoreacres Pier           27.0             28.0   \n",
       "1                 Jones Bay at Bayou Vista           28.0             29.5   \n",
       "2          Jones Bay at Tiki Tom's RV Park           28.0             28.5   \n",
       "3  Clear Lake at Watergate Yachting Center           27.0             29.0   \n",
       "\n",
       "   Dissolved Oxygen (mg/L)   pH  Salinity (ppt)  Enterococcus  Decimal_Date  \\\n",
       "0                      5.6  8.0           14.10           1.0   2018.635388   \n",
       "1                      3.4  8.0           23.60          20.0   2018.632648   \n",
       "2                      4.0  8.0           28.60          10.0   2018.632648   \n",
       "3                      3.8  8.6           10.95           1.0   2018.629909   \n",
       "\n",
       "   PRCP  week_rolling_avg_PRCP  \n",
       "0   0.0                    0.0  \n",
       "1   0.0                    0.0  \n",
       "2   0.0                    0.0  \n",
       "3   0.0                    0.0  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bay_data_germs = bay_data_germs.join(rain_data.set_index('Decimal_Date'), on = 'Decimal_Date')\n",
    "bay_data_germs.head(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "plt.plot([2017 + 8/12+30/265 for i in range(2)],\n",
    "         [0, np.max(bay_data_germs.loc[(bay_data_germs['Decimal_Date'] >= 2017.0) &\n",
    "                                       (bay_data_germs['Decimal_Date'] < 2018.0)]['PRCP'])],\n",
    "         linestyle = '-', color = 'r',\n",
    "        label = 'Precipitation')\n",
    "plt.plot(bay_data_germs.loc[(bay_data_germs['Decimal_Date'] >= 2017.0) & \n",
    "                            (bay_data_germs['Decimal_Date'] < 2018.0)]['Decimal_Date'],\n",
    "         bay_data_germs.loc[(bay_data_germs['Decimal_Date'] >= 2017.0) & \n",
    "                            (bay_data_germs['Decimal_Date'] < 2018.0)]['PRCP'],\n",
    "        linestyle = 'None', marker = '.', color = 'g',\n",
    "        label = 'Hurricane Harvey')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Inches per day')\n",
    "plt.title('Houston Hobby Precipitation not Catching Hurricane Harvey')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Does a weekly average feature better expose precipitation around Hurricane Harvey?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "plt.plot([2017 + 8/12+30/265 for i in range(2)],\n",
    "         [0, np.max(bay_data_germs.loc[(bay_data_germs['Decimal_Date'] >= 2017.0) & \n",
    "                                       (bay_data_germs['Decimal_Date'] < 2018.0)]['week_rolling_avg_PRCP'])],\n",
    "         linestyle = '-', color = 'r')\n",
    "plt.plot(bay_data_germs.loc[(bay_data_germs['Decimal_Date'] >= 2017.0) & \n",
    "                            (bay_data_germs['Decimal_Date'] < 2018.0)]['Decimal_Date'],\n",
    "         (bay_data_germs\n",
    "          .loc[(bay_data_germs['Decimal_Date'] >= 2017.0) & \n",
    "               (bay_data_germs['Decimal_Date'] < 2018.0)]\n",
    "          ['week_rolling_avg_PRCP']),\n",
    "        linestyle = 'None', marker = '.', color = 'g')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Inches per Day')\n",
    "plt.title('Houston Hobby Rolling Weekly Avg Daily Precipitation')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Section 3: Buffalo Bayou water levels\n",
    "Data source:\n",
    "<br>https://waterdata.usgs.gov/usa/nwis/uv?site_no=08073700\n",
    "<br>TS   parameter     Description\n",
    "<br>        140428       00060     Discharge, cubic feet per second\n",
    "<br>        140429       00065     Gage height, feet, [Primary Sensor]\n",
    "\n",
    "Support link: groupby's in pandas\n",
    "<br>https://www.shanelynn.ie/summarising-aggregation-and-grouping-data-in-python-pandas/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>Date</th>\n",
       "      <th>Area</th>\n",
       "      <th>Air Temp (°C)</th>\n",
       "      <th>Water Temp (°C)</th>\n",
       "      <th>Dissolved Oxygen (mg/L)</th>\n",
       "      <th>pH</th>\n",
       "      <th>Salinity (ppt)</th>\n",
       "      <th>Enterococcus</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7/25/2018 12:24 pm</td>\n",
       "      <td>Clear Lake at Marina Del Sol</td>\n",
       "      <td>32.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>6.1</td>\n",
       "      <td>8.5</td>\n",
       "      <td>12.4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7/25/2018 8:55 am</td>\n",
       "      <td>Galveston Bay at Bayshore Park</td>\n",
       "      <td>29.5</td>\n",
       "      <td>27.5</td>\n",
       "      <td>4.1</td>\n",
       "      <td>8.3</td>\n",
       "      <td>16.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7/25/2018 8:55 am</td>\n",
       "      <td>Galveston Bay at Bayshore Park</td>\n",
       "      <td>29.5</td>\n",
       "      <td>27.5</td>\n",
       "      <td>4.1</td>\n",
       "      <td>8.3</td>\n",
       "      <td>16.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7/20/2018 4:55 pm</td>\n",
       "      <td>Clear Lake at Nassau Bay Upper Bay Road</td>\n",
       "      <td>38.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>9.6</td>\n",
       "      <td>8.7</td>\n",
       "      <td>5.2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Date                                     Area  Air Temp (°C)  \\\n",
       "0  7/25/2018 12:24 pm             Clear Lake at Marina Del Sol           32.0   \n",
       "1   7/25/2018 8:55 am           Galveston Bay at Bayshore Park           29.5   \n",
       "2   7/25/2018 8:55 am           Galveston Bay at Bayshore Park           29.5   \n",
       "3   7/20/2018 4:55 pm  Clear Lake at Nassau Bay Upper Bay Road           38.0   \n",
       "\n",
       "   Water Temp (°C)  Dissolved Oxygen (mg/L)   pH  Salinity (ppt)  Enterococcus  \n",
       "0             31.0                      6.1  8.5            12.4           NaN  \n",
       "1             27.5                      4.1  8.3            16.5           NaN  \n",
       "2             27.5                      4.1  8.3            16.5           NaN  \n",
       "3             34.0                      9.6  8.7             5.2           NaN  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### get the bay data for a northern location in the bay\n",
    "bay_data_buff_bayou = (pd.read_csv(\"Galveston Bay Foundation Data_20190516.csv\")\n",
    "                       .reset_index(inplace = False, drop = True))\n",
    "bay_data_buff_bayou.head(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "#sorted(list(bay_data_buff_bayou['Area'].unique()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "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",
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       "    }\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>Area</th>\n",
       "      <th>Air Temp (°C)</th>\n",
       "      <th>Water Temp (°C)</th>\n",
       "      <th>Dissolved Oxygen (mg/L)</th>\n",
       "      <th>pH</th>\n",
       "      <th>Salinity (ppt)</th>\n",
       "      <th>Enterococcus</th>\n",
       "      <th>Decimal_Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Clear Lake at Marina Del Sol</td>\n",
       "      <td>32.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>6.1</td>\n",
       "      <td>8.5</td>\n",
       "      <td>12.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2018.651826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Galveston Bay at Bayshore Park</td>\n",
       "      <td>29.5</td>\n",
       "      <td>27.5</td>\n",
       "      <td>4.1</td>\n",
       "      <td>8.3</td>\n",
       "      <td>16.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2018.651826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Galveston Bay at Bayshore Park</td>\n",
       "      <td>29.5</td>\n",
       "      <td>27.5</td>\n",
       "      <td>4.1</td>\n",
       "      <td>8.3</td>\n",
       "      <td>16.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2018.651826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Clear Lake at Nassau Bay Upper Bay Road</td>\n",
       "      <td>38.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>9.6</td>\n",
       "      <td>8.7</td>\n",
       "      <td>5.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2018.638128</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      Area  Air Temp (°C)  Water Temp (°C)  \\\n",
       "0             Clear Lake at Marina Del Sol           32.0             31.0   \n",
       "1           Galveston Bay at Bayshore Park           29.5             27.5   \n",
       "2           Galveston Bay at Bayshore Park           29.5             27.5   \n",
       "3  Clear Lake at Nassau Bay Upper Bay Road           38.0             34.0   \n",
       "\n",
       "   Dissolved Oxygen (mg/L)   pH  Salinity (ppt)  Enterococcus  Decimal_Date  \n",
       "0                      6.1  8.5            12.4           NaN   2018.651826  \n",
       "1                      4.1  8.3            16.5           NaN   2018.651826  \n",
       "2                      4.1  8.3            16.5           NaN   2018.651826  \n",
       "3                      9.6  8.7             5.2           NaN   2018.638128  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bay_data_buff_bayou['Date'] =  pd.to_datetime(bay_data_buff_bayou['Date'])\n",
    "bay_data_buff_bayou['Year'] = bay_data_buff_bayou['Date'].dt.year\n",
    "bay_data_buff_bayou['Month'] = bay_data_buff_bayou['Date'].dt.month\n",
    "bay_data_buff_bayou['Day'] = bay_data_buff_bayou['Date'].dt.day\n",
    "bay_data_buff_bayou['Decimal_Date'] = (bay_data_buff_bayou['Year'] + \n",
    "                                       bay_data_buff_bayou['Month'] / 12 + \n",
    "                                       bay_data_buff_bayou['Day'] / 365)\n",
    "bay_data_buff_bayou = bay_data_buff_bayou[['Area', 'Air Temp (°C)', 'Water Temp (°C)', 'Dissolved Oxygen (mg/L)', \n",
    "                                           'pH', 'Salinity (ppt)', 'Enterococcus', 'Decimal_Date']]\n",
    "bay_data_buff_bayou.head(4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Remove bay samples far from buffalo bayou:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "bay_data_buff_bayou = (bay_data_buff_bayou[bay_data_buff_bayou['Area']\n",
    "                                           .str.contains(\"Christmas|East Bay|\\\n",
    "                                                         Eckert|Jones|West Bay|Trinity|Anahuac|\\\n",
    "                                                         Highland Bayou|Offatt|\\\n",
    "                                                         Swan\")==False])\n",
    "bay_data_buff_bayou = (bay_data_buff_bayou[bay_data_buff_bayou['Area']\n",
    "                                           .str.contains(\"Highland Bayou|Offatt|Swan Lake\")==False])\n",
    "#sorted(list(bay_data_buff_bayou['Area'].unique()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>Discharge_cfpd</th>\n",
       "      <th>Gage_ht_ft</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Decimal_Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2009.086073</th>\n",
       "      <td>94.188542</td>\n",
       "      <td>28.486250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009.088813</th>\n",
       "      <td>91.780208</td>\n",
       "      <td>28.454583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009.091553</th>\n",
       "      <td>88.593750</td>\n",
       "      <td>28.412292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009.094292</th>\n",
       "      <td>87.441667</td>\n",
       "      <td>28.396146</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Discharge_cfpd  Gage_ht_ft\n",
       "Decimal_Date                            \n",
       "2009.086073        94.188542   28.486250\n",
       "2009.088813        91.780208   28.454583\n",
       "2009.091553        88.593750   28.412292\n",
       "2009.094292        87.441667   28.396146"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "buff_bayou = pd.read_csv('buffalo bayou 1.txt', sep = '\\t', skiprows = [1])\n",
    "buff_bayou.rename(columns={'140428_00060': 'Discharge_cfpd', '140429_00065': 'Gage_ht_ft'}, inplace=True)\n",
    "\n",
    "buff_bayou['datetime'] = pd.to_datetime(buff_bayou['datetime'])\n",
    "\n",
    "buff_bayou['Year'] = buff_bayou['datetime'].dt.year\n",
    "buff_bayou['Month'] = buff_bayou['datetime'].dt.month\n",
    "buff_bayou['Day'] = buff_bayou['datetime'].dt.day\n",
    "buff_bayou['Decimal_Date'] = buff_bayou['Year'] + buff_bayou['Month'] / 12 + buff_bayou['Day'] / 365\n",
    "\n",
    "buff_bayou = buff_bayou[['Decimal_Date', 'Discharge_cfpd', 'Gage_ht_ft']]\n",
    "\n",
    "buff_bayou = buff_bayou.groupby('Decimal_Date')[['Discharge_cfpd', 'Gage_ht_ft']].mean()\n",
    "\n",
    "buff_bayou.head(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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>Area</th>\n",
       "      <th>Air Temp (°C)</th>\n",
       "      <th>Water Temp (°C)</th>\n",
       "      <th>Dissolved Oxygen (mg/L)</th>\n",
       "      <th>pH</th>\n",
       "      <th>Salinity (ppt)</th>\n",
       "      <th>Enterococcus</th>\n",
       "      <th>Decimal_Date</th>\n",
       "      <th>Discharge_cfpd</th>\n",
       "      <th>Gage_ht_ft</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Clear Lake at Marina Del Sol</td>\n",
       "      <td>32.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>6.1</td>\n",
       "      <td>8.5</td>\n",
       "      <td>12.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2018.651826</td>\n",
       "      <td>96.297917</td>\n",
       "      <td>28.021042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Galveston Bay at Bayshore Park</td>\n",
       "      <td>29.5</td>\n",
       "      <td>27.5</td>\n",
       "      <td>4.1</td>\n",
       "      <td>8.3</td>\n",
       "      <td>16.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2018.651826</td>\n",
       "      <td>96.297917</td>\n",
       "      <td>28.021042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Galveston Bay at Bayshore Park</td>\n",
       "      <td>29.5</td>\n",
       "      <td>27.5</td>\n",
       "      <td>4.1</td>\n",
       "      <td>8.3</td>\n",
       "      <td>16.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2018.651826</td>\n",
       "      <td>96.297917</td>\n",
       "      <td>28.021042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Clear Lake at Nassau Bay Upper Bay Road</td>\n",
       "      <td>38.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>9.6</td>\n",
       "      <td>8.7</td>\n",
       "      <td>5.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2018.638128</td>\n",
       "      <td>108.083333</td>\n",
       "      <td>28.157500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      Area  Air Temp (°C)  Water Temp (°C)  \\\n",
       "0             Clear Lake at Marina Del Sol           32.0             31.0   \n",
       "1           Galveston Bay at Bayshore Park           29.5             27.5   \n",
       "2           Galveston Bay at Bayshore Park           29.5             27.5   \n",
       "3  Clear Lake at Nassau Bay Upper Bay Road           38.0             34.0   \n",
       "\n",
       "   Dissolved Oxygen (mg/L)   pH  Salinity (ppt)  Enterococcus  Decimal_Date  \\\n",
       "0                      6.1  8.5            12.4           NaN   2018.651826   \n",
       "1                      4.1  8.3            16.5           NaN   2018.651826   \n",
       "2                      4.1  8.3            16.5           NaN   2018.651826   \n",
       "3                      9.6  8.7             5.2           NaN   2018.638128   \n",
       "\n",
       "   Discharge_cfpd  Gage_ht_ft  \n",
       "0       96.297917   28.021042  \n",
       "1       96.297917   28.021042  \n",
       "2       96.297917   28.021042  \n",
       "3      108.083333   28.157500  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bay_data_buff_bayou = bay_data_buff_bayou.join(buff_bayou, on = 'Decimal_Date')\n",
    "bay_data_buff_bayou.head(4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Buffalo Bayou gauge does a good job of capturing Hurricane Harvey."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "plt.plot([2017 + 8/12+30/265 for i in range(2)],\n",
    "         [0, np.max(bay_data_buff_bayou.loc[(bay_data_buff_bayou['Decimal_Date'] >= 2017.0) & \n",
    "                                            (bay_data_buff_bayou['Decimal_Date'] < 2018.0)]['Discharge_cfpd'])],\n",
    "         linestyle = '-', color = 'r')\n",
    "plt.plot(bay_data_buff_bayou.loc[(bay_data_buff_bayou['Decimal_Date'] >= 2017.0) & \n",
    "                                 (bay_data_buff_bayou['Decimal_Date'] < 2018.0)]['Decimal_Date'],\n",
    "         (bay_data_buff_bayou\n",
    "          .loc[(bay_data_buff_bayou['Decimal_Date'] >= 2017.0) & \n",
    "               (bay_data_buff_bayou['Decimal_Date'] < 2018.0)]\n",
    "          ['Discharge_cfpd']),\n",
    "        linestyle = 'None', marker = '.', color = 'g',\n",
    "        label = 'Hurricane Harvey')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Discharge_cfpd')\n",
    "plt.title('Buffalo Bayou Discharge Volume CF per Day')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "plt.plot([2017 + 8/12+30/265 for i in range(2)],\n",
    "         [0, np.max(bay_data_buff_bayou.loc[(bay_data_buff_bayou['Decimal_Date'] >= 2017.0) &\n",
    "                                            (bay_data_buff_bayou['Decimal_Date'] < 2018.0)]['Gage_ht_ft'])],\n",
    "         linestyle = '-', color = 'r')\n",
    "plt.plot(bay_data_buff_bayou.loc[(bay_data_buff_bayou['Decimal_Date'] >= 2017.0) & \n",
    "                                 (bay_data_buff_bayou['Decimal_Date'] < 2018.0)]['Decimal_Date'],\n",
    "         (bay_data_buff_bayou\n",
    "          .loc[(bay_data_buff_bayou['Decimal_Date'] >= 2017.0) & \n",
    "               (bay_data_buff_bayou['Decimal_Date'] < 2018.0)]\n",
    "          ['Gage_ht_ft']),\n",
    "        linestyle = 'None', marker = '.', color = 'g',\n",
    "        label = 'Hurricane Harvey')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Gage_ht_ft')\n",
    "plt.title('Buffalo Bayou Gage Height Feet')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Salinity and gauge data both correlate with Hurricane Harvey.\n",
    "<br>Crossplot those features."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "plt.plot((bay_data_buff_bayou.loc[(bay_data_buff_bayou['Decimal_Date'] >= 2017.0) & \n",
    "                                  (bay_data_buff_bayou['Decimal_Date'] < 2018.0)]\n",
    "          ['Salinity (ppt)']),\n",
    "         (bay_data_buff_bayou\n",
    "          .loc[(bay_data_buff_bayou['Decimal_Date'] >= 2017.0) & \n",
    "               (bay_data_buff_bayou['Decimal_Date'] < 2018.0)]\n",
    "          ['Gage_ht_ft']),\n",
    "        linestyle = 'None', marker = '.', color = 'g')\n",
    "plt.xlabel('Salinity')\n",
    "plt.ylabel('Gage_ht_ft')\n",
    "plt.title('Buffalo Bayou Gage Height vs. Salinity Trend')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "plt.plot((bay_data_buff_bayou.loc[(bay_data_buff_bayou['Decimal_Date'] >= 2017.0) & \n",
    "                                  (bay_data_buff_bayou['Decimal_Date'] < 2018.0)]\n",
    "          ['Salinity (ppt)']),\n",
    "         (bay_data_buff_bayou\n",
    "          .loc[(bay_data_buff_bayou['Decimal_Date'] >= 2017.0) & \n",
    "               (bay_data_buff_bayou['Decimal_Date'] < 2018.0)]\n",
    "          ['Discharge_cfpd']),\n",
    "        linestyle = 'None', marker = '.', color = 'g')\n",
    "plt.xlabel('Salinity')\n",
    "plt.ylabel('Discharge_cfpd')\n",
    "plt.title('Buffalo Bayou Discharge Rate vs. Salinity Trend')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Not all, but some Galveston Bay sampling areas correlate to buffalo bayou discharge rates.\n",
    "<br>Identify sampling locations where data correlate:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Clear Lake at 18 Waterford Oak Lane',\n",
       " 'Clear Lake at Blue Dolphin Yachting Center',\n",
       " 'Clear Lake at Clear Lake Park Pier',\n",
       " 'Clear Lake at Lakewood Yacht Club',\n",
       " 'Clear Lake at Nassau Bay Upper Bay Road',\n",
       " 'Clear Lake at Sea Cove Ct',\n",
       " 'Clear Lake at South Shore Harbor',\n",
       " 'Clear Lake at Taylor Lake Entrance and Nasa Road',\n",
       " 'Clear Lake at Waterford Harbor Marina',\n",
       " 'Clear Lake at Watergate Yachting Center',\n",
       " 'Galveston Bay at 1109 6th St. San Leon',\n",
       " 'Galveston Bay at 3903 Bayshore Bacliff',\n",
       " 'Galveston Bay at Pine Gully Park',\n",
       " 'Galveston Bay at Seascape Pier',\n",
       " 'Galveston Bay at Shoreacres Pier',\n",
       " 'Galveston Bay at Todville Road',\n",
       " 'Galveston Bay at Topwater Grill',\n",
       " 'Moses Lake at Texas City Prairie Preserve']"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(bay_data_buff_bayou.loc[(bay_data_buff_bayou['Gage_ht_ft'] > 55) & \n",
    "                               (bay_data_buff_bayou['Salinity (ppt)'] < 5)]['Area'].unique())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "List of correlating locations (and Buffalo Bayou gauge location) on google maps:\n",
    "<br>https://goo.gl/maps/EqNykH7SuF6UE5yC6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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