Demo_plot_RDG_Ian.ipynb

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   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d8f219b0-3f05-4388-8981-b3922464b643",
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   "source": [
    "### Water-level data from SW Florida during Ian from USGS  \n",
    "\n",
    "This notebook demos reading in the tab-delimited water-level data from four files using Pandas.  \n",
    "\n",
    "There are also some data available from the Keys, but they are not included here.  \n",
    "\n",
    "All data were downloaded using the Flood Event Viewr (https://stn.wim.usgs.gov/fev/#2022Ian) to open the legacy web page (e.g. https://waterdata.usgs.gov/nwis/uv?site_no=275840082495601&legacy=1) on 1/18/2023.  \n",
    "\n",
    "Tide guage and wave data  \n",
    "NWIS SITE 02293202  \n",
    "CALOOSAHATCHEE RIVER AT FORT MYERS FL  \n",
    "\n",
    "62620 Elevation, ocean/est, NAVD88 [Mean level]\t2022-09-26 \t2022-10-03  \n",
    "62622 Elevation, ocean/est, NAVD88 [Maximum level]\t2022-09-26 \t2022-10-03  \n",
    "62622 Elevation, ocean/est, NAVD88 [Mean level]\t2022-09-26 \t2022-10-03  \n",
    "62622 Elevation, ocean/est, NAVD88 [Minimum level]\t2022-09-26 \t2022-10-03  \n",
    "72286 Significant wave ht\t2022-09-26 \t2022-10-03  \n",
    "72287 Significant wave pd [TPEAK]\t2022-09-26 \t2022-10-03  \n",
    "\n",
    "RDGs  \n",
    "Site 275840082495601  \n",
    "Gulf of Mexico at Clearwater Beach, FL  \n",
    "\n",
    "Site 273511082371300  \n",
    "Tampa Bay at Skyway Bridge near Terraceia, FL  \n",
    "\n",
    "Site 271956082345200  \n",
    "New Pass at Lido Key near Sarasota, FL  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ad58fdc3-9922-4a53-891f-682d804aa40e",
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   "outputs": [],
   "source": [
    "data_dir = r'/vortexfs1/home/csherwood/proj/NOPP/data/'\n",
    "ftmyers = 'USGS_02293202_Caloosahatchee'\n",
    "tbay = 'USGS_273511082371300_Tampa_Bay'\n",
    "clear = 'USGS_275840082495601_Clearwater'\n",
    "npass = 'USGS_271956082345200_New_Pass'"
   ]
  },
  {
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   "execution_count": 3,
   "id": "546bd8d0-f471-4af0-95c2-e23601108da3",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Agency</th>\n",
       "      <th>Site</th>\n",
       "      <th>Date</th>\n",
       "      <th>Time</th>\n",
       "      <th>TZ</th>\n",
       "      <th>Elev ft</th>\n",
       "      <th>Approved</th>\n",
       "      <th>dt</th>\n",
       "      <th>Elev (m)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>USGS</td>\n",
       "      <td>2293202</td>\n",
       "      <td>2022-09-24</td>\n",
       "      <td>01:00</td>\n",
       "      <td>EDT</td>\n",
       "      <td>0.47</td>\n",
       "      <td>A</td>\n",
       "      <td>2022-09-24 01:00:00+04:00</td>\n",
       "      <td>0.143256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>USGS</td>\n",
       "      <td>2293202</td>\n",
       "      <td>2022-09-24</td>\n",
       "      <td>01:15</td>\n",
       "      <td>EDT</td>\n",
       "      <td>0.53</td>\n",
       "      <td>A</td>\n",
       "      <td>2022-09-24 01:15:00+04:00</td>\n",
       "      <td>0.161544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>USGS</td>\n",
       "      <td>2293202</td>\n",
       "      <td>2022-09-24</td>\n",
       "      <td>01:30</td>\n",
       "      <td>EDT</td>\n",
       "      <td>0.57</td>\n",
       "      <td>A</td>\n",
       "      <td>2022-09-24 01:30:00+04:00</td>\n",
       "      <td>0.173736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>USGS</td>\n",
       "      <td>2293202</td>\n",
       "      <td>2022-09-24</td>\n",
       "      <td>01:45</td>\n",
       "      <td>EDT</td>\n",
       "      <td>0.65</td>\n",
       "      <td>A</td>\n",
       "      <td>2022-09-24 01:45:00+04:00</td>\n",
       "      <td>0.198120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>USGS</td>\n",
       "      <td>2293202</td>\n",
       "      <td>2022-09-24</td>\n",
       "      <td>02:00</td>\n",
       "      <td>EDT</td>\n",
       "      <td>0.68</td>\n",
       "      <td>A</td>\n",
       "      <td>2022-09-24 02:00:00+04:00</td>\n",
       "      <td>0.207264</td>\n",
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       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>759</th>\n",
       "      <td>USGS</td>\n",
       "      <td>2293202</td>\n",
       "      <td>2022-10-01</td>\n",
       "      <td>22:45</td>\n",
       "      <td>EDT</td>\n",
       "      <td>1.18</td>\n",
       "      <td>A</td>\n",
       "      <td>2022-10-01 22:45:00+04:00</td>\n",
       "      <td>0.359664</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>760</th>\n",
       "      <td>USGS</td>\n",
       "      <td>2293202</td>\n",
       "      <td>2022-10-01</td>\n",
       "      <td>23:00</td>\n",
       "      <td>EDT</td>\n",
       "      <td>1.19</td>\n",
       "      <td>A</td>\n",
       "      <td>2022-10-01 23:00:00+04:00</td>\n",
       "      <td>0.362712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>761</th>\n",
       "      <td>USGS</td>\n",
       "      <td>2293202</td>\n",
       "      <td>2022-10-01</td>\n",
       "      <td>23:15</td>\n",
       "      <td>EDT</td>\n",
       "      <td>1.20</td>\n",
       "      <td>A</td>\n",
       "      <td>2022-10-01 23:15:00+04:00</td>\n",
       "      <td>0.365760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>762</th>\n",
       "      <td>USGS</td>\n",
       "      <td>2293202</td>\n",
       "      <td>2022-10-01</td>\n",
       "      <td>23:30</td>\n",
       "      <td>EDT</td>\n",
       "      <td>1.17</td>\n",
       "      <td>A</td>\n",
       "      <td>2022-10-01 23:30:00+04:00</td>\n",
       "      <td>0.356616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>763</th>\n",
       "      <td>USGS</td>\n",
       "      <td>2293202</td>\n",
       "      <td>2022-10-01</td>\n",
       "      <td>23:45</td>\n",
       "      <td>EDT</td>\n",
       "      <td>1.14</td>\n",
       "      <td>A</td>\n",
       "      <td>2022-10-01 23:45:00+04:00</td>\n",
       "      <td>0.347472</td>\n",
       "    </tr>\n",
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       "<p>764 rows × 9 columns</p>\n",
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       "    Agency     Site        Date   Time   TZ  Elev ft Approved  \\\n",
       "0     USGS  2293202  2022-09-24  01:00  EDT     0.47        A   \n",
       "1     USGS  2293202  2022-09-24  01:15  EDT     0.53        A   \n",
       "2     USGS  2293202  2022-09-24  01:30  EDT     0.57        A   \n",
       "3     USGS  2293202  2022-09-24  01:45  EDT     0.65        A   \n",
       "4     USGS  2293202  2022-09-24  02:00  EDT     0.68        A   \n",
       "..     ...      ...         ...    ...  ...      ...      ...   \n",
       "759   USGS  2293202  2022-10-01  22:45  EDT     1.18        A   \n",
       "760   USGS  2293202  2022-10-01  23:00  EDT     1.19        A   \n",
       "761   USGS  2293202  2022-10-01  23:15  EDT     1.20        A   \n",
       "762   USGS  2293202  2022-10-01  23:30  EDT     1.17        A   \n",
       "763   USGS  2293202  2022-10-01  23:45  EDT     1.14        A   \n",
       "\n",
       "                           dt  Elev (m)  \n",
       "0   2022-09-24 01:00:00+04:00  0.143256  \n",
       "1   2022-09-24 01:15:00+04:00  0.161544  \n",
       "2   2022-09-24 01:30:00+04:00  0.173736  \n",
       "3   2022-09-24 01:45:00+04:00  0.198120  \n",
       "4   2022-09-24 02:00:00+04:00  0.207264  \n",
       "..                        ...       ...  \n",
       "759 2022-10-01 22:45:00+04:00  0.359664  \n",
       "760 2022-10-01 23:00:00+04:00  0.362712  \n",
       "761 2022-10-01 23:15:00+04:00  0.365760  \n",
       "762 2022-10-01 23:30:00+04:00  0.356616  \n",
       "763 2022-10-01 23:45:00+04:00  0.347472  \n",
       "\n",
       "[764 rows x 9 columns]"
      ]
     },
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   ],
   "source": [
    "col_names = ['Agency','Site','Date','Time','TZ','Elev ft','Approved'] \n",
    "df_fm = pd.read_csv( data_dir + ftmyers + '.txt', skiprows = 28, header=None, names = col_names, delim_whitespace=True )\n",
    "df_fm['dt'] = pd.to_datetime( df_fm['Date'].astype(str) + ' ' + df_fm['Time'].astype(str) + ' +0400' )\n",
    "df_fm['Elev (m)'] = df_fm['Elev ft'].values*.3048\n",
    "df_fm"
   ]
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       "      <th>Site No</th>\n",
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       "      <th>Time</th>\n",
       "      <th>TZ</th>\n",
       "      <th>Elev ft</th>\n",
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       "      <th>0</th>\n",
       "      <td>USGS</td>\n",
       "      <td>271956082345200</td>\n",
       "      <td>2022-09-24</td>\n",
       "      <td>10:45</td>\n",
       "      <td>EDT</td>\n",
       "      <td>1.21</td>\n",
       "      <td>A</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>USGS</td>\n",
       "      <td>271956082345200</td>\n",
       "      <td>2022-09-24</td>\n",
       "      <td>11:00</td>\n",
       "      <td>EDT</td>\n",
       "      <td>1.27</td>\n",
       "      <td>A</td>\n",
       "      <td>2022-09-24 11:00:00+04:00</td>\n",
       "      <td>0.387096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>USGS</td>\n",
       "      <td>271956082345200</td>\n",
       "      <td>2022-09-24</td>\n",
       "      <td>11:15</td>\n",
       "      <td>EDT</td>\n",
       "      <td>1.34</td>\n",
       "      <td>A</td>\n",
       "      <td>2022-09-24 11:15:00+04:00</td>\n",
       "      <td>0.408432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>USGS</td>\n",
       "      <td>271956082345200</td>\n",
       "      <td>2022-09-24</td>\n",
       "      <td>11:30</td>\n",
       "      <td>EDT</td>\n",
       "      <td>1.38</td>\n",
       "      <td>A</td>\n",
       "      <td>2022-09-24 11:30:00+04:00</td>\n",
       "      <td>0.420624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>USGS</td>\n",
       "      <td>271956082345200</td>\n",
       "      <td>2022-09-24</td>\n",
       "      <td>11:45</td>\n",
       "      <td>EDT</td>\n",
       "      <td>1.41</td>\n",
       "      <td>A</td>\n",
       "      <td>2022-09-24 11:45:00+04:00</td>\n",
       "      <td>0.429768</td>\n",
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       "    <tr>\n",
       "      <th>667</th>\n",
       "      <td>USGS</td>\n",
       "      <td>271956082345200</td>\n",
       "      <td>2022-10-01</td>\n",
       "      <td>09:30</td>\n",
       "      <td>EDT</td>\n",
       "      <td>-0.54</td>\n",
       "      <td>A</td>\n",
       "      <td>2022-10-01 09:30:00+04:00</td>\n",
       "      <td>-0.164592</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>668</th>\n",
       "      <td>USGS</td>\n",
       "      <td>271956082345200</td>\n",
       "      <td>2022-10-01</td>\n",
       "      <td>09:45</td>\n",
       "      <td>EDT</td>\n",
       "      <td>-0.61</td>\n",
       "      <td>A</td>\n",
       "      <td>2022-10-01 09:45:00+04:00</td>\n",
       "      <td>-0.185928</td>\n",
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       "    <tr>\n",
       "      <th>669</th>\n",
       "      <td>USGS</td>\n",
       "      <td>271956082345200</td>\n",
       "      <td>2022-10-01</td>\n",
       "      <td>10:00</td>\n",
       "      <td>EDT</td>\n",
       "      <td>-0.67</td>\n",
       "      <td>A</td>\n",
       "      <td>2022-10-01 10:00:00+04:00</td>\n",
       "      <td>-0.204216</td>\n",
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       "    <tr>\n",
       "      <th>670</th>\n",
       "      <td>USGS</td>\n",
       "      <td>271956082345200</td>\n",
       "      <td>2022-10-01</td>\n",
       "      <td>10:15</td>\n",
       "      <td>EDT</td>\n",
       "      <td>-0.71</td>\n",
       "      <td>P</td>\n",
       "      <td>2022-10-01 10:15:00+04:00</td>\n",
       "      <td>-0.216408</td>\n",
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       "    <tr>\n",
       "      <th>671</th>\n",
       "      <td>USGS</td>\n",
       "      <td>271956082345200</td>\n",
       "      <td>2022-10-01</td>\n",
       "      <td>10:30</td>\n",
       "      <td>EDT</td>\n",
       "      <td>-0.74</td>\n",
       "      <td>P</td>\n",
       "      <td>2022-10-01 10:30:00+04:00</td>\n",
       "      <td>-0.225552</td>\n",
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      "text/plain": [
       "    Agency          Site No        Date   Time   TZ  Elev ft Approved  \\\n",
       "0     USGS  271956082345200  2022-09-24  10:45  EDT     1.21        A   \n",
       "1     USGS  271956082345200  2022-09-24  11:00  EDT     1.27        A   \n",
       "2     USGS  271956082345200  2022-09-24  11:15  EDT     1.34        A   \n",
       "3     USGS  271956082345200  2022-09-24  11:30  EDT     1.38        A   \n",
       "4     USGS  271956082345200  2022-09-24  11:45  EDT     1.41        A   \n",
       "..     ...              ...         ...    ...  ...      ...      ...   \n",
       "667   USGS  271956082345200  2022-10-01  09:30  EDT    -0.54        A   \n",
       "668   USGS  271956082345200  2022-10-01  09:45  EDT    -0.61        A   \n",
       "669   USGS  271956082345200  2022-10-01  10:00  EDT    -0.67        A   \n",
       "670   USGS  271956082345200  2022-10-01  10:15  EDT    -0.71        P   \n",
       "671   USGS  271956082345200  2022-10-01  10:30  EDT    -0.74        P   \n",
       "\n",
       "                           dt  Elev (m)  \n",
       "0   2022-09-24 10:45:00+04:00  0.368808  \n",
       "1   2022-09-24 11:00:00+04:00  0.387096  \n",
       "2   2022-09-24 11:15:00+04:00  0.408432  \n",
       "3   2022-09-24 11:30:00+04:00  0.420624  \n",
       "4   2022-09-24 11:45:00+04:00  0.429768  \n",
       "..                        ...       ...  \n",
       "667 2022-10-01 09:30:00+04:00 -0.164592  \n",
       "668 2022-10-01 09:45:00+04:00 -0.185928  \n",
       "669 2022-10-01 10:00:00+04:00 -0.204216  \n",
       "670 2022-10-01 10:15:00+04:00 -0.216408  \n",
       "671 2022-10-01 10:30:00+04:00 -0.225552  \n",
       "\n",
       "[672 rows x 9 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "col_names = ['Agency','Site No','Date','Time','TZ','Elev ft','Approved'] \n",
    "df_np = pd.read_csv( data_dir + npass + '.txt', skiprows = 29, header=None, names = col_names, delim_whitespace=True )\n",
    "df_np['dt'] = pd.to_datetime( df_np['Date'].astype(str) + ' ' + df_np['Time'].astype(str) + ' +0400' )\n",
    "df_np['Elev (m)'] = df_np['Elev ft'].values*.3048\n",
    "df_np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "a5a1fd52-a31a-46af-a182-ec91d21e9b7e",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Agency</th>\n",
       "      <th>Site No</th>\n",
       "      <th>Date</th>\n",
       "      <th>Time</th>\n",
       "      <th>TZ</th>\n",
       "      <th>Elev ft</th>\n",
       "      <th>Approved</th>\n",
       "      <th>dt</th>\n",
       "      <th>Elev (m)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>USGS</td>\n",
       "      <td>273511082371300</td>\n",
       "      <td>2022-09-24</td>\n",
       "      <td>18:00</td>\n",
       "      <td>EDT</td>\n",
       "      <td>-0.29</td>\n",
       "      <td>A</td>\n",
       "      <td>2022-09-24 18:00:00+04:00</td>\n",
       "      <td>-0.088392</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>USGS</td>\n",
       "      <td>273511082371300</td>\n",
       "      <td>2022-09-24</td>\n",
       "      <td>18:15</td>\n",
       "      <td>EDT</td>\n",
       "      <td>-0.36</td>\n",
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       "      <td>2022-09-24 18:15:00+04:00</td>\n",
       "      <td>-0.109728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>USGS</td>\n",
       "      <td>273511082371300</td>\n",
       "      <td>2022-09-24</td>\n",
       "      <td>18:30</td>\n",
       "      <td>EDT</td>\n",
       "      <td>-0.38</td>\n",
       "      <td>A</td>\n",
       "      <td>2022-09-24 18:30:00+04:00</td>\n",
       "      <td>-0.115824</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>USGS</td>\n",
       "      <td>273511082371300</td>\n",
       "      <td>2022-09-24</td>\n",
       "      <td>18:45</td>\n",
       "      <td>EDT</td>\n",
       "      <td>-0.43</td>\n",
       "      <td>A</td>\n",
       "      <td>2022-09-24 18:45:00+04:00</td>\n",
       "      <td>-0.131064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>USGS</td>\n",
       "      <td>273511082371300</td>\n",
       "      <td>2022-09-24</td>\n",
       "      <td>19:00</td>\n",
       "      <td>EDT</td>\n",
       "      <td>-0.46</td>\n",
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       "      <td>2022-09-24 19:00:00+04:00</td>\n",
       "      <td>-0.140208</td>\n",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>569</th>\n",
       "      <td>USGS</td>\n",
       "      <td>273511082371300</td>\n",
       "      <td>2022-09-30</td>\n",
       "      <td>16:15</td>\n",
       "      <td>EDT</td>\n",
       "      <td>0.18</td>\n",
       "      <td>A</td>\n",
       "      <td>2022-09-30 16:15:00+04:00</td>\n",
       "      <td>0.054864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>570</th>\n",
       "      <td>USGS</td>\n",
       "      <td>273511082371300</td>\n",
       "      <td>2022-09-30</td>\n",
       "      <td>16:30</td>\n",
       "      <td>EDT</td>\n",
       "      <td>0.26</td>\n",
       "      <td>A</td>\n",
       "      <td>2022-09-30 16:30:00+04:00</td>\n",
       "      <td>0.079248</td>\n",
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       "    <tr>\n",
       "      <th>571</th>\n",
       "      <td>USGS</td>\n",
       "      <td>273511082371300</td>\n",
       "      <td>2022-09-30</td>\n",
       "      <td>16:45</td>\n",
       "      <td>EDT</td>\n",
       "      <td>0.31</td>\n",
       "      <td>A</td>\n",
       "      <td>2022-09-30 16:45:00+04:00</td>\n",
       "      <td>0.094488</td>\n",
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       "    <tr>\n",
       "      <th>572</th>\n",
       "      <td>USGS</td>\n",
       "      <td>273511082371300</td>\n",
       "      <td>2022-09-30</td>\n",
       "      <td>17:00</td>\n",
       "      <td>EDT</td>\n",
       "      <td>0.37</td>\n",
       "      <td>A</td>\n",
       "      <td>2022-09-30 17:00:00+04:00</td>\n",
       "      <td>0.112776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>573</th>\n",
       "      <td>USGS</td>\n",
       "      <td>273511082371300</td>\n",
       "      <td>2022-09-30</td>\n",
       "      <td>17:15</td>\n",
       "      <td>EDT</td>\n",
       "      <td>0.42</td>\n",
       "      <td>P</td>\n",
       "      <td>2022-09-30 17:15:00+04:00</td>\n",
       "      <td>0.128016</td>\n",
       "    </tr>\n",
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       "</table>\n",
       "<p>574 rows × 9 columns</p>\n",
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      ],
      "text/plain": [
       "    Agency          Site No        Date   Time   TZ  Elev ft Approved  \\\n",
       "0     USGS  273511082371300  2022-09-24  18:00  EDT    -0.29        A   \n",
       "1     USGS  273511082371300  2022-09-24  18:15  EDT    -0.36        A   \n",
       "2     USGS  273511082371300  2022-09-24  18:30  EDT    -0.38        A   \n",
       "3     USGS  273511082371300  2022-09-24  18:45  EDT    -0.43        A   \n",
       "4     USGS  273511082371300  2022-09-24  19:00  EDT    -0.46        A   \n",
       "..     ...              ...         ...    ...  ...      ...      ...   \n",
       "569   USGS  273511082371300  2022-09-30  16:15  EDT     0.18        A   \n",
       "570   USGS  273511082371300  2022-09-30  16:30  EDT     0.26        A   \n",
       "571   USGS  273511082371300  2022-09-30  16:45  EDT     0.31        A   \n",
       "572   USGS  273511082371300  2022-09-30  17:00  EDT     0.37        A   \n",
       "573   USGS  273511082371300  2022-09-30  17:15  EDT     0.42        P   \n",
       "\n",
       "                           dt  Elev (m)  \n",
       "0   2022-09-24 18:00:00+04:00 -0.088392  \n",
       "1   2022-09-24 18:15:00+04:00 -0.109728  \n",
       "2   2022-09-24 18:30:00+04:00 -0.115824  \n",
       "3   2022-09-24 18:45:00+04:00 -0.131064  \n",
       "4   2022-09-24 19:00:00+04:00 -0.140208  \n",
       "..                        ...       ...  \n",
       "569 2022-09-30 16:15:00+04:00  0.054864  \n",
       "570 2022-09-30 16:30:00+04:00  0.079248  \n",
       "571 2022-09-30 16:45:00+04:00  0.094488  \n",
       "572 2022-09-30 17:00:00+04:00  0.112776  \n",
       "573 2022-09-30 17:15:00+04:00  0.128016  \n",
       "\n",
       "[574 rows x 9 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "col_names = ['Agency','Site No','Date','Time','TZ','Elev ft','Approved'] \n",
    "df_tb = pd.read_csv( data_dir + tbay + '.txt', skiprows = 29, header=None, names = col_names, delim_whitespace=True )\n",
    "df_tb['dt'] = pd.to_datetime( df_tb['Date'].astype(str) + ' ' + df_tb['Time'].astype(str) + ' +0400' )\n",
    "df_tb['Elev (m)'] = df_tb['Elev ft'].values*.3048\n",
    "df_tb"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7468cc7d-174b-438e-a6bb-41f3ae7287d8",
   "metadata": {},
   "source": [
    "#### Read and plot the data from Clearwater site 275840082495601  \n",
    "This is in a different format and has more columns, incl. wave data.  \n",
    "Some data cleanup would be required for a nice plot.  \n",
    "All data is labelled 'P' for provisional.  \n",
    "Last data column is same as column 2, but in feet.  \n",
    "\n",
    " TS      parameter     Description  \n",
    "317558       62622     Estuary or ocean water surface elevation above NAVD 1988, meters, [Maximum level]  \n",
    "317559       62622     Estuary or ocean water surface elevation above NAVD 1988, meters, [Mean level]  \n",
    "317561       62622     Estuary or ocean water surface elevation above NAVD 1988, meters, [Minimum level]  \n",
    "317563       72286     Significant wave height, meters  \n",
    "317566       72287     Significant wave period, seconds, [TPEAK]  \n",
    "317657       62620     Estuary or ocean water surface elevation above NAVD 1988, feet, [Mean level]  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "b0923e40-47ba-4849-8743-a0c9cf4bf4b3",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Agency</th>\n",
       "      <th>Site No</th>\n",
       "      <th>Date</th>\n",
       "      <th>Time</th>\n",
       "      <th>TZ</th>\n",
       "      <th>Max. Elev. (m)</th>\n",
       "      <th>A0</th>\n",
       "      <th>Mean Elev. (m)</th>\n",
       "      <th>A1</th>\n",
       "      <th>Min. Elev. (m)</th>\n",
       "      <th>A2</th>\n",
       "      <th>Hs (m)</th>\n",
       "      <th>A3</th>\n",
       "      <th>Tp (s)</th>\n",
       "      <th>A4</th>\n",
       "      <th>Elev. (ft)</th>\n",
       "      <th>A5</th>\n",
       "      <th>dt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>USGS</td>\n",
       "      <td>275840082495601</td>\n",
       "      <td>2022-09-26</td>\n",
       "      <td>15:06</td>\n",
       "      <td>EDT</td>\n",
       "      <td>0.870</td>\n",
       "      <td>P</td>\n",
       "      <td>0.617</td>\n",
       "      <td>P</td>\n",
       "      <td>0.360</td>\n",
       "      <td>P</td>\n",
       "      <td>0.358</td>\n",
       "      <td>P</td>\n",
       "      <td>2.3</td>\n",
       "      <td>P</td>\n",
       "      <td>2.02</td>\n",
       "      <td>P</td>\n",
       "      <td>2022-09-26 15:06:00+04:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>USGS</td>\n",
       "      <td>275840082495601</td>\n",
       "      <td>2022-09-26</td>\n",
       "      <td>15:12</td>\n",
       "      <td>EDT</td>\n",
       "      <td>0.822</td>\n",
       "      <td>P</td>\n",
       "      <td>0.600</td>\n",
       "      <td>P</td>\n",
       "      <td>0.417</td>\n",
       "      <td>P</td>\n",
       "      <td>0.324</td>\n",
       "      <td>P</td>\n",
       "      <td>2.8</td>\n",
       "      <td>P</td>\n",
       "      <td>1.97</td>\n",
       "      <td>P</td>\n",
       "      <td>2022-09-26 15:12:00+04:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>USGS</td>\n",
       "      <td>275840082495601</td>\n",
       "      <td>2022-09-26</td>\n",
       "      <td>15:18</td>\n",
       "      <td>EDT</td>\n",
       "      <td>0.831</td>\n",
       "      <td>P</td>\n",
       "      <td>0.589</td>\n",
       "      <td>P</td>\n",
       "      <td>0.378</td>\n",
       "      <td>P</td>\n",
       "      <td>0.379</td>\n",
       "      <td>P</td>\n",
       "      <td>2.3</td>\n",
       "      <td>P</td>\n",
       "      <td>1.93</td>\n",
       "      <td>P</td>\n",
       "      <td>2022-09-26 15:18:00+04:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>USGS</td>\n",
       "      <td>275840082495601</td>\n",
       "      <td>2022-09-26</td>\n",
       "      <td>15:24</td>\n",
       "      <td>EDT</td>\n",
       "      <td>0.840</td>\n",
       "      <td>P</td>\n",
       "      <td>0.557</td>\n",
       "      <td>P</td>\n",
       "      <td>0.344</td>\n",
       "      <td>P</td>\n",
       "      <td>0.336</td>\n",
       "      <td>P</td>\n",
       "      <td>2.1</td>\n",
       "      <td>P</td>\n",
       "      <td>1.83</td>\n",
       "      <td>P</td>\n",
       "      <td>2022-09-26 15:24:00+04:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>USGS</td>\n",
       "      <td>275840082495601</td>\n",
       "      <td>2022-09-26</td>\n",
       "      <td>15:30</td>\n",
       "      <td>EDT</td>\n",
       "      <td>0.821</td>\n",
       "      <td>P</td>\n",
       "      <td>0.528</td>\n",
       "      <td>P</td>\n",
       "      <td>0.309</td>\n",
       "      <td>P</td>\n",
       "      <td>0.393</td>\n",
       "      <td>P</td>\n",
       "      <td>2.8</td>\n",
       "      <td>P</td>\n",
       "      <td>1.73</td>\n",
       "      <td>P</td>\n",
       "      <td>2022-09-26 15:30:00+04:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1662</th>\n",
       "      <td>USGS</td>\n",
       "      <td>275840082495601</td>\n",
       "      <td>2022-10-03</td>\n",
       "      <td>14:36</td>\n",
       "      <td>EDT</td>\n",
       "      <td>0.158</td>\n",
       "      <td>P</td>\n",
       "      <td>-0.174</td>\n",
       "      <td>P</td>\n",
       "      <td>-0.433</td>\n",
       "      <td>P</td>\n",
       "      <td>0.462</td>\n",
       "      <td>P</td>\n",
       "      <td>2.8</td>\n",
       "      <td>P</td>\n",
       "      <td>-0.57</td>\n",
       "      <td>P</td>\n",
       "      <td>2022-10-03 14:36:00+04:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1663</th>\n",
       "      <td>USGS</td>\n",
       "      <td>275840082495601</td>\n",
       "      <td>2022-10-03</td>\n",
       "      <td>14:42</td>\n",
       "      <td>EDT</td>\n",
       "      <td>0.112</td>\n",
       "      <td>P</td>\n",
       "      <td>-0.173</td>\n",
       "      <td>P</td>\n",
       "      <td>-0.411</td>\n",
       "      <td>P</td>\n",
       "      <td>0.357</td>\n",
       "      <td>P</td>\n",
       "      <td>2.3</td>\n",
       "      <td>P</td>\n",
       "      <td>-0.57</td>\n",
       "      <td>P</td>\n",
       "      <td>2022-10-03 14:42:00+04:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1664</th>\n",
       "      <td>USGS</td>\n",
       "      <td>275840082495601</td>\n",
       "      <td>2022-10-03</td>\n",
       "      <td>14:48</td>\n",
       "      <td>EDT</td>\n",
       "      <td>0.126</td>\n",
       "      <td>P</td>\n",
       "      <td>-0.162</td>\n",
       "      <td>P</td>\n",
       "      <td>-0.406</td>\n",
       "      <td>P</td>\n",
       "      <td>0.464</td>\n",
       "      <td>P</td>\n",
       "      <td>3.2</td>\n",
       "      <td>P</td>\n",
       "      <td>-0.53</td>\n",
       "      <td>P</td>\n",
       "      <td>2022-10-03 14:48:00+04:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1665</th>\n",
       "      <td>USGS</td>\n",
       "      <td>275840082495601</td>\n",
       "      <td>2022-10-03</td>\n",
       "      <td>14:54</td>\n",
       "      <td>EDT</td>\n",
       "      <td>0.118</td>\n",
       "      <td>P</td>\n",
       "      <td>-0.140</td>\n",
       "      <td>P</td>\n",
       "      <td>-0.463</td>\n",
       "      <td>P</td>\n",
       "      <td>0.414</td>\n",
       "      <td>P</td>\n",
       "      <td>3.2</td>\n",
       "      <td>P</td>\n",
       "      <td>-0.46</td>\n",
       "      <td>P</td>\n",
       "      <td>2022-10-03 14:54:00+04:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1666</th>\n",
       "      <td>USGS</td>\n",
       "      <td>275840082495601</td>\n",
       "      <td>2022-10-03</td>\n",
       "      <td>15:00</td>\n",
       "      <td>EDT</td>\n",
       "      <td>0.169</td>\n",
       "      <td>P</td>\n",
       "      <td>-0.147</td>\n",
       "      <td>P</td>\n",
       "      <td>-0.449</td>\n",
       "      <td>P</td>\n",
       "      <td>0.500</td>\n",
       "      <td>P</td>\n",
       "      <td>5.1</td>\n",
       "      <td>P</td>\n",
       "      <td>-0.48</td>\n",
       "      <td>P</td>\n",
       "      <td>2022-10-03 15:00:00+04:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1667 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Agency          Site No        Date   Time   TZ  Max. Elev. (m) A0  \\\n",
       "0      USGS  275840082495601  2022-09-26  15:06  EDT           0.870  P   \n",
       "1      USGS  275840082495601  2022-09-26  15:12  EDT           0.822  P   \n",
       "2      USGS  275840082495601  2022-09-26  15:18  EDT           0.831  P   \n",
       "3      USGS  275840082495601  2022-09-26  15:24  EDT           0.840  P   \n",
       "4      USGS  275840082495601  2022-09-26  15:30  EDT           0.821  P   \n",
       "...     ...              ...         ...    ...  ...             ... ..   \n",
       "1662   USGS  275840082495601  2022-10-03  14:36  EDT           0.158  P   \n",
       "1663   USGS  275840082495601  2022-10-03  14:42  EDT           0.112  P   \n",
       "1664   USGS  275840082495601  2022-10-03  14:48  EDT           0.126  P   \n",
       "1665   USGS  275840082495601  2022-10-03  14:54  EDT           0.118  P   \n",
       "1666   USGS  275840082495601  2022-10-03  15:00  EDT           0.169  P   \n",
       "\n",
       "      Mean Elev. (m) A1  Min. Elev. (m) A2  Hs (m) A3  Tp (s) A4  Elev. (ft)  \\\n",
       "0              0.617  P           0.360  P   0.358  P     2.3  P        2.02   \n",
       "1              0.600  P           0.417  P   0.324  P     2.8  P        1.97   \n",
       "2              0.589  P           0.378  P   0.379  P     2.3  P        1.93   \n",
       "3              0.557  P           0.344  P   0.336  P     2.1  P        1.83   \n",
       "4              0.528  P           0.309  P   0.393  P     2.8  P        1.73   \n",
       "...              ... ..             ... ..     ... ..     ... ..         ...   \n",
       "1662          -0.174  P          -0.433  P   0.462  P     2.8  P       -0.57   \n",
       "1663          -0.173  P          -0.411  P   0.357  P     2.3  P       -0.57   \n",
       "1664          -0.162  P          -0.406  P   0.464  P     3.2  P       -0.53   \n",
       "1665          -0.140  P          -0.463  P   0.414  P     3.2  P       -0.46   \n",
       "1666          -0.147  P          -0.449  P   0.500  P     5.1  P       -0.48   \n",
       "\n",
       "     A5                        dt  \n",
       "0     P 2022-09-26 15:06:00+04:00  \n",
       "1     P 2022-09-26 15:12:00+04:00  \n",
       "2     P 2022-09-26 15:18:00+04:00  \n",
       "3     P 2022-09-26 15:24:00+04:00  \n",
       "4     P 2022-09-26 15:30:00+04:00  \n",
       "...  ..                       ...  \n",
       "1662  P 2022-10-03 14:36:00+04:00  \n",
       "1663  P 2022-10-03 14:42:00+04:00  \n",
       "1664  P 2022-10-03 14:48:00+04:00  \n",
       "1665  P 2022-10-03 14:54:00+04:00  \n",
       "1666  P 2022-10-03 15:00:00+04:00  \n",
       "\n",
       "[1667 rows x 18 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "col_names = ['Agency','Site No','Date','Time','TZ','Max. Elev. (m)','A0',\\\n",
    "             'Mean Elev. (m)','A1','Min. Elev. (m)','A2', 'Hs (m)', 'A3', 'Tp (s)', 'A4',\n",
    "             'Elev. (ft)', 'A5'] \n",
    "df_clr = pd.read_csv( data_dir + clear + '.txt', skiprows = 34, names = col_names, header=None, delim_whitespace=True )\n",
    "df_clr['dt'] = pd.to_datetime( df_clr['Date'].astype(str) + ' ' + df_clr['Time'].astype(str) + ' +0400' )\n",
    "df_clr"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c12f300f-1fdf-4fbb-ba3a-96936d96a9c2",
   "metadata": {},
   "source": [
    "### Plot the Clearwater water levels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "21ac7c5c-8665-4ea6-bed6-a7c05029fd00",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(df_clr['dt'],df_clr['Elev. (ft)']*.3048, label='Elev')\n",
    "plt.plot(df_clr['dt'],df_clr['Max. Elev. (m)'],'.', label='Max')\n",
    "plt.plot(df_clr['dt'],df_clr['Mean Elev. (m)'], label='Mean')\n",
    "plt.plot(df_clr['dt'],df_clr['Min. Elev. (m)'], '.', label='Min')\n",
    "\n",
    "plt.legend()\n",
    "plt.ylabel('Elevation (m NAVD88)')\n",
    "_ = plt.xticks(rotation=45)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "747105ba-7a18-447c-9926-122b58fccc97",
   "metadata": {},
   "source": [
    "#### Plot the Clearwater wave data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d302dd12-a715-44ac-8bc8-a5518ea50d0d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(df_clr['dt'],df_clr['Hs (m)'],'.',label='Hs')\n",
    "plt.plot(df_clr['dt'],df_clr['Tp (s)'],'.', label='Tp')\n",
    "\n",
    "plt.legend()\n",
    "plt.ylabel('Elevation (m), Period (s)')\n",
    "_ = plt.xticks(rotation=45)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e90cb648-2ee7-4f5c-8594-ffbe36ad830e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#### Plot all of the water-level data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "67c43814-8ff6-498d-8361-d417701286d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(df_tb['dt'],df_tb['Elev (m)'], label='Tampa Bay')\n",
    "plt.plot(df_fm['dt'],df_fm['Elev (m)'], label='Ft Myers')\n",
    "plt.plot(df_np['dt'],df_np['Elev (m)'], label='New Pass')\n",
    "plt.plot(df_clr['dt'],df_clr['Mean Elev. (m)'], label='Clearwater')\n",
    "\n",
    "plt.legend()\n",
    "plt.ylabel('Elevation (m NAVD88)')\n",
    "_ = plt.xticks(rotation=45)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0baeffbe-53f0-4b35-b53f-9460716a842d",
   "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": "3.9.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}