2.0_DischargeAdjustment.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "dc785af0-2e2f-431b-96b2-195ed14e8528",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import os\n",
    "from datetime import datetime\n",
    "from dataretrieval import nwis\n",
    "import matplotlib.pyplot as plt\n",
    "import pytz\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2240db91",
   "metadata": {},
   "source": [
    "### In this note book we will:\n",
    "- Extract the flow at the nearest USGS gage from the date of each flowtracker measurement\n",
    "- Get the proportion of our measured flow to the flow at the USGS gage at the same time\n",
    "- Apply that proportion to the time period we want to model, to adjust boundary and tributary flows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "ee213db8-906b-477d-8eca-b8d633e406d6",
   "metadata": {},
   "outputs": [],
   "source": [
    "#reading in data with relative paths so that it can be used by others who clone repository from github\n",
    "script_dir = os.getcwd()\n",
    "\n",
    "#flowtracker Observations\n",
    "flowtracker_path = os.path.abspath(os.path.join(script_dir, '..', '..', 'observations','FlowTrackerObs', 'FlowtrackerMaster2023.csv'))\n",
    "\n",
    "\n",
    "#read flowtracker data\n",
    "flowtracker = pd.read_csv(flowtracker_path)\n",
    "# flowtracker.index = flowtracker['Name']\n",
    "flowtracker.set_index('Name', drop=True, inplace=True)\n",
    "# July calibration Files\n",
    "july_hsfiles_path = os.path.abspath(os.path.join(script_dir, '..', '..', 'calibration','July'))\n",
    "\n",
    "# June calibration Files\n",
    "june_hsfiles_path = os.path.abspath(os.path.join(script_dir, '..', '..', 'calibration','June'))\n",
    "\n",
    "# August calibration Files\n",
    "august_hsfiles_path = os.path.abspath(os.path.join(script_dir, '..', '..', 'calibration','August'))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "b62e4ee2",
   "metadata": {},
   "outputs": [
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       "      <th>Lat</th>\n",
       "      <th>Lon</th>\n",
       "      <th>Name.1</th>\n",
       "      <th>Datetime</th>\n",
       "      <th>Width</th>\n",
       "      <th>Area</th>\n",
       "      <th>Discharge</th>\n",
       "      <th>discharge_uncertaintyIVE_perc</th>\n",
       "      <th>Depth</th>\n",
       "      <th>Velocity</th>\n",
       "      <th>velocity_uncertaintyIVE_perc</th>\n",
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       "    <tr>\n",
       "      <th>Name</th>\n",
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       "      <th>Sb_conf</th>\n",
       "      <td>43.595100</td>\n",
       "      <td>-90.782040</td>\n",
       "      <td>Sb.conf</td>\n",
       "      <td>6/23/2023 11:39</td>\n",
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       "      <td>0.2740</td>\n",
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       "      <td>0.169</td>\n",
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       "      <td>43.604770</td>\n",
       "      <td>-90.834870</td>\n",
       "      <td>Sb.crumedown</td>\n",
       "      <td>6/27/2023 11:56</td>\n",
       "      <td>4.54</td>\n",
       "      <td>0.719</td>\n",
       "      <td>0.0980</td>\n",
       "      <td>19.236</td>\n",
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       "      <th>Sb_crumetrib</th>\n",
       "      <td>43.603910</td>\n",
       "      <td>-90.837360</td>\n",
       "      <td>Sb.crumetrib</td>\n",
       "      <td>6/27/2023 12:56</td>\n",
       "      <td>2.50</td>\n",
       "      <td>0.302</td>\n",
       "      <td>0.0730</td>\n",
       "      <td>6.633</td>\n",
       "      <td>0.121</td>\n",
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       "      <td>4.727</td>\n",
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       "    <tr>\n",
       "      <th>Sb_crumeup</th>\n",
       "      <td>43.603050</td>\n",
       "      <td>-90.839470</td>\n",
       "      <td>Sb.crumeup</td>\n",
       "      <td>6/27/2023 13:55</td>\n",
       "      <td>3.40</td>\n",
       "      <td>0.602</td>\n",
       "      <td>0.0520</td>\n",
       "      <td>5.891</td>\n",
       "      <td>0.177</td>\n",
       "      <td>0.086</td>\n",
       "      <td>5.298</td>\n",
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       "    <tr>\n",
       "      <th>Sb_thdown</th>\n",
       "      <td>43.606780</td>\n",
       "      <td>-90.808920</td>\n",
       "      <td>Sb.thdown</td>\n",
       "      <td>6/13/2023 14:15</td>\n",
       "      <td>5.40</td>\n",
       "      <td>1.245</td>\n",
       "      <td>0.2260</td>\n",
       "      <td>7.174</td>\n",
       "      <td>0.231</td>\n",
       "      <td>0.182</td>\n",
       "      <td>6.280</td>\n",
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       "    <tr>\n",
       "      <th>Sb_thtrib</th>\n",
       "      <td>43.609738</td>\n",
       "      <td>-90.812206</td>\n",
       "      <td>Sb.thtrib</td>\n",
       "      <td>6/13/2023 13:05</td>\n",
       "      <td>1.30</td>\n",
       "      <td>0.073</td>\n",
       "      <td>0.0050</td>\n",
       "      <td>60.032</td>\n",
       "      <td>0.056</td>\n",
       "      <td>0.069</td>\n",
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       "      <th>SB_thup</th>\n",
       "      <td>43.610060</td>\n",
       "      <td>-90.813530</td>\n",
       "      <td>SB.thup</td>\n",
       "      <td>6/13/2023 11:59</td>\n",
       "      <td>4.80</td>\n",
       "      <td>1.023</td>\n",
       "      <td>0.2100</td>\n",
       "      <td>6.459</td>\n",
       "      <td>0.213</td>\n",
       "      <td>0.206</td>\n",
       "      <td>5.753</td>\n",
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       "      <th>WF_sportsclubDOWN</th>\n",
       "      <td>43.596940</td>\n",
       "      <td>-90.780300</td>\n",
       "      <td>Wfsc.down2</td>\n",
       "      <td>6/23/2023 12:39</td>\n",
       "      <td>6.42</td>\n",
       "      <td>1.124</td>\n",
       "      <td>0.6940</td>\n",
       "      <td>4.838</td>\n",
       "      <td>0.175</td>\n",
       "      <td>0.617</td>\n",
       "      <td>3.834</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wfsc_down</th>\n",
       "      <td>43.596940</td>\n",
       "      <td>-90.780300</td>\n",
       "      <td>Wfsc.down</td>\n",
       "      <td>6/15/2023 6:49</td>\n",
       "      <td>7.75</td>\n",
       "      <td>1.721</td>\n",
       "      <td>0.9780</td>\n",
       "      <td>5.104</td>\n",
       "      <td>0.222</td>\n",
       "      <td>0.568</td>\n",
       "      <td>4.439</td>\n",
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       "    <tr>\n",
       "      <th>WF_wfscUP</th>\n",
       "      <td>43.599750</td>\n",
       "      <td>-90.779830</td>\n",
       "      <td>Wf.wfscup2</td>\n",
       "      <td>8/2/2023 7:25</td>\n",
       "      <td>6.05</td>\n",
       "      <td>1.597</td>\n",
       "      <td>0.6200</td>\n",
       "      <td>3.489</td>\n",
       "      <td>0.264</td>\n",
       "      <td>0.389</td>\n",
       "      <td>2.688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wfsc_up</th>\n",
       "      <td>43.599750</td>\n",
       "      <td>-90.779830</td>\n",
       "      <td>Wf.wfscup1</td>\n",
       "      <td>6/15/2023 7:47</td>\n",
       "      <td>5.70</td>\n",
       "      <td>2.172</td>\n",
       "      <td>1.0640</td>\n",
       "      <td>3.258</td>\n",
       "      <td>0.381</td>\n",
       "      <td>0.490</td>\n",
       "      <td>2.811</td>\n",
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       "      <th>Wf_bloomtrib</th>\n",
       "      <td>43.643990</td>\n",
       "      <td>-90.783590</td>\n",
       "      <td>Wf.bloomtrib</td>\n",
       "      <td>6/28/2023 11:45</td>\n",
       "      <td>1.09</td>\n",
       "      <td>0.089</td>\n",
       "      <td>0.0010</td>\n",
       "      <td>53.218</td>\n",
       "      <td>0.082</td>\n",
       "      <td>0.009</td>\n",
       "      <td>51.580</td>\n",
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       "    <tr>\n",
       "      <th>Wf_boydtrib</th>\n",
       "      <td>43.653970</td>\n",
       "      <td>-90.778880</td>\n",
       "      <td>Wf.boydtrib</td>\n",
       "      <td>6/22/2023 15:03</td>\n",
       "      <td>2.10</td>\n",
       "      <td>0.383</td>\n",
       "      <td>0.0420</td>\n",
       "      <td>6.521</td>\n",
       "      <td>0.182</td>\n",
       "      <td>0.109</td>\n",
       "      <td>5.565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WF_ebloomingdaleRd</th>\n",
       "      <td>43.638220</td>\n",
       "      <td>-90.773430</td>\n",
       "      <td>Wf.eblmrd</td>\n",
       "      <td>6/22/2023 10:01</td>\n",
       "      <td>7.60</td>\n",
       "      <td>2.024</td>\n",
       "      <td>0.4760</td>\n",
       "      <td>4.785</td>\n",
       "      <td>0.266</td>\n",
       "      <td>0.235</td>\n",
       "      <td>3.757</td>\n",
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       "    <tr>\n",
       "      <th>Wf_haLl</th>\n",
       "      <td>43.636500</td>\n",
       "      <td>-90.767570</td>\n",
       "      <td>Wf.haLl</td>\n",
       "      <td>6/23/2023 9:28</td>\n",
       "      <td>2.42</td>\n",
       "      <td>0.290</td>\n",
       "      <td>0.0320</td>\n",
       "      <td>6.091</td>\n",
       "      <td>0.120</td>\n",
       "      <td>0.109</td>\n",
       "      <td>3.840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WF_hayesDOWN</th>\n",
       "      <td>43.654730</td>\n",
       "      <td>-90.780990</td>\n",
       "      <td>Wf.hayesdn</td>\n",
       "      <td>6/22/2023 13:55</td>\n",
       "      <td>6.80</td>\n",
       "      <td>1.891</td>\n",
       "      <td>0.4230</td>\n",
       "      <td>6.230</td>\n",
       "      <td>0.278</td>\n",
       "      <td>0.224</td>\n",
       "      <td>5.936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WF_hayesUP</th>\n",
       "      <td>43.661720</td>\n",
       "      <td>-90.785160</td>\n",
       "      <td>Wf.hayesup2</td>\n",
       "      <td>6/22/2023 16:06</td>\n",
       "      <td>7.60</td>\n",
       "      <td>2.334</td>\n",
       "      <td>0.3480</td>\n",
       "      <td>5.416</td>\n",
       "      <td>0.307</td>\n",
       "      <td>0.149</td>\n",
       "      <td>4.593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wf_hayesup_1</th>\n",
       "      <td>43.661720</td>\n",
       "      <td>-90.785160</td>\n",
       "      <td>Wf.hayesup</td>\n",
       "      <td>6/1/2023 12:25</td>\n",
       "      <td>7.21</td>\n",
       "      <td>1.877</td>\n",
       "      <td>0.2160</td>\n",
       "      <td>2.362</td>\n",
       "      <td>0.260</td>\n",
       "      <td>0.115</td>\n",
       "      <td>1.426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wf_hayes_trib</th>\n",
       "      <td>43.656575</td>\n",
       "      <td>-90.783876</td>\n",
       "      <td>Wf.hayes.trib</td>\n",
       "      <td>6/22/2023 13:08</td>\n",
       "      <td>2.80</td>\n",
       "      <td>0.380</td>\n",
       "      <td>0.0580</td>\n",
       "      <td>9.486</td>\n",
       "      <td>0.136</td>\n",
       "      <td>0.153</td>\n",
       "      <td>4.984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wf_hwy82tribup</th>\n",
       "      <td>43.563881</td>\n",
       "      <td>-90.762369</td>\n",
       "      <td>Wf.hwy82trib</td>\n",
       "      <td>5/31/2023 15:28</td>\n",
       "      <td>3.60</td>\n",
       "      <td>0.471</td>\n",
       "      <td>0.0470</td>\n",
       "      <td>8.564</td>\n",
       "      <td>0.131</td>\n",
       "      <td>0.099</td>\n",
       "      <td>7.546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WF_hwy82UP</th>\n",
       "      <td>43.563830</td>\n",
       "      <td>-90.761460</td>\n",
       "      <td>Wf.hwy82up</td>\n",
       "      <td>5/31/2023 16:12</td>\n",
       "      <td>12.79</td>\n",
       "      <td>4.094</td>\n",
       "      <td>1.0780</td>\n",
       "      <td>4.646</td>\n",
       "      <td>0.320</td>\n",
       "      <td>0.263</td>\n",
       "      <td>3.215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WF_knapptrib</th>\n",
       "      <td>43.664650</td>\n",
       "      <td>-90.786800</td>\n",
       "      <td>Wf.knapptrib</td>\n",
       "      <td>7/18/2023 12:47</td>\n",
       "      <td>5.00</td>\n",
       "      <td>1.360</td>\n",
       "      <td>0.1030</td>\n",
       "      <td>5.781</td>\n",
       "      <td>0.272</td>\n",
       "      <td>0.076</td>\n",
       "      <td>5.468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WF_lukensDOWN</th>\n",
       "      <td>43.553130</td>\n",
       "      <td>-90.747600</td>\n",
       "      <td>Wf.lukensdown</td>\n",
       "      <td>5/31/2023 11:30</td>\n",
       "      <td>12.90</td>\n",
       "      <td>3.536</td>\n",
       "      <td>1.2740</td>\n",
       "      <td>3.144</td>\n",
       "      <td>0.274</td>\n",
       "      <td>0.360</td>\n",
       "      <td>2.323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WF_lukensUP</th>\n",
       "      <td>43.556200</td>\n",
       "      <td>-90.754500</td>\n",
       "      <td>Wf.lukensup</td>\n",
       "      <td>5/31/2023 9:09</td>\n",
       "      <td>16.80</td>\n",
       "      <td>5.736</td>\n",
       "      <td>1.2100</td>\n",
       "      <td>2.599</td>\n",
       "      <td>0.341</td>\n",
       "      <td>0.211</td>\n",
       "      <td>1.409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wf_mayertrib</th>\n",
       "      <td>43.608600</td>\n",
       "      <td>-90.776340</td>\n",
       "      <td>Wf.mayertrib</td>\n",
       "      <td>6/28/2023 12:47</td>\n",
       "      <td>1.12</td>\n",
       "      <td>0.099</td>\n",
       "      <td>0.0080</td>\n",
       "      <td>14.359</td>\n",
       "      <td>0.088</td>\n",
       "      <td>0.083</td>\n",
       "      <td>12.252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WF_pietschrd</th>\n",
       "      <td>43.589424</td>\n",
       "      <td>-90.773142</td>\n",
       "      <td>Wf.pietsch</td>\n",
       "      <td>6/23/2023 7:21</td>\n",
       "      <td>7.16</td>\n",
       "      <td>2.399</td>\n",
       "      <td>1.0760</td>\n",
       "      <td>4.258</td>\n",
       "      <td>0.335</td>\n",
       "      <td>0.449</td>\n",
       "      <td>3.922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wf_riverrd_trib</th>\n",
       "      <td>43.591450</td>\n",
       "      <td>-90.778420</td>\n",
       "      <td>Wf.riverrd.trib</td>\n",
       "      <td>6/23/2023 8:35</td>\n",
       "      <td>1.70</td>\n",
       "      <td>0.169</td>\n",
       "      <td>0.0350</td>\n",
       "      <td>10.620</td>\n",
       "      <td>0.099</td>\n",
       "      <td>0.207</td>\n",
       "      <td>9.234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wf_rockyrun</th>\n",
       "      <td>43.560070</td>\n",
       "      <td>-90.754950</td>\n",
       "      <td>Wf.rockyrun</td>\n",
       "      <td>5/31/2023 14:11</td>\n",
       "      <td>3.94</td>\n",
       "      <td>1.208</td>\n",
       "      <td>0.0820</td>\n",
       "      <td>6.045</td>\n",
       "      <td>0.307</td>\n",
       "      <td>0.068</td>\n",
       "      <td>4.314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WF_riverview</th>\n",
       "      <td>43.665980</td>\n",
       "      <td>-90.789750</td>\n",
       "      <td>Wf.rrunup</td>\n",
       "      <td>7/18/2023 11:47</td>\n",
       "      <td>3.95</td>\n",
       "      <td>0.831</td>\n",
       "      <td>0.1470</td>\n",
       "      <td>7.366</td>\n",
       "      <td>0.210</td>\n",
       "      <td>0.177</td>\n",
       "      <td>6.928</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wf_salem</th>\n",
       "      <td>43.628620</td>\n",
       "      <td>-90.761540</td>\n",
       "      <td>Wf.salem</td>\n",
       "      <td>6/23/2023 10:12</td>\n",
       "      <td>1.88</td>\n",
       "      <td>0.161</td>\n",
       "      <td>0.0380</td>\n",
       "      <td>20.641</td>\n",
       "      <td>0.086</td>\n",
       "      <td>0.235</td>\n",
       "      <td>17.793</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WF_saunders</th>\n",
       "      <td>43.574130</td>\n",
       "      <td>-90.763530</td>\n",
       "      <td>Wf.saunders</td>\n",
       "      <td>7/20/2023 9:33</td>\n",
       "      <td>15.40</td>\n",
       "      <td>7.012</td>\n",
       "      <td>0.9440</td>\n",
       "      <td>2.474</td>\n",
       "      <td>0.455</td>\n",
       "      <td>0.135</td>\n",
       "      <td>1.771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WF_smarthallow</th>\n",
       "      <td>43.613080</td>\n",
       "      <td>-90.781280</td>\n",
       "      <td>Wf.smarthallowup</td>\n",
       "      <td>6/1/2023 7:18</td>\n",
       "      <td>10.65</td>\n",
       "      <td>3.806</td>\n",
       "      <td>0.5960</td>\n",
       "      <td>5.296</td>\n",
       "      <td>0.357</td>\n",
       "      <td>0.156</td>\n",
       "      <td>3.151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wf_smrthlw_trb</th>\n",
       "      <td>43.610922</td>\n",
       "      <td>-90.781018</td>\n",
       "      <td>Wf.smrthlw.trb</td>\n",
       "      <td>6/1/2023 8:10</td>\n",
       "      <td>0.53</td>\n",
       "      <td>0.040</td>\n",
       "      <td>0.0020</td>\n",
       "      <td>16.620</td>\n",
       "      <td>0.075</td>\n",
       "      <td>0.056</td>\n",
       "      <td>8.550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WF_starksDOWN</th>\n",
       "      <td>43.644870</td>\n",
       "      <td>-90.780530</td>\n",
       "      <td>Wf.starks2</td>\n",
       "      <td>6/22/2023 12:00</td>\n",
       "      <td>7.60</td>\n",
       "      <td>2.012</td>\n",
       "      <td>0.4830</td>\n",
       "      <td>7.358</td>\n",
       "      <td>0.265</td>\n",
       "      <td>0.240</td>\n",
       "      <td>7.079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wf_starks</th>\n",
       "      <td>43.644870</td>\n",
       "      <td>-90.780530</td>\n",
       "      <td>Wf.starks</td>\n",
       "      <td>6/22/2023 11:14</td>\n",
       "      <td>7.60</td>\n",
       "      <td>2.052</td>\n",
       "      <td>0.4770</td>\n",
       "      <td>13.969</td>\n",
       "      <td>0.270</td>\n",
       "      <td>0.232</td>\n",
       "      <td>13.821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wf_thnorthdown</th>\n",
       "      <td>43.618908</td>\n",
       "      <td>-90.780521</td>\n",
       "      <td>Wf.thnorthdown</td>\n",
       "      <td>6/1/2023 9:18</td>\n",
       "      <td>13.80</td>\n",
       "      <td>4.450</td>\n",
       "      <td>0.5710</td>\n",
       "      <td>5.853</td>\n",
       "      <td>0.322</td>\n",
       "      <td>0.128</td>\n",
       "      <td>5.134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WF_thnorthUP</th>\n",
       "      <td>43.620197</td>\n",
       "      <td>-90.774907</td>\n",
       "      <td>Wf.thnorthup</td>\n",
       "      <td>6/1/2023 10:18</td>\n",
       "      <td>12.45</td>\n",
       "      <td>2.515</td>\n",
       "      <td>0.5260</td>\n",
       "      <td>10.397</td>\n",
       "      <td>0.202</td>\n",
       "      <td>0.209</td>\n",
       "      <td>10.004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wf_thnorth_trib</th>\n",
       "      <td>43.620150</td>\n",
       "      <td>-90.779782</td>\n",
       "      <td>Wf.thnorth.trib</td>\n",
       "      <td>6/1/2023 8:44</td>\n",
       "      <td>0.90</td>\n",
       "      <td>0.096</td>\n",
       "      <td>0.0150</td>\n",
       "      <td>12.193</td>\n",
       "      <td>0.107</td>\n",
       "      <td>0.152</td>\n",
       "      <td>10.038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WF_thsouthup</th>\n",
       "      <td>43.588093</td>\n",
       "      <td>-90.773650</td>\n",
       "      <td>Wf.thsouthup</td>\n",
       "      <td>7/20/2023 7:52</td>\n",
       "      <td>8.53</td>\n",
       "      <td>4.341</td>\n",
       "      <td>0.8940</td>\n",
       "      <td>4.064</td>\n",
       "      <td>0.509</td>\n",
       "      <td>0.206</td>\n",
       "      <td>3.762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WF_thsouth</th>\n",
       "      <td>43.578510</td>\n",
       "      <td>-90.775570</td>\n",
       "      <td>Wf.thsouth</td>\n",
       "      <td>7/18/2023 15:04</td>\n",
       "      <td>9.50</td>\n",
       "      <td>2.975</td>\n",
       "      <td>0.9070</td>\n",
       "      <td>6.924</td>\n",
       "      <td>0.313</td>\n",
       "      <td>0.305</td>\n",
       "      <td>4.257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WF_yoder</th>\n",
       "      <td>43.630587</td>\n",
       "      <td>-90.770006</td>\n",
       "      <td>Wf.yoderdown</td>\n",
       "      <td>6/28/2023 10:28</td>\n",
       "      <td>7.50</td>\n",
       "      <td>1.995</td>\n",
       "      <td>0.5030</td>\n",
       "      <td>6.887</td>\n",
       "      <td>0.266</td>\n",
       "      <td>0.252</td>\n",
       "      <td>6.601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WF_yodertrib</th>\n",
       "      <td>43.629955</td>\n",
       "      <td>-90.770427</td>\n",
       "      <td>Wf.yodertribdown</td>\n",
       "      <td>7/19/2023 9:05</td>\n",
       "      <td>1.80</td>\n",
       "      <td>0.214</td>\n",
       "      <td>0.0300</td>\n",
       "      <td>17.056</td>\n",
       "      <td>0.119</td>\n",
       "      <td>0.139</td>\n",
       "      <td>16.036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WF_yoderup</th>\n",
       "      <td>43.635190</td>\n",
       "      <td>-90.768230</td>\n",
       "      <td>Wf.yoderup</td>\n",
       "      <td>8/3/2023 9:00</td>\n",
       "      <td>13.45</td>\n",
       "      <td>7.314</td>\n",
       "      <td>0.4850</td>\n",
       "      <td>4.071</td>\n",
       "      <td>0.544</td>\n",
       "      <td>0.066</td>\n",
       "      <td>3.802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WF_hwy82tribDOWN</th>\n",
       "      <td>43.561268</td>\n",
       "      <td>-90.762898</td>\n",
       "      <td>WF_hwy82tribDOWN</td>\n",
       "      <td>7/20/2023 7:56</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0153</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          Lat        Lon            Name.1         Datetime  \\\n",
       "Name                                                                          \n",
       "Sb_conf             43.595100 -90.782040           Sb.conf  6/23/2023 11:39   \n",
       "Sb_crumedown        43.604770 -90.834870      Sb.crumedown  6/27/2023 11:56   \n",
       "Sb_crumetrib        43.603910 -90.837360      Sb.crumetrib  6/27/2023 12:56   \n",
       "Sb_crumeup          43.603050 -90.839470        Sb.crumeup  6/27/2023 13:55   \n",
       "Sb_thdown           43.606780 -90.808920         Sb.thdown  6/13/2023 14:15   \n",
       "Sb_thtrib           43.609738 -90.812206         Sb.thtrib  6/13/2023 13:05   \n",
       "SB_thup             43.610060 -90.813530           SB.thup  6/13/2023 11:59   \n",
       "WF_sportsclubDOWN   43.596940 -90.780300        Wfsc.down2  6/23/2023 12:39   \n",
       "Wfsc_down           43.596940 -90.780300         Wfsc.down   6/15/2023 6:49   \n",
       "WF_wfscUP           43.599750 -90.779830        Wf.wfscup2    8/2/2023 7:25   \n",
       "Wfsc_up             43.599750 -90.779830        Wf.wfscup1   6/15/2023 7:47   \n",
       "Wf_bloomtrib        43.643990 -90.783590      Wf.bloomtrib  6/28/2023 11:45   \n",
       "Wf_boydtrib         43.653970 -90.778880       Wf.boydtrib  6/22/2023 15:03   \n",
       "WF_ebloomingdaleRd  43.638220 -90.773430         Wf.eblmrd  6/22/2023 10:01   \n",
       "Wf_haLl             43.636500 -90.767570           Wf.haLl   6/23/2023 9:28   \n",
       "WF_hayesDOWN        43.654730 -90.780990        Wf.hayesdn  6/22/2023 13:55   \n",
       "WF_hayesUP          43.661720 -90.785160       Wf.hayesup2  6/22/2023 16:06   \n",
       "Wf_hayesup_1        43.661720 -90.785160        Wf.hayesup   6/1/2023 12:25   \n",
       "Wf_hayes_trib       43.656575 -90.783876     Wf.hayes.trib  6/22/2023 13:08   \n",
       "Wf_hwy82tribup      43.563881 -90.762369      Wf.hwy82trib  5/31/2023 15:28   \n",
       "WF_hwy82UP          43.563830 -90.761460        Wf.hwy82up  5/31/2023 16:12   \n",
       "WF_knapptrib        43.664650 -90.786800      Wf.knapptrib  7/18/2023 12:47   \n",
       "WF_lukensDOWN       43.553130 -90.747600     Wf.lukensdown  5/31/2023 11:30   \n",
       "WF_lukensUP         43.556200 -90.754500       Wf.lukensup   5/31/2023 9:09   \n",
       "Wf_mayertrib        43.608600 -90.776340      Wf.mayertrib  6/28/2023 12:47   \n",
       "WF_pietschrd        43.589424 -90.773142        Wf.pietsch   6/23/2023 7:21   \n",
       "Wf_riverrd_trib     43.591450 -90.778420   Wf.riverrd.trib   6/23/2023 8:35   \n",
       "Wf_rockyrun         43.560070 -90.754950       Wf.rockyrun  5/31/2023 14:11   \n",
       "WF_riverview        43.665980 -90.789750         Wf.rrunup  7/18/2023 11:47   \n",
       "Wf_salem            43.628620 -90.761540          Wf.salem  6/23/2023 10:12   \n",
       "WF_saunders         43.574130 -90.763530       Wf.saunders   7/20/2023 9:33   \n",
       "WF_smarthallow      43.613080 -90.781280  Wf.smarthallowup    6/1/2023 7:18   \n",
       "Wf_smrthlw_trb      43.610922 -90.781018    Wf.smrthlw.trb    6/1/2023 8:10   \n",
       "WF_starksDOWN       43.644870 -90.780530        Wf.starks2  6/22/2023 12:00   \n",
       "Wf_starks           43.644870 -90.780530         Wf.starks  6/22/2023 11:14   \n",
       "Wf_thnorthdown      43.618908 -90.780521    Wf.thnorthdown    6/1/2023 9:18   \n",
       "WF_thnorthUP        43.620197 -90.774907      Wf.thnorthup   6/1/2023 10:18   \n",
       "Wf_thnorth_trib     43.620150 -90.779782   Wf.thnorth.trib    6/1/2023 8:44   \n",
       "WF_thsouthup        43.588093 -90.773650      Wf.thsouthup   7/20/2023 7:52   \n",
       "WF_thsouth          43.578510 -90.775570        Wf.thsouth  7/18/2023 15:04   \n",
       "WF_yoder            43.630587 -90.770006      Wf.yoderdown  6/28/2023 10:28   \n",
       "WF_yodertrib        43.629955 -90.770427  Wf.yodertribdown   7/19/2023 9:05   \n",
       "WF_yoderup          43.635190 -90.768230        Wf.yoderup    8/3/2023 9:00   \n",
       "WF_hwy82tribDOWN    43.561268 -90.762898  WF_hwy82tribDOWN   7/20/2023 7:56   \n",
       "\n",
       "                    Width   Area  Discharge  discharge_uncertaintyIVE_perc  \\\n",
       "Name                                                                         \n",
       "Sb_conf              4.43  0.747     0.2740                          7.384   \n",
       "Sb_crumedown         4.54  0.719     0.0980                         19.236   \n",
       "Sb_crumetrib         2.50  0.302     0.0730                          6.633   \n",
       "Sb_crumeup           3.40  0.602     0.0520                          5.891   \n",
       "Sb_thdown            5.40  1.245     0.2260                          7.174   \n",
       "Sb_thtrib            1.30  0.073     0.0050                         60.032   \n",
       "SB_thup              4.80  1.023     0.2100                          6.459   \n",
       "WF_sportsclubDOWN    6.42  1.124     0.6940                          4.838   \n",
       "Wfsc_down            7.75  1.721     0.9780                          5.104   \n",
       "WF_wfscUP            6.05  1.597     0.6200                          3.489   \n",
       "Wfsc_up              5.70  2.172     1.0640                          3.258   \n",
       "Wf_bloomtrib         1.09  0.089     0.0010                         53.218   \n",
       "Wf_boydtrib          2.10  0.383     0.0420                          6.521   \n",
       "WF_ebloomingdaleRd   7.60  2.024     0.4760                          4.785   \n",
       "Wf_haLl              2.42  0.290     0.0320                          6.091   \n",
       "WF_hayesDOWN         6.80  1.891     0.4230                          6.230   \n",
       "WF_hayesUP           7.60  2.334     0.3480                          5.416   \n",
       "Wf_hayesup_1         7.21  1.877     0.2160                          2.362   \n",
       "Wf_hayes_trib        2.80  0.380     0.0580                          9.486   \n",
       "Wf_hwy82tribup       3.60  0.471     0.0470                          8.564   \n",
       "WF_hwy82UP          12.79  4.094     1.0780                          4.646   \n",
       "WF_knapptrib         5.00  1.360     0.1030                          5.781   \n",
       "WF_lukensDOWN       12.90  3.536     1.2740                          3.144   \n",
       "WF_lukensUP         16.80  5.736     1.2100                          2.599   \n",
       "Wf_mayertrib         1.12  0.099     0.0080                         14.359   \n",
       "WF_pietschrd         7.16  2.399     1.0760                          4.258   \n",
       "Wf_riverrd_trib      1.70  0.169     0.0350                         10.620   \n",
       "Wf_rockyrun          3.94  1.208     0.0820                          6.045   \n",
       "WF_riverview         3.95  0.831     0.1470                          7.366   \n",
       "Wf_salem             1.88  0.161     0.0380                         20.641   \n",
       "WF_saunders         15.40  7.012     0.9440                          2.474   \n",
       "WF_smarthallow      10.65  3.806     0.5960                          5.296   \n",
       "Wf_smrthlw_trb       0.53  0.040     0.0020                         16.620   \n",
       "WF_starksDOWN        7.60  2.012     0.4830                          7.358   \n",
       "Wf_starks            7.60  2.052     0.4770                         13.969   \n",
       "Wf_thnorthdown      13.80  4.450     0.5710                          5.853   \n",
       "WF_thnorthUP        12.45  2.515     0.5260                         10.397   \n",
       "Wf_thnorth_trib      0.90  0.096     0.0150                         12.193   \n",
       "WF_thsouthup         8.53  4.341     0.8940                          4.064   \n",
       "WF_thsouth           9.50  2.975     0.9070                          6.924   \n",
       "WF_yoder             7.50  1.995     0.5030                          6.887   \n",
       "WF_yodertrib         1.80  0.214     0.0300                         17.056   \n",
       "WF_yoderup          13.45  7.314     0.4850                          4.071   \n",
       "WF_hwy82tribDOWN      NaN    NaN     0.0153                            NaN   \n",
       "\n",
       "                    Depth  Velocity  velocity_uncertaintyIVE_perc  \n",
       "Name                                                               \n",
       "Sb_conf             0.169     0.367                         6.700  \n",
       "Sb_crumedown        0.158     0.137                        18.852  \n",
       "Sb_crumetrib        0.121     0.242                         4.727  \n",
       "Sb_crumeup          0.177     0.086                         5.298  \n",
       "Sb_thdown           0.231     0.182                         6.280  \n",
       "Sb_thtrib           0.056     0.069                        58.554  \n",
       "SB_thup             0.213     0.206                         5.753  \n",
       "WF_sportsclubDOWN   0.175     0.617                         3.834  \n",
       "Wfsc_down           0.222     0.568                         4.439  \n",
       "WF_wfscUP           0.264     0.389                         2.688  \n",
       "Wfsc_up             0.381     0.490                         2.811  \n",
       "Wf_bloomtrib        0.082     0.009                        51.580  \n",
       "Wf_boydtrib         0.182     0.109                         5.565  \n",
       "WF_ebloomingdaleRd  0.266     0.235                         3.757  \n",
       "Wf_haLl             0.120     0.109                         3.840  \n",
       "WF_hayesDOWN        0.278     0.224                         5.936  \n",
       "WF_hayesUP          0.307     0.149                         4.593  \n",
       "Wf_hayesup_1        0.260     0.115                         1.426  \n",
       "Wf_hayes_trib       0.136     0.153                         4.984  \n",
       "Wf_hwy82tribup      0.131     0.099                         7.546  \n",
       "WF_hwy82UP          0.320     0.263                         3.215  \n",
       "WF_knapptrib        0.272     0.076                         5.468  \n",
       "WF_lukensDOWN       0.274     0.360                         2.323  \n",
       "WF_lukensUP         0.341     0.211                         1.409  \n",
       "Wf_mayertrib        0.088     0.083                        12.252  \n",
       "WF_pietschrd        0.335     0.449                         3.922  \n",
       "Wf_riverrd_trib     0.099     0.207                         9.234  \n",
       "Wf_rockyrun         0.307     0.068                         4.314  \n",
       "WF_riverview        0.210     0.177                         6.928  \n",
       "Wf_salem            0.086     0.235                        17.793  \n",
       "WF_saunders         0.455     0.135                         1.771  \n",
       "WF_smarthallow      0.357     0.156                         3.151  \n",
       "Wf_smrthlw_trb      0.075     0.056                         8.550  \n",
       "WF_starksDOWN       0.265     0.240                         7.079  \n",
       "Wf_starks           0.270     0.232                        13.821  \n",
       "Wf_thnorthdown      0.322     0.128                         5.134  \n",
       "WF_thnorthUP        0.202     0.209                        10.004  \n",
       "Wf_thnorth_trib     0.107     0.152                        10.038  \n",
       "WF_thsouthup        0.509     0.206                         3.762  \n",
       "WF_thsouth          0.313     0.305                         4.257  \n",
       "WF_yoder            0.266     0.252                         6.601  \n",
       "WF_yodertrib        0.119     0.139                        16.036  \n",
       "WF_yoderup          0.544     0.066                         3.802  \n",
       "WF_hwy82tribDOWN      NaN       NaN                           NaN  "
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "flowtracker"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "05146552-7c31-4c7f-95fd-cc92f013fab5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "# Specify the USGS gauge station code and the period of interest\n",
    "station_code = '05408000'  # Replace with the actual code of the gauge station you are interested in\n",
    "start_date = '2023-05-01'\n",
    "end_date = '2023-09-01'\n",
    "timestamp_format = '%m/%d/%Y %H:%M'\n",
    "\n",
    "# Use the nwis class to retrieve daily streamflow data for the specified station\n",
    "data = nwis.get_record(sites=station_code, service='iv', start=start_date, end=end_date, parameterCd='00060')\n",
    "data.index = pd.to_datetime(data.index, format=timestamp_format)#.tz_localize(None)\n",
    "\n",
    "# Plot the streamflow data\n",
    "plt.plot(data.index, data['00060'], label='Streamflow')\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('Streamflow (cfs)')\n",
    "plt.title(f'USGS Gauge Data - Station {station_code}')\n",
    "plt.legend()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "312cd577",
   "metadata": {},
   "source": [
    "### Get the file names for each tributary file and the boundary file, in order to adjust flows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "fe29f64b-11fd-4f60-9ee3-1d75c126a8c7",
   "metadata": {},
   "outputs": [],
   "source": [
    "#listing trib files to apply corrections\n",
    "import os\n",
    "\n",
    "def get_files(folder_path):\n",
    "    # Initialize an empty list to store file names\n",
    "    file_names = []\n",
    "    \n",
    "    # Iterate over all files in the folder\n",
    "    for filename in os.listdir(folder_path):\n",
    "        #print(f\"Checking file: {filename}\")\n",
    "\n",
    "        # Check if the filename contains 'trib'\n",
    "        if ('trib' in filename or 'boundary' in filename) and 'accretion' not in filename:\n",
    "            # Add the filename to the list\n",
    "            print(f\"Adding file: {filename}\")\n",
    "\n",
    "            file_names.append(filename)\n",
    "    return file_names\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e0805713",
   "metadata": {},
   "outputs": [],
   "source": [
    "# July function usage\n",
    "july_folder_path = os.path.join(july_hsfiles_path, 'inputs')\n",
    "july_file_names = get_files(july_folder_path)\n",
    "print(file_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b94496ab",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Adding file: bloomtrib.csv\n",
      "Adding file: boydtrib.csv\n",
      "Adding file: halltrib.csv\n",
      "Adding file: hayestrib.csv\n",
      "Adding file: hwy82downtrib.csv\n",
      "Adding file: hwy82uptrib.csv\n",
      "Adding file: mayertrib.csv\n",
      "Adding file: riverrdtrib.csv\n",
      "Adding file: rockyruntrib.csv\n",
      "Adding file: seasbranchtrib.csv\n",
      "Adding file: smarthallowtrib.csv\n",
      "Adding file: thnorthtrib.csv\n",
      "Adding file: WFK23_boundary.csv\n",
      "Adding file: yodertrib.csv\n",
      "['bloomtrib.csv', 'boydtrib.csv', 'halltrib.csv', 'hayestrib.csv', 'hwy82downtrib.csv', 'hwy82uptrib.csv', 'mayertrib.csv', 'riverrdtrib.csv', 'rockyruntrib.csv', 'seasbranchtrib.csv', 'smarthallowtrib.csv', 'thnorthtrib.csv', 'WFK23_boundary.csv', 'yodertrib.csv']\n"
     ]
    }
   ],
   "source": [
    "# June function usage\n",
    "june_folder_path = os.path.join(june_hsfiles_path, 'inputs')\n",
    "june_file_names = get_files(june_folder_path)\n",
    "print(june_file_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "121f5478",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Adding file: bloomtrib.csv\n",
      "Adding file: boydtrib.csv\n",
      "Adding file: halltrib.csv\n",
      "Adding file: hayestrib.csv\n",
      "Adding file: hwy82downtrib.csv\n",
      "Adding file: hwy82uptrib.csv\n",
      "Adding file: mayertrib.csv\n",
      "Adding file: riverrdtrib.csv\n",
      "Adding file: rockyruntrib.csv\n",
      "Adding file: seasbranchtrib.csv\n",
      "Adding file: smarthallowtrib.csv\n",
      "Adding file: thnorthtrib.csv\n",
      "Adding file: WFK23_boundary.csv\n",
      "Adding file: yodertrib.csv\n",
      "['bloomtrib.csv', 'boydtrib.csv', 'halltrib.csv', 'hayestrib.csv', 'hwy82downtrib.csv', 'hwy82uptrib.csv', 'mayertrib.csv', 'riverrdtrib.csv', 'rockyruntrib.csv', 'seasbranchtrib.csv', 'smarthallowtrib.csv', 'thnorthtrib.csv', 'WFK23_boundary.csv', 'yodertrib.csv']\n"
     ]
    }
   ],
   "source": [
    "# August function usage\n",
    "august_folder_path = os.path.join(august_hsfiles_path, 'inputs')\n",
    "august_file_names = get_files(august_folder_path)\n",
    "print(august_file_names)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66408cd4",
   "metadata": {},
   "source": [
    "### Make a dictionary that links the name of each flowtracker measurement with the correspondiing heatsource file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "ffbf9ac0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# This dictionary ties the name of each flow file to the flowtracker measurement name\n",
    "trib_dict = {'WFK23_boundary': 'WF_hayesUP', 'bloomtrib': 'Wf_bloomtrib', 'boydtrib': 'Wf_boydtrib', 'halltrib': 'Wf_haLl', 'hayestrib':'Wf_hayes_trib',\n",
    "             'hwy82downtrib':'WF_hwy82tribDOWN',  'hwy82uptrib':'Wf_hwy82tribup', 'mayertrib': 'Wf_mayertrib', 'riverrdtrib': 'Wf_riverrd_trib',\n",
    "             'rockyruntrib':'Wf_rockyrun', 'seasbranchtrib': 'Sb_conf', 'smarthallowtrib': 'Wf_smrthlw_trb', 'thnorthtrib':'Wf_thnorth_trib',\n",
    "             'yodertrib':'WF_yodertrib'}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ffd8a14",
   "metadata": {},
   "source": [
    "### Correcting each flow file based on the proportion of flow between flowtracker measurment and LaFarge USGS flow gage, writing to csv in heatsource file folder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "2c491a7e-a185-4cb6-b3b9-1772dfe7abb0",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wf_bloomtrib\n",
      "flowtracker cms: 0.001\n",
      "flowtracker date: 2023-06-28 12:00:00\n",
      "Lafarge Gage cms: 4.81386399\n",
      "                          DATETIME     FLOW1  TEMPERATURE1\n",
      "DATETIME                                                  \n",
      "2023-08-01 00:00:00  8/1/2023 0:00  0.000862     13.197221\n",
      "2023-08-01 01:00:00  8/1/2023 1:00  0.000862     13.013661\n",
      "2023-08-01 02:00:00  8/1/2023 2:00  0.000862     12.853105\n",
      "2023-08-01 03:00:00  8/1/2023 3:00  0.000862     12.703573\n",
      "2023-08-01 04:00:00  8/1/2023 4:00  0.000862     12.531036\n",
      "2023-08-01 05:00:00  8/1/2023 5:00  0.000862     12.404030\n",
      "2023-08-01 06:00:00  8/1/2023 6:00  0.000862     12.277023\n",
      "2023-08-01 07:00:00  8/1/2023 7:00  0.000862     12.184524\n",
      "2023-08-01 08:00:00  8/1/2023 8:00  0.000862     12.254018\n",
      "2023-08-01 09:00:00  8/1/2023 9:00  0.000862     12.484547\n",
      "Wf_boydtrib\n",
      "flowtracker cms: 0.042\n",
      "flowtracker date: 2023-06-22 15:00:00\n",
      "Lafarge Gage cms: 4.785547143\n",
      "                          DATETIME     FLOW1  TEMPERATURE1\n",
      "DATETIME                                                  \n",
      "2023-08-01 00:00:00  8/1/2023 0:00  0.036408        19.698\n",
      "2023-08-01 01:00:00  8/1/2023 1:00  0.036408        19.080\n",
      "2023-08-01 02:00:00  8/1/2023 2:00  0.036408        18.533\n",
      "2023-08-01 03:00:00  8/1/2023 3:00  0.036408        18.010\n",
      "2023-08-01 04:00:00  8/1/2023 4:00  0.036408        17.534\n",
      "2023-08-01 05:00:00  8/1/2023 5:00  0.036408        17.106\n",
      "2023-08-01 06:00:00  8/1/2023 6:00  0.036408        16.725\n",
      "2023-08-01 07:00:00  8/1/2023 7:00  0.036408        16.463\n",
      "2023-08-01 08:00:00  8/1/2023 8:00  0.036408        16.439\n",
      "2023-08-01 09:00:00  8/1/2023 9:00  0.036408        16.915\n",
      "Wf_haLl\n",
      "flowtracker cms: 0.032\n",
      "flowtracker date: 2023-06-23 09:00:00\n",
      "Lafarge Gage cms: 4.7572302959999995\n",
      "                          DATETIME     FLOW1  TEMPERATURE1\n",
      "DATETIME                                                  \n",
      "2023-08-01 00:00:00  8/1/2023 0:00  0.027905     16.085180\n",
      "2023-08-01 01:00:00  8/1/2023 1:00  0.027905     15.652201\n",
      "2023-08-01 02:00:00  8/1/2023 2:00  0.027905     15.292360\n",
      "2023-08-01 03:00:00  8/1/2023 3:00  0.027905     14.987409\n",
      "2023-08-01 04:00:00  8/1/2023 4:00  0.027905     14.701963\n",
      "2023-08-01 05:00:00  8/1/2023 5:00  0.027905     14.464705\n",
      "2023-08-01 06:00:00  8/1/2023 6:00  0.027905     14.278376\n",
      "2023-08-01 07:00:00  8/1/2023 7:00  0.027905     14.155552\n",
      "2023-08-01 08:00:00  8/1/2023 8:00  0.027905     14.251499\n",
      "2023-08-01 09:00:00  8/1/2023 9:00  0.027905     14.539459\n",
      "Wf_hayes_trib\n",
      "flowtracker cms: 0.058\n",
      "flowtracker date: 2023-06-22 13:00:00\n",
      "Lafarge Gage cms: 4.81386399\n",
      "                          DATETIME     FLOW1  TEMPERATURE1\n",
      "DATETIME                                                  \n",
      "2023-08-01 00:00:00  8/1/2023 0:00  0.049982        14.912\n",
      "2023-08-01 01:00:00  8/1/2023 1:00  0.049982        14.529\n",
      "2023-08-01 02:00:00  8/1/2023 2:00  0.049982        14.194\n",
      "2023-08-01 03:00:00  8/1/2023 3:00  0.049982        13.882\n",
      "2023-08-01 04:00:00  8/1/2023 4:00  0.049982        13.522\n",
      "2023-08-01 05:00:00  8/1/2023 5:00  0.049982        13.257\n",
      "2023-08-01 06:00:00  8/1/2023 6:00  0.049982        12.992\n",
      "2023-08-01 07:00:00  8/1/2023 7:00  0.049982        12.799\n",
      "2023-08-01 08:00:00  8/1/2023 8:00  0.049982        12.944\n",
      "2023-08-01 09:00:00  8/1/2023 9:00  0.049982        13.425\n",
      "WF_hwy82tribDOWN\n",
      "flowtracker cms: 0.0153\n",
      "flowtracker date: 2023-07-20 08:00:00\n",
      "Lafarge Gage cms: 4.360794438\n",
      "                          DATETIME     FLOW1  TEMPERATURE1\n",
      "DATETIME                                                  \n",
      "2023-08-01 00:00:00  8/1/2023 0:00  0.014555        16.034\n",
      "2023-08-01 01:00:00  8/1/2023 1:00  0.014555        15.485\n",
      "2023-08-01 02:00:00  8/1/2023 2:00  0.014555        14.984\n",
      "2023-08-01 03:00:00  8/1/2023 3:00  0.014555        14.529\n",
      "2023-08-01 04:00:00  8/1/2023 4:00  0.014555        14.098\n",
      "2023-08-01 05:00:00  8/1/2023 5:00  0.014555        13.762\n",
      "2023-08-01 06:00:00  8/1/2023 6:00  0.014555        13.473\n",
      "2023-08-01 07:00:00  8/1/2023 7:00  0.014555        13.281\n",
      "2023-08-01 08:00:00  8/1/2023 8:00  0.014555        13.425\n",
      "2023-08-01 09:00:00  8/1/2023 9:00  0.014555        13.858\n",
      "Wf_hwy82tribup\n",
      "flowtracker cms: 0.047\n",
      "flowtracker date: 2023-05-31 15:00:00\n",
      "Lafarge Gage cms: 5.6633694\n",
      "                          DATETIME     FLOW1  TEMPERATURE1\n",
      "DATETIME                                                  \n",
      "2023-08-01 00:00:00  8/1/2023 0:00  0.034427     15.943888\n",
      "2023-08-01 01:00:00  8/1/2023 1:00  0.034427     15.357714\n",
      "2023-08-01 02:00:00  8/1/2023 2:00  0.034427     14.851395\n",
      "2023-08-01 03:00:00  8/1/2023 3:00  0.034427     14.389793\n",
      "2023-08-01 04:00:00  8/1/2023 4:00  0.034427     13.892179\n",
      "2023-08-01 05:00:00  8/1/2023 5:00  0.034427     13.509452\n",
      "2023-08-01 06:00:00  8/1/2023 6:00  0.034427     13.149339\n",
      "2023-08-01 07:00:00  8/1/2023 7:00  0.034427     12.893087\n",
      "2023-08-01 08:00:00  8/1/2023 8:00  0.034427     13.068560\n",
      "2023-08-01 09:00:00  8/1/2023 9:00  0.034427     13.685796\n",
      "Wf_mayertrib\n",
      "flowtracker cms: 0.008\n",
      "flowtracker date: 2023-06-28 13:00:00\n",
      "Lafarge Gage cms: 4.785547143\n",
      "                          DATETIME     FLOW1  TEMPERATURE1\n",
      "DATETIME                                                  \n",
      "2023-08-01 00:00:00  8/1/2023 0:00  0.006935     13.853522\n",
      "2023-08-01 01:00:00  8/1/2023 1:00  0.006935     13.368541\n",
      "2023-08-01 02:00:00  8/1/2023 2:00  0.006935     12.959073\n",
      "2023-08-01 03:00:00  8/1/2023 3:00  0.006935     12.600656\n",
      "2023-08-01 04:00:00  8/1/2023 4:00  0.006935     12.267764\n",
      "2023-08-01 05:00:00  8/1/2023 5:00  0.006935     11.984859\n",
      "2023-08-01 06:00:00  8/1/2023 6:00  0.006935     11.754067\n",
      "2023-08-01 07:00:00  8/1/2023 7:00  0.006935     11.599852\n",
      "2023-08-01 08:00:00  8/1/2023 8:00  0.006935     11.676428\n",
      "2023-08-01 09:00:00  8/1/2023 9:00  0.006935     12.011447\n",
      "Wf_riverrd_trib\n",
      "flowtracker cms: 0.035\n",
      "flowtracker date: 2023-06-23 09:00:00\n",
      "Lafarge Gage cms: 4.7572302959999995\n",
      "                          DATETIME     FLOW1  TEMPERATURE1\n",
      "DATETIME                                                  \n",
      "2023-08-01 00:00:00  8/1/2023 0:00  0.030521     12.597108\n",
      "2023-08-01 01:00:00  8/1/2023 1:00  0.030521     12.261115\n",
      "2023-08-01 02:00:00  8/1/2023 2:00  0.030521     11.987395\n",
      "2023-08-01 03:00:00  8/1/2023 3:00  0.030521     11.763865\n",
      "2023-08-01 04:00:00  8/1/2023 4:00  0.030521     11.616364\n",
      "2023-08-01 05:00:00  8/1/2023 5:00  0.030521     11.455963\n",
      "2023-08-01 06:00:00  8/1/2023 6:00  0.030521     11.366898\n",
      "2023-08-01 07:00:00  8/1/2023 7:00  0.030521     11.321017\n",
      "2023-08-01 08:00:00  8/1/2023 8:00  0.030521     11.301713\n",
      "2023-08-01 09:00:00  8/1/2023 9:00  0.030521     11.348548\n",
      "Wf_rockyrun\n",
      "flowtracker cms: 0.082\n",
      "flowtracker date: 2023-05-31 14:00:00\n",
      "Lafarge Gage cms: 5.720003094\n",
      "                          DATETIME    FLOW1  TEMPERATURE1\n",
      "DATETIME                                                 \n",
      "2023-08-01 00:00:00  8/1/2023 0:00  0.05947        14.433\n",
      "2023-08-01 01:00:00  8/1/2023 1:00  0.05947        14.122\n",
      "2023-08-01 02:00:00  8/1/2023 2:00  0.05947        13.810\n",
      "2023-08-01 03:00:00  8/1/2023 3:00  0.05947        13.497\n",
      "2023-08-01 04:00:00  8/1/2023 4:00  0.05947        13.185\n",
      "2023-08-01 05:00:00  8/1/2023 5:00  0.05947        12.920\n",
      "2023-08-01 06:00:00  8/1/2023 6:00  0.05947        12.654\n",
      "2023-08-01 07:00:00  8/1/2023 7:00  0.05947        12.509\n",
      "2023-08-01 08:00:00  8/1/2023 8:00  0.05947        12.509\n",
      "2023-08-01 09:00:00  8/1/2023 9:00  0.05947        12.871\n",
      "Sb_conf\n",
      "flowtracker cms: 0.274\n",
      "flowtracker date: 2023-06-23 12:00:00\n",
      "Lafarge Gage cms: 4.728913449\n",
      "                          DATETIME     FLOW1  TEMPERATURE1\n",
      "DATETIME                                                  \n",
      "2023-08-01 00:00:00  8/1/2023 0:00  0.240365     16.928059\n",
      "2023-08-01 01:00:00  8/1/2023 1:00  0.240365     16.516376\n",
      "2023-08-01 02:00:00  8/1/2023 2:00  0.240365     16.153974\n",
      "2023-08-01 03:00:00  8/1/2023 3:00  0.240365     15.864894\n",
      "2023-08-01 04:00:00  8/1/2023 4:00  0.240365     15.586614\n",
      "2023-08-01 05:00:00  8/1/2023 5:00  0.240365     15.331805\n",
      "2023-08-01 06:00:00  8/1/2023 6:00  0.240365     15.115694\n",
      "2023-08-01 07:00:00  8/1/2023 7:00  0.240365     14.956332\n",
      "2023-08-01 08:00:00  8/1/2023 8:00  0.240365     15.006112\n",
      "2023-08-01 09:00:00  8/1/2023 9:00  0.240365     15.409890\n",
      "Wf_smrthlw_trb\n",
      "flowtracker cms: 0.002\n",
      "flowtracker date: 2023-06-01 08:00:00\n",
      "Lafarge Gage cms: 5.720003094\n",
      "                          DATETIME    FLOW1  TEMPERATURE1\n",
      "DATETIME                                                 \n",
      "2023-08-01 00:00:00  8/1/2023 0:00  0.00145     13.599622\n",
      "2023-08-01 01:00:00  8/1/2023 1:00  0.00145     13.290423\n",
      "2023-08-01 02:00:00  8/1/2023 2:00  0.00145     13.037644\n",
      "2023-08-01 03:00:00  8/1/2023 3:00  0.00145     12.829730\n",
      "2023-08-01 04:00:00  8/1/2023 4:00  0.00145     12.686579\n",
      "2023-08-01 05:00:00  8/1/2023 5:00  0.00145     12.535796\n",
      "2023-08-01 06:00:00  8/1/2023 6:00  0.00145     12.447517\n",
      "2023-08-01 07:00:00  8/1/2023 7:00  0.00145     12.399859\n",
      "2023-08-01 08:00:00  8/1/2023 8:00  0.00145     12.388547\n",
      "2023-08-01 09:00:00  8/1/2023 9:00  0.00145     12.448168\n",
      "Wf_thnorth_trib\n",
      "flowtracker cms: 0.015\n",
      "flowtracker date: 2023-06-01 09:00:00\n",
      "Lafarge Gage cms: 5.720003094\n",
      "                          DATETIME     FLOW1  TEMPERATURE1\n",
      "DATETIME                                                  \n",
      "2023-08-01 00:00:00  8/1/2023 0:00  0.010879        14.266\n",
      "2023-08-01 01:00:00  8/1/2023 1:00  0.010879        13.810\n",
      "2023-08-01 02:00:00  8/1/2023 2:00  0.010879        13.425\n",
      "2023-08-01 03:00:00  8/1/2023 3:00  0.010879        13.088\n",
      "2023-08-01 04:00:00  8/1/2023 4:00  0.010879        12.775\n",
      "2023-08-01 05:00:00  8/1/2023 5:00  0.010879        12.509\n",
      "2023-08-01 06:00:00  8/1/2023 6:00  0.010879        12.292\n",
      "2023-08-01 07:00:00  8/1/2023 7:00  0.010879        12.147\n",
      "2023-08-01 08:00:00  8/1/2023 8:00  0.010879        12.219\n",
      "2023-08-01 09:00:00  8/1/2023 9:00  0.010879        12.534\n",
      "WF_hayesUP\n",
      "flowtracker cms: 0.348\n",
      "flowtracker date: 2023-06-22 16:00:00\n",
      "Lafarge Gage cms: 4.81386399\n",
      "                          DATETIME    INFLOW  TEMPERATURE\n",
      "DATETIME                                                 \n",
      "2023-08-01 00:00:00  8/1/2023 0:00  0.299894       19.770\n",
      "2023-08-01 01:00:00  8/1/2023 1:00  0.299894       19.127\n",
      "2023-08-01 02:00:00  8/1/2023 2:00  0.299894       18.533\n",
      "2023-08-01 03:00:00  8/1/2023 3:00  0.299894       18.010\n",
      "2023-08-01 04:00:00  8/1/2023 4:00  0.299894       17.534\n",
      "2023-08-01 05:00:00  8/1/2023 5:00  0.299894       17.130\n",
      "2023-08-01 06:00:00  8/1/2023 6:00  0.299894       16.773\n",
      "2023-08-01 07:00:00  8/1/2023 7:00  0.299894       16.511\n",
      "2023-08-01 08:00:00  8/1/2023 8:00  0.299894       16.415\n",
      "2023-08-01 09:00:00  8/1/2023 9:00  0.299894       16.701\n",
      "WF_yodertrib\n",
      "flowtracker cms: 0.03\n",
      "flowtracker date: 2023-07-19 09:00:00\n",
      "Lafarge Gage cms: 4.502378673\n",
      "                          DATETIME     FLOW1  TEMPERATURE1\n",
      "DATETIME                                                  \n",
      "2023-08-01 00:00:00  8/1/2023 0:00  0.027642     14.189881\n",
      "2023-08-01 01:00:00  8/1/2023 1:00  0.027642     13.931010\n",
      "2023-08-01 02:00:00  8/1/2023 2:00  0.027642     13.717470\n",
      "2023-08-01 03:00:00  8/1/2023 3:00  0.027642     13.538658\n",
      "2023-08-01 04:00:00  8/1/2023 4:00  0.027642     13.402908\n",
      "2023-08-01 05:00:00  8/1/2023 5:00  0.027642     13.269859\n",
      "2023-08-01 06:00:00  8/1/2023 6:00  0.027642     13.182402\n",
      "2023-08-01 07:00:00  8/1/2023 7:00  0.027642     13.130842\n",
      "2023-08-01 08:00:00  8/1/2023 8:00  0.027642     13.135210\n",
      "2023-08-01 09:00:00  8/1/2023 9:00  0.027642     13.220564\n"
     ]
    }
   ],
   "source": [
    "# Iterate over each file name in the file_names list\n",
    "for i in august_file_names:\n",
    "    # Create the full file path for the current file\n",
    "    file = os.path.join(august_hsfiles_path,'inputs', i)\n",
    "    # Remove the last 4 characters from the file name (usually the file extension)\n",
    "    name = i[:-4]\n",
    "    # Read the CSV file into a pandas DataFrame\n",
    "    csv = pd.read_csv(file)\n",
    "    # Convert the 'DATETIME' column to datetime and set it as the DataFrame index\n",
    "    csv.index = pd.to_datetime(csv['DATETIME'])\n",
    "    # Get the flowtracker measurement name from trib_dict using the current name\n",
    "    flowtracker_measurment_name = trib_dict[name]\n",
    "    # Print the flowtracker measurement name\n",
    "    print(flowtracker_measurment_name)\n",
    "    # Get the index of the row with the matching name in the flowtracker DataFrame\n",
    "    row_index = flowtracker.loc[flowtracker.index == flowtracker_measurment_name].index[0]\n",
    "    # Get the measured flow value from the flowtracker DataFrame\n",
    "    measured_flow = flowtracker.at[row_index, 'Discharge']\n",
    "    # Print the measured flow value\n",
    "    print('flowtracker cms: ' + str(measured_flow))\n",
    "    # Get the flow date from the flowtracker DataFrame\n",
    "    flow_date = flowtracker.at[row_index, 'Datetime']\n",
    "    timestamp = pd.to_datetime(flow_date, format='%m/%d/%Y %H:%M')#.tz_localize(None)\n",
    "    rounded_timestamp = timestamp.round('H')\n",
    "\n",
    "\n",
    "   # flow_date = pd.to_datetime(flow_date, format='%m/%d/%Y %H:%M')\n",
    "\n",
    "    # Print the flow date\n",
    "    print('flowtracker date: ' + str(rounded_timestamp))\n",
    "    # Convert the flow rate at a specific time to cubic meters per second\n",
    "    lafarge_cms = data.loc[str(rounded_timestamp)]['00060'] * .028316847\n",
    "    # Print the converted flow rate\n",
    "    print('Lafarge Gage cms: ' + str(lafarge_cms))\n",
    "    # Calculate the proportion of measured flow to the Lafarge Gage flow rate\n",
    "    proportion = measured_flow / lafarge_cms\n",
    "    # Resample the data to daily mean values and convert to cubic meters per second\n",
    "    daily_mean_cms = pd.DataFrame(data['00060'].resample('D').mean() * .028316847)\n",
    "    # Apply the proportion to get the corrected flow\n",
    "    daily_mean_cms['corrected_flow'] = daily_mean_cms['00060'] * proportion\n",
    "\n",
    "    # Resample to hourly data and forward-fill missing values\n",
    "    daily_mean_cms = daily_mean_cms.resample('H').ffill()\n",
    "    # Change things so that timezone information lines up and is compatible\n",
    "    if daily_mean_cms.index.tz is None:\n",
    "        # Localize the daily_mean_cms index to no timezone\n",
    "        daily_mean_cms.index = daily_mean_cms.index.tz_localize(None)\n",
    "    else:\n",
    "        # Convert the daily_mean_cms index to the boundary file's timezone\n",
    "        daily_mean_cms.index = daily_mean_cms.index.tz_convert(csv.index.tz)\n",
    "\n",
    "    # Join the summer long boundary condition file with the heatsoure time period\n",
    "    result = csv.merge(daily_mean_cms, how='left', left_index=True, right_index=True)\n",
    "    if 'FLOW1' in csv.columns:\n",
    "        csv.drop(columns=['FLOW1'], inplace=True)\n",
    "    # Make the discharge in the boundary condition csv equal the corrected flows which we determined earlier with the USGS gage\n",
    "    if 'boundary' in i:\n",
    "        csv['INFLOW'] = result['corrected_flow']\n",
    "    else:\n",
    "        #csv.drop(columns = ['FLOW1'], inplace = True)\n",
    "        csv['FLOW1'] = result['corrected_flow']\n",
    "    # Print the first 10 rows of the updated csv DataFrame\n",
    "    columns = list(csv.columns)\n",
    "    # need to make sure columns are in the correct order, was getting an error from heatsource otherwise\n",
    "    if 'FLOW1' in columns and 'TEMPERATURE1' in columns:\n",
    "        columns.insert(columns.index('TEMPERATURE1'), columns.pop(columns.index('FLOW1')))\n",
    "        csv = csv[columns]\n",
    "    print(csv.head(10))\n",
    "    # Save the updated csv DataFrame back to the file without writing the index\n",
    "    csv.to_csv(file, index=False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "8c4fb9f8",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATETIME</th>\n",
       "      <th>FLOW1</th>\n",
       "      <th>TEMPERATURE1</th>\n",
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       "    <tr>\n",
       "      <th>DATETIME</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-08-01 00:00:00</th>\n",
       "      <td>8/1/2023 0:00</td>\n",
       "      <td>0.027642</td>\n",
       "      <td>14.189881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-01 01:00:00</th>\n",
       "      <td>8/1/2023 1:00</td>\n",
       "      <td>0.027642</td>\n",
       "      <td>13.931010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-01 02:00:00</th>\n",
       "      <td>8/1/2023 2:00</td>\n",
       "      <td>0.027642</td>\n",
       "      <td>13.717470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-01 03:00:00</th>\n",
       "      <td>8/1/2023 3:00</td>\n",
       "      <td>0.027642</td>\n",
       "      <td>13.538658</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-01 04:00:00</th>\n",
       "      <td>8/1/2023 4:00</td>\n",
       "      <td>0.027642</td>\n",
       "      <td>13.402908</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-05 20:00:00</th>\n",
       "      <td>8/5/2023 20:00</td>\n",
       "      <td>0.026557</td>\n",
       "      <td>15.759669</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-05 21:00:00</th>\n",
       "      <td>8/5/2023 21:00</td>\n",
       "      <td>0.026557</td>\n",
       "      <td>15.520754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-05 22:00:00</th>\n",
       "      <td>8/5/2023 22:00</td>\n",
       "      <td>0.026557</td>\n",
       "      <td>15.218048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-05 23:00:00</th>\n",
       "      <td>8/5/2023 23:00</td>\n",
       "      <td>0.026557</td>\n",
       "      <td>14.937174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-06 00:00:00</th>\n",
       "      <td>8/6/2023 0:00</td>\n",
       "      <td>0.026110</td>\n",
       "      <td>14.662634</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>121 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                           DATETIME     FLOW1  TEMPERATURE1\n",
       "DATETIME                                                   \n",
       "2023-08-01 00:00:00   8/1/2023 0:00  0.027642     14.189881\n",
       "2023-08-01 01:00:00   8/1/2023 1:00  0.027642     13.931010\n",
       "2023-08-01 02:00:00   8/1/2023 2:00  0.027642     13.717470\n",
       "2023-08-01 03:00:00   8/1/2023 3:00  0.027642     13.538658\n",
       "2023-08-01 04:00:00   8/1/2023 4:00  0.027642     13.402908\n",
       "...                             ...       ...           ...\n",
       "2023-08-05 20:00:00  8/5/2023 20:00  0.026557     15.759669\n",
       "2023-08-05 21:00:00  8/5/2023 21:00  0.026557     15.520754\n",
       "2023-08-05 22:00:00  8/5/2023 22:00  0.026557     15.218048\n",
       "2023-08-05 23:00:00  8/5/2023 23:00  0.026557     14.937174\n",
       "2023-08-06 00:00:00   8/6/2023 0:00  0.026110     14.662634\n",
       "\n",
       "[121 rows x 3 columns]"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e8475862",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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