From fdc87bb3a02b456a053a23074a976cd76de82f22 Mon Sep 17 00:00:00 2001
From: Bousquin <Bousquin.Justin@epa.gov>
Date: Tue, 6 Feb 2024 20:36:40 -0600
Subject: [PATCH] Update data results for 2/6/2024

---
 demos/Harmonize_GOM.ipynb | 2427 +++++++++++++++++++------------------
 1 file changed, 1214 insertions(+), 1213 deletions(-)

diff --git a/demos/Harmonize_GOM.ipynb b/demos/Harmonize_GOM.ipynb
index a8ca791..0b65a01 100644
--- a/demos/Harmonize_GOM.ipynb
+++ b/demos/Harmonize_GOM.ipynb
@@ -75,7 +75,7 @@
    "source": [
     "# Read geometry for Area of Interest from geojson file url\n",
     "# NOTE: alternatively you can direct it to a local shapefile\n",
-    "aoi_url = r'https://raw.githubusercontent.com/USEPA/harmonize-wq/demo_refresh/harmonize_wq/tests/data/NCCA_dissolved_GOM.geojson'"
+    "aoi_url = r'https://raw.githubusercontent.com/USEPA/harmonize-wq/new_release_0-3-8/harmonize_wq/tests/data/NCCA_dissolved_GOM.geojson'"
    ]
   },
   {
@@ -820,12 +820,12 @@
        "      <th>0</th>\n",
        "      <td>TCEQMAIN</td>\n",
        "      <td>Texas Commission on Environmental Quality</td>\n",
-       "      <td>TCEQMAIN-14363288</td>\n",
-       "      <td>2013-10-10</td>\n",
+       "      <td>TCEQMAIN-13702013</td>\n",
+       "      <td>2013-04-29</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>TCEQMAIN-11455</td>\n",
-       "      <td>STORET-422883712</td>\n",
+       "      <td>TCEQMAIN-15224</td>\n",
+       "      <td>STORET-422578803</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -844,12 +844,12 @@
        "      <th>1</th>\n",
        "      <td>TCEQMAIN</td>\n",
        "      <td>Texas Commission on Environmental Quality</td>\n",
-       "      <td>TCEQMAIN-13702013</td>\n",
-       "      <td>2013-04-29</td>\n",
+       "      <td>TCEQMAIN-13947279</td>\n",
+       "      <td>2013-07-11</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>TCEQMAIN-15224</td>\n",
-       "      <td>STORET-422578803</td>\n",
+       "      <td>TCEQMAIN-11446</td>\n",
+       "      <td>STORET-422881708</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -868,12 +868,12 @@
        "      <th>2</th>\n",
        "      <td>TCEQMAIN</td>\n",
        "      <td>Texas Commission on Environmental Quality</td>\n",
-       "      <td>TCEQMAIN-13947279</td>\n",
-       "      <td>2013-07-11</td>\n",
+       "      <td>TCEQMAIN-14329114</td>\n",
+       "      <td>2013-10-08</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>TCEQMAIN-11446</td>\n",
-       "      <td>STORET-422881708</td>\n",
+       "      <td>TCEQMAIN-15906</td>\n",
+       "      <td>STORET-422797456</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -892,12 +892,12 @@
        "      <th>3</th>\n",
        "      <td>TCEQMAIN</td>\n",
        "      <td>Texas Commission on Environmental Quality</td>\n",
-       "      <td>TCEQMAIN-14117837</td>\n",
-       "      <td>2013-01-28</td>\n",
+       "      <td>TCEQMAIN-13899297</td>\n",
+       "      <td>2013-08-01</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>TCEQMAIN-11370</td>\n",
-       "      <td>STORET-422872173</td>\n",
+       "      <td>TCEQMAIN-11287</td>\n",
+       "      <td>STORET-422829817</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -916,12 +916,12 @@
        "      <th>4</th>\n",
        "      <td>TCEQMAIN</td>\n",
        "      <td>Texas Commission on Environmental Quality</td>\n",
-       "      <td>TCEQMAIN-14208371</td>\n",
-       "      <td>2013-07-16</td>\n",
+       "      <td>TCEQMAIN-13702703</td>\n",
+       "      <td>2013-05-14</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>TCEQMAIN-16659</td>\n",
-       "      <td>STORET-423043742</td>\n",
+       "      <td>TCEQMAIN-15216</td>\n",
+       "      <td>STORET-422577293</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -961,15 +961,15 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248058</th>\n",
+       "      <th>249329</th>\n",
        "      <td>USGS-TX</td>\n",
        "      <td>USGS Texas Water Science Center</td>\n",
-       "      <td>nwistx.01.02302746</td>\n",
-       "      <td>2023-07-18</td>\n",
-       "      <td>11:45:00</td>\n",
-       "      <td>CDT</td>\n",
-       "      <td>USGS-08042554</td>\n",
-       "      <td>NWIS-125841792</td>\n",
+       "      <td>nwistx.01.02400657</td>\n",
+       "      <td>2024-01-25</td>\n",
+       "      <td>08:35:00</td>\n",
+       "      <td>CST</td>\n",
+       "      <td>USGS-08042546</td>\n",
+       "      <td>NWIS-126809215</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -985,15 +985,15 @@
        "      <td>NWIS</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248059</th>\n",
+       "      <th>249330</th>\n",
        "      <td>USGS-TX</td>\n",
        "      <td>USGS Texas Water Science Center</td>\n",
-       "      <td>nwistx.01.02302749</td>\n",
-       "      <td>2023-07-18</td>\n",
-       "      <td>12:45:00</td>\n",
-       "      <td>CDT</td>\n",
+       "      <td>nwistx.01.02400657</td>\n",
+       "      <td>2024-01-25</td>\n",
+       "      <td>08:35:00</td>\n",
+       "      <td>CST</td>\n",
        "      <td>USGS-08042546</td>\n",
-       "      <td>NWIS-125842112</td>\n",
+       "      <td>NWIS-126809227</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -1009,15 +1009,15 @@
        "      <td>NWIS</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248060</th>\n",
+       "      <th>249331</th>\n",
        "      <td>USGS-TX</td>\n",
        "      <td>USGS Texas Water Science Center</td>\n",
-       "      <td>nwistx.01.02302749</td>\n",
-       "      <td>2023-07-18</td>\n",
-       "      <td>12:45:00</td>\n",
-       "      <td>CDT</td>\n",
-       "      <td>USGS-08042546</td>\n",
-       "      <td>NWIS-125842120</td>\n",
+       "      <td>nwistx.01.02400659</td>\n",
+       "      <td>2024-01-25</td>\n",
+       "      <td>12:35:00</td>\n",
+       "      <td>CST</td>\n",
+       "      <td>USGS-08042554</td>\n",
+       "      <td>NWIS-126809095</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -1033,15 +1033,15 @@
        "      <td>NWIS</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248061</th>\n",
+       "      <th>249332</th>\n",
        "      <td>USGS-TX</td>\n",
        "      <td>USGS Texas Water Science Center</td>\n",
-       "      <td>nwistx.01.02302749</td>\n",
-       "      <td>2023-07-18</td>\n",
-       "      <td>12:45:00</td>\n",
-       "      <td>CDT</td>\n",
-       "      <td>USGS-08042546</td>\n",
-       "      <td>NWIS-125842125</td>\n",
+       "      <td>nwistx.01.02400659</td>\n",
+       "      <td>2024-01-25</td>\n",
+       "      <td>12:35:00</td>\n",
+       "      <td>CST</td>\n",
+       "      <td>USGS-08042554</td>\n",
+       "      <td>NWIS-126809105</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -1057,15 +1057,15 @@
        "      <td>NWIS</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248062</th>\n",
+       "      <th>249333</th>\n",
        "      <td>USGS-TX</td>\n",
        "      <td>USGS Texas Water Science Center</td>\n",
-       "      <td>nwistx.01.02302749</td>\n",
-       "      <td>2023-07-18</td>\n",
-       "      <td>12:45:00</td>\n",
-       "      <td>CDT</td>\n",
-       "      <td>USGS-08042546</td>\n",
-       "      <td>NWIS-125842127</td>\n",
+       "      <td>nwistx.01.02400659</td>\n",
+       "      <td>2024-01-25</td>\n",
+       "      <td>12:35:00</td>\n",
+       "      <td>CST</td>\n",
+       "      <td>USGS-08042554</td>\n",
+       "      <td>NWIS-126809117</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -1082,7 +1082,7 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>248063 rows × 78 columns</p>\n",
+       "<p>249334 rows × 78 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
@@ -1093,50 +1093,50 @@
        "3                    TCEQMAIN  Texas Commission on Environmental Quality   \n",
        "4                    TCEQMAIN  Texas Commission on Environmental Quality   \n",
        "...                       ...                                        ...   \n",
-       "248058                USGS-TX            USGS Texas Water Science Center   \n",
-       "248059                USGS-TX            USGS Texas Water Science Center   \n",
-       "248060                USGS-TX            USGS Texas Water Science Center   \n",
-       "248061                USGS-TX            USGS Texas Water Science Center   \n",
-       "248062                USGS-TX            USGS Texas Water Science Center   \n",
+       "249329                USGS-TX            USGS Texas Water Science Center   \n",
+       "249330                USGS-TX            USGS Texas Water Science Center   \n",
+       "249331                USGS-TX            USGS Texas Water Science Center   \n",
+       "249332                USGS-TX            USGS Texas Water Science Center   \n",
+       "249333                USGS-TX            USGS Texas Water Science Center   \n",
        "\n",
        "        ActivityIdentifier ActivityStartDate ActivityStartTime/Time  \\\n",
-       "0        TCEQMAIN-14363288        2013-10-10                    NaN   \n",
-       "1        TCEQMAIN-13702013        2013-04-29                    NaN   \n",
-       "2        TCEQMAIN-13947279        2013-07-11                    NaN   \n",
-       "3        TCEQMAIN-14117837        2013-01-28                    NaN   \n",
-       "4        TCEQMAIN-14208371        2013-07-16                    NaN   \n",
+       "0        TCEQMAIN-13702013        2013-04-29                    NaN   \n",
+       "1        TCEQMAIN-13947279        2013-07-11                    NaN   \n",
+       "2        TCEQMAIN-14329114        2013-10-08                    NaN   \n",
+       "3        TCEQMAIN-13899297        2013-08-01                    NaN   \n",
+       "4        TCEQMAIN-13702703        2013-05-14                    NaN   \n",
        "...                    ...               ...                    ...   \n",
-       "248058  nwistx.01.02302746        2023-07-18               11:45:00   \n",
-       "248059  nwistx.01.02302749        2023-07-18               12:45:00   \n",
-       "248060  nwistx.01.02302749        2023-07-18               12:45:00   \n",
-       "248061  nwistx.01.02302749        2023-07-18               12:45:00   \n",
-       "248062  nwistx.01.02302749        2023-07-18               12:45:00   \n",
+       "249329  nwistx.01.02400657        2024-01-25               08:35:00   \n",
+       "249330  nwistx.01.02400657        2024-01-25               08:35:00   \n",
+       "249331  nwistx.01.02400659        2024-01-25               12:35:00   \n",
+       "249332  nwistx.01.02400659        2024-01-25               12:35:00   \n",
+       "249333  nwistx.01.02400659        2024-01-25               12:35:00   \n",
        "\n",
        "       ActivityStartTime/TimeZoneCode MonitoringLocationIdentifier  \\\n",
-       "0                                 NaN               TCEQMAIN-11455   \n",
-       "1                                 NaN               TCEQMAIN-15224   \n",
-       "2                                 NaN               TCEQMAIN-11446   \n",
-       "3                                 NaN               TCEQMAIN-11370   \n",
-       "4                                 NaN               TCEQMAIN-16659   \n",
+       "0                                 NaN               TCEQMAIN-15224   \n",
+       "1                                 NaN               TCEQMAIN-11446   \n",
+       "2                                 NaN               TCEQMAIN-15906   \n",
+       "3                                 NaN               TCEQMAIN-11287   \n",
+       "4                                 NaN               TCEQMAIN-15216   \n",
        "...                               ...                          ...   \n",
-       "248058                            CDT                USGS-08042554   \n",
-       "248059                            CDT                USGS-08042546   \n",
-       "248060                            CDT                USGS-08042546   \n",
-       "248061                            CDT                USGS-08042546   \n",
-       "248062                            CDT                USGS-08042546   \n",
+       "249329                            CST                USGS-08042546   \n",
+       "249330                            CST                USGS-08042546   \n",
+       "249331                            CST                USGS-08042554   \n",
+       "249332                            CST                USGS-08042554   \n",
+       "249333                            CST                USGS-08042554   \n",
        "\n",
        "        ResultIdentifier  DataLoggerLine ResultDetectionConditionText  ...  \\\n",
-       "0       STORET-422883712             NaN                          NaN  ...   \n",
-       "1       STORET-422578803             NaN                          NaN  ...   \n",
-       "2       STORET-422881708             NaN                          NaN  ...   \n",
-       "3       STORET-422872173             NaN                          NaN  ...   \n",
-       "4       STORET-423043742             NaN                          NaN  ...   \n",
+       "0       STORET-422578803             NaN                          NaN  ...   \n",
+       "1       STORET-422881708             NaN                          NaN  ...   \n",
+       "2       STORET-422797456             NaN                          NaN  ...   \n",
+       "3       STORET-422829817             NaN                          NaN  ...   \n",
+       "4       STORET-422577293             NaN                          NaN  ...   \n",
        "...                  ...             ...                          ...  ...   \n",
-       "248058    NWIS-125841792             NaN                          NaN  ...   \n",
-       "248059    NWIS-125842112             NaN                          NaN  ...   \n",
-       "248060    NWIS-125842120             NaN                          NaN  ...   \n",
-       "248061    NWIS-125842125             NaN                          NaN  ...   \n",
-       "248062    NWIS-125842127             NaN                          NaN  ...   \n",
+       "249329    NWIS-126809215             NaN                          NaN  ...   \n",
+       "249330    NWIS-126809227             NaN                          NaN  ...   \n",
+       "249331    NWIS-126809095             NaN                          NaN  ...   \n",
+       "249332    NWIS-126809105             NaN                          NaN  ...   \n",
+       "249333    NWIS-126809117             NaN                          NaN  ...   \n",
        "\n",
        "       AnalysisEndTime/TimeZoneCode ResultLaboratoryCommentCode  \\\n",
        "0                               NaN                         NaN   \n",
@@ -1145,11 +1145,11 @@
        "3                               NaN                         NaN   \n",
        "4                               NaN                         NaN   \n",
        "...                             ...                         ...   \n",
-       "248058                          NaN                         NaN   \n",
-       "248059                          NaN                         NaN   \n",
-       "248060                          NaN                         NaN   \n",
-       "248061                          NaN                         NaN   \n",
-       "248062                          NaN                         NaN   \n",
+       "249329                          NaN                         NaN   \n",
+       "249330                          NaN                         NaN   \n",
+       "249331                          NaN                         NaN   \n",
+       "249332                          NaN                         NaN   \n",
+       "249333                          NaN                         NaN   \n",
        "\n",
        "       ResultLaboratoryCommentText  ResultDetectionQuantitationLimitUrl  \\\n",
        "0                              NaN                                  NaN   \n",
@@ -1158,11 +1158,11 @@
        "3                              NaN                                  NaN   \n",
        "4                              NaN                                  NaN   \n",
        "...                            ...                                  ...   \n",
-       "248058                         NaN                                  NaN   \n",
-       "248059                         NaN                                  NaN   \n",
-       "248060                         NaN                                  NaN   \n",
-       "248061                         NaN                                  NaN   \n",
-       "248062                         NaN                                  NaN   \n",
+       "249329                         NaN                                  NaN   \n",
+       "249330                         NaN                                  NaN   \n",
+       "249331                         NaN                                  NaN   \n",
+       "249332                         NaN                                  NaN   \n",
+       "249333                         NaN                                  NaN   \n",
        "\n",
        "       LaboratoryAccreditationIndicator LaboratoryAccreditationAuthorityName  \\\n",
        "0                                   NaN                                  NaN   \n",
@@ -1171,11 +1171,11 @@
        "3                                   NaN                                  NaN   \n",
        "4                                   NaN                                  NaN   \n",
        "...                                 ...                                  ...   \n",
-       "248058                              NaN                                  NaN   \n",
-       "248059                              NaN                                  NaN   \n",
-       "248060                              NaN                                  NaN   \n",
-       "248061                              NaN                                  NaN   \n",
-       "248062                              NaN                                  NaN   \n",
+       "249329                              NaN                                  NaN   \n",
+       "249330                              NaN                                  NaN   \n",
+       "249331                              NaN                                  NaN   \n",
+       "249332                              NaN                                  NaN   \n",
+       "249333                              NaN                                  NaN   \n",
        "\n",
        "       TaxonomistAccreditationIndicator TaxonomistAccreditationAuthorityName  \\\n",
        "0                                   NaN                                  NaN   \n",
@@ -1184,11 +1184,11 @@
        "3                                   NaN                                  NaN   \n",
        "4                                   NaN                                  NaN   \n",
        "...                                 ...                                  ...   \n",
-       "248058                              NaN                                  NaN   \n",
-       "248059                              NaN                                  NaN   \n",
-       "248060                              NaN                                  NaN   \n",
-       "248061                              NaN                                  NaN   \n",
-       "248062                              NaN                                  NaN   \n",
+       "249329                              NaN                                  NaN   \n",
+       "249330                              NaN                                  NaN   \n",
+       "249331                              NaN                                  NaN   \n",
+       "249332                              NaN                                  NaN   \n",
+       "249333                              NaN                                  NaN   \n",
        "\n",
        "       LabSamplePreparationUrl ProviderName  \n",
        "0                          NaN       STORET  \n",
@@ -1197,13 +1197,13 @@
        "3                          NaN       STORET  \n",
        "4                          NaN       STORET  \n",
        "...                        ...          ...  \n",
-       "248058                     NaN         NWIS  \n",
-       "248059                     NaN         NWIS  \n",
-       "248060                     NaN         NWIS  \n",
-       "248061                     NaN         NWIS  \n",
-       "248062                     NaN         NWIS  \n",
+       "249329                     NaN         NWIS  \n",
+       "249330                     NaN         NWIS  \n",
+       "249331                     NaN         NWIS  \n",
+       "249332                     NaN         NWIS  \n",
+       "249333                     NaN         NWIS  \n",
        "\n",
-       "[248063 rows x 78 columns]"
+       "[249334 rows x 78 columns]"
       ]
      },
      "execution_count": 12,
@@ -1236,7 +1236,7 @@
     },
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -1274,56 +1274,68 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\harmonize_wq\\harmonize.py:131: UserWarning: WARNING: 'None' UNDEFINED UNIT for E_coli\n",
+      "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\harmonize_wq\\wq_data.py:329: UserWarning: WARNING: 'ug/cm2' UNDEFINED UNIT for Chlorophyll\n",
       "  warn(\"WARNING: \" + problem)\n",
       "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\pandas\\core\\dtypes\\cast.py:1784: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray.\n",
       "  result[:] = values\n",
-      "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\harmonize_wq\\harmonize.py:645: UserWarning: WARNING: 'MPN/100mL' converted to NaN\n",
-      "  warn(\"WARNING: '{}' converted to NaN\".format(unit))\n",
-      "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\harmonize_wq\\harmonize.py:645: UserWarning: WARNING: 'CFU/100mL' converted to NaN\n",
-      "  warn(\"WARNING: '{}' converted to NaN\".format(unit))\n",
-      "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\harmonize_wq\\harmonize.py:645: UserWarning: WARNING: 'hours' converted to NaN\n",
-      "  warn(\"WARNING: '{}' converted to NaN\".format(unit))\n",
       "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\pandas\\core\\dtypes\\cast.py:1784: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray.\n",
       "  result[:] = values\n",
       "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\pandas\\core\\dtypes\\cast.py:1784: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray.\n",
       "  result[:] = values\n",
-      "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\harmonize_wq\\harmonize.py:131: UserWarning: WARNING: 'ug/cm2' UNDEFINED UNIT for Chlorophyll\n",
-      "  warn(\"WARNING: \" + problem)\n",
       "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\pandas\\core\\dtypes\\cast.py:1784: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray.\n",
       "  result[:] = values\n",
-      "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\harmonize_wq\\harmonize.py:645: UserWarning: WARNING: 'g / H2O' converted to NaN\n",
-      "  warn(\"WARNING: '{}' converted to NaN\".format(unit))\n",
+      "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\harmonize_wq\\wq_data.py:329: UserWarning: WARNING: 'None' UNDEFINED UNIT for E_coli\n",
+      "  warn(\"WARNING: \" + problem)\n",
+      "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\harmonize_wq\\harmonize.py:142: UserWarning: WARNING: 'MPN/100mL' converted to NaN\n",
+      "  warn(f\"WARNING: '{unit}' converted to NaN\")\n",
+      "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\harmonize_wq\\harmonize.py:142: UserWarning: WARNING: 'CFU/100mL' converted to NaN\n",
+      "  warn(f\"WARNING: '{unit}' converted to NaN\")\n",
       "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\pandas\\core\\dtypes\\cast.py:1784: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray.\n",
       "  result[:] = values\n",
+      "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\harmonize_wq\\harmonize.py:142: UserWarning: WARNING: 'hours' converted to NaN\n",
+      "  warn(f\"WARNING: '{unit}' converted to NaN\")\n",
+      "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\harmonize_wq\\wq_data.py:329: UserWarning: WARNING: 'None' UNDEFINED UNIT for Fecal_Coliform\n",
+      "  warn(\"WARNING: \" + problem)\n",
       "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\pandas\\core\\dtypes\\cast.py:1784: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray.\n",
       "  result[:] = values\n",
+      "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\harmonize_wq\\harmonize.py:142: UserWarning: WARNING: 'CFU/100mL' converted to NaN\n",
+      "  warn(f\"WARNING: '{unit}' converted to NaN\")\n",
       "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\pandas\\core\\dtypes\\cast.py:1784: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray.\n",
       "  result[:] = values\n",
-      "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\harmonize_wq\\harmonize.py:645: UserWarning: WARNING: 'nu' converted to NaN\n",
-      "  warn(\"WARNING: '{}' converted to NaN\".format(unit))\n",
       "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\pandas\\core\\dtypes\\cast.py:1784: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray.\n",
       "  result[:] = values\n",
-      "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\harmonize_wq\\harmonize.py:131: UserWarning: WARNING: 'None' UNDEFINED UNIT for Fecal_Coliform\n",
-      "  warn(\"WARNING: \" + problem)\n",
       "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\pandas\\core\\dtypes\\cast.py:1784: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray.\n",
-      "  result[:] = values\n",
-      "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\harmonize_wq\\harmonize.py:645: UserWarning: WARNING: 'CFU/100mL' converted to NaN\n",
-      "  warn(\"WARNING: '{}' converted to NaN\".format(unit))\n",
+      "  result[:] = values\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2 Phosphorus sample fractions not in frac_dict\n",
+      "2 Phosphorus sample fractions not in frac_dict found in expected domains, mapped to \"Other_Phosphorus\"\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
       "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\pandas\\core\\dtypes\\cast.py:1784: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray.\n",
       "  result[:] = values\n",
+      "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\harmonize_wq\\harmonize.py:142: UserWarning: WARNING: 'nu' converted to NaN\n",
+      "  warn(f\"WARNING: '{unit}' converted to NaN\")\n",
+      "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\harmonize_wq\\harmonize.py:142: UserWarning: WARNING: 'g / H2O' converted to NaN\n",
+      "  warn(f\"WARNING: '{unit}' converted to NaN\")\n",
       "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\pandas\\core\\dtypes\\cast.py:1784: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray.\n",
       "  result[:] = values\n",
-      "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\harmonize_wq\\harmonize.py:131: UserWarning: WARNING: 'None' UNDEFINED UNIT for Turbidity\n",
+      "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\harmonize_wq\\wq_data.py:329: UserWarning: WARNING: 'None' UNDEFINED UNIT for Turbidity\n",
       "  warn(\"WARNING: \" + problem)\n",
       "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\pandas\\core\\dtypes\\cast.py:1784: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray.\n",
       "  result[:] = values\n",
       "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\pandas\\core\\dtypes\\cast.py:1784: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray.\n",
       "  result[:] = values\n",
-      "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\harmonize_wq\\harmonize.py:645: UserWarning: WARNING: 'nu' converted to NaN\n",
-      "  warn(\"WARNING: '{}' converted to NaN\".format(unit))\n",
-      "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\pandas\\core\\dtypes\\cast.py:1784: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray.\n",
-      "  result[:] = values\n"
+      "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\harmonize_wq\\harmonize.py:142: UserWarning: WARNING: 'nu' converted to NaN\n",
+      "  warn(f\"WARNING: '{unit}' converted to NaN\")\n"
      ]
     },
     {
@@ -1358,16 +1370,16 @@
        "      <th>DataLoggerLine</th>\n",
        "      <th>ResultDetectionConditionText</th>\n",
        "      <th>...</th>\n",
-       "      <th>DO</th>\n",
-       "      <th>Fecal_Coliform</th>\n",
+       "      <th>Carbon</th>\n",
        "      <th>Phosphorus</th>\n",
        "      <th>TP_Phosphorus</th>\n",
        "      <th>TDP_Phosphorus</th>\n",
        "      <th>Other_Phosphorus</th>\n",
+       "      <th>Salinity</th>\n",
+       "      <th>Sediment</th>\n",
        "      <th>Temperature</th>\n",
        "      <th>Turbidity</th>\n",
-       "      <th>Salinity</th>\n",
-       "      <th>Conductivity</th>\n",
+       "      <th>pH</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
@@ -1375,21 +1387,21 @@
        "      <th>0</th>\n",
        "      <td>TCEQMAIN</td>\n",
        "      <td>Texas Commission on Environmental Quality</td>\n",
-       "      <td>TCEQMAIN-14363288</td>\n",
-       "      <td>2013-10-10</td>\n",
+       "      <td>TCEQMAIN-13702013</td>\n",
+       "      <td>2013-04-29</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>TCEQMAIN-11455</td>\n",
-       "      <td>STORET-422883712</td>\n",
+       "      <td>TCEQMAIN-15224</td>\n",
+       "      <td>STORET-422578803</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>0.09 milligram / liter</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.19 milligram / liter</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>0.09 milligram / liter</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.19 milligram / liter</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -1399,44 +1411,44 @@
        "      <th>1</th>\n",
        "      <td>TCEQMAIN</td>\n",
        "      <td>Texas Commission on Environmental Quality</td>\n",
-       "      <td>TCEQMAIN-13702013</td>\n",
-       "      <td>2013-04-29</td>\n",
+       "      <td>TCEQMAIN-13947279</td>\n",
+       "      <td>2013-07-11</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>TCEQMAIN-15224</td>\n",
-       "      <td>STORET-422578803</td>\n",
+       "      <td>TCEQMAIN-11446</td>\n",
+       "      <td>STORET-422881708</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.09 milligram / liter</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.09 milligram / liter</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7.9 dimensionless</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>TCEQMAIN</td>\n",
        "      <td>Texas Commission on Environmental Quality</td>\n",
-       "      <td>TCEQMAIN-13947279</td>\n",
-       "      <td>2013-07-11</td>\n",
+       "      <td>TCEQMAIN-14329114</td>\n",
+       "      <td>2013-10-08</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>TCEQMAIN-11446</td>\n",
-       "      <td>STORET-422881708</td>\n",
+       "      <td>TCEQMAIN-15906</td>\n",
+       "      <td>STORET-422797456</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>0.24 milligram / liter</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>0.24 milligram / liter</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -1447,12 +1459,12 @@
        "      <th>3</th>\n",
        "      <td>TCEQMAIN</td>\n",
        "      <td>Texas Commission on Environmental Quality</td>\n",
-       "      <td>TCEQMAIN-14117837</td>\n",
-       "      <td>2013-01-28</td>\n",
+       "      <td>TCEQMAIN-13899297</td>\n",
+       "      <td>2013-08-01</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>TCEQMAIN-11370</td>\n",
-       "      <td>STORET-422872173</td>\n",
+       "      <td>TCEQMAIN-11287</td>\n",
+       "      <td>STORET-422829817</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -1471,12 +1483,12 @@
        "      <th>4</th>\n",
        "      <td>TCEQMAIN</td>\n",
        "      <td>Texas Commission on Environmental Quality</td>\n",
-       "      <td>TCEQMAIN-14208371</td>\n",
-       "      <td>2013-07-16</td>\n",
+       "      <td>TCEQMAIN-13702703</td>\n",
+       "      <td>2013-05-14</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>TCEQMAIN-16659</td>\n",
-       "      <td>STORET-423043742</td>\n",
+       "      <td>TCEQMAIN-15216</td>\n",
+       "      <td>STORET-422577293</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -1485,7 +1497,7 @@
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>28.2 Practical_Salinity_Units</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -1516,15 +1528,15 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248058</th>\n",
+       "      <th>249329</th>\n",
        "      <td>USGS-TX</td>\n",
        "      <td>USGS Texas Water Science Center</td>\n",
-       "      <td>nwistx.01.02302746</td>\n",
-       "      <td>2023-07-18</td>\n",
-       "      <td>11:45:00</td>\n",
-       "      <td>CDT</td>\n",
-       "      <td>USGS-08042554</td>\n",
-       "      <td>NWIS-125841792</td>\n",
+       "      <td>nwistx.01.02400657</td>\n",
+       "      <td>2024-01-25</td>\n",
+       "      <td>08:35:00</td>\n",
+       "      <td>CST</td>\n",
+       "      <td>USGS-08042546</td>\n",
+       "      <td>NWIS-126809215</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -1535,20 +1547,20 @@
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>46.0 Nephelometric_Turbidity_Units</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>6.6 dimensionless</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248059</th>\n",
+       "      <th>249330</th>\n",
        "      <td>USGS-TX</td>\n",
        "      <td>USGS Texas Water Science Center</td>\n",
-       "      <td>nwistx.01.02302749</td>\n",
-       "      <td>2023-07-18</td>\n",
-       "      <td>12:45:00</td>\n",
-       "      <td>CDT</td>\n",
+       "      <td>nwistx.01.02400657</td>\n",
+       "      <td>2024-01-25</td>\n",
+       "      <td>08:35:00</td>\n",
+       "      <td>CST</td>\n",
        "      <td>USGS-08042546</td>\n",
-       "      <td>NWIS-125842112</td>\n",
+       "      <td>NWIS-126809227</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -1558,21 +1570,21 @@
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>31.8 degree_Celsius</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>57.0 Nephelometric_Turbidity_Units</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248060</th>\n",
+       "      <th>249331</th>\n",
        "      <td>USGS-TX</td>\n",
        "      <td>USGS Texas Water Science Center</td>\n",
-       "      <td>nwistx.01.02302749</td>\n",
-       "      <td>2023-07-18</td>\n",
-       "      <td>12:45:00</td>\n",
-       "      <td>CDT</td>\n",
-       "      <td>USGS-08042546</td>\n",
-       "      <td>NWIS-125842120</td>\n",
+       "      <td>nwistx.01.02400659</td>\n",
+       "      <td>2024-01-25</td>\n",
+       "      <td>12:35:00</td>\n",
+       "      <td>CST</td>\n",
+       "      <td>USGS-08042554</td>\n",
+       "      <td>NWIS-126809095</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -1583,20 +1595,20 @@
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>16.0 degree_Celsius</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248061</th>\n",
+       "      <th>249332</th>\n",
        "      <td>USGS-TX</td>\n",
        "      <td>USGS Texas Water Science Center</td>\n",
-       "      <td>nwistx.01.02302749</td>\n",
-       "      <td>2023-07-18</td>\n",
-       "      <td>12:45:00</td>\n",
-       "      <td>CDT</td>\n",
-       "      <td>USGS-08042546</td>\n",
-       "      <td>NWIS-125842125</td>\n",
+       "      <td>nwistx.01.02400659</td>\n",
+       "      <td>2024-01-25</td>\n",
+       "      <td>12:35:00</td>\n",
+       "      <td>CST</td>\n",
+       "      <td>USGS-08042554</td>\n",
+       "      <td>NWIS-126809105</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -1609,18 +1621,18 @@
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>6.5 dimensionless</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248062</th>\n",
+       "      <th>249333</th>\n",
        "      <td>USGS-TX</td>\n",
        "      <td>USGS Texas Water Science Center</td>\n",
-       "      <td>nwistx.01.02302749</td>\n",
-       "      <td>2023-07-18</td>\n",
-       "      <td>12:45:00</td>\n",
-       "      <td>CDT</td>\n",
-       "      <td>USGS-08042546</td>\n",
-       "      <td>NWIS-125842127</td>\n",
+       "      <td>nwistx.01.02400659</td>\n",
+       "      <td>2024-01-25</td>\n",
+       "      <td>12:35:00</td>\n",
+       "      <td>CST</td>\n",
+       "      <td>USGS-08042554</td>\n",
+       "      <td>NWIS-126809117</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -1631,13 +1643,13 @@
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>11.0 Nephelometric_Turbidity_Units</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>49.0 Nephelometric_Turbidity_Units</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>248063 rows × 97 columns</p>\n",
+       "<p>249334 rows × 98 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
@@ -1648,91 +1660,104 @@
        "3                    TCEQMAIN  Texas Commission on Environmental Quality   \n",
        "4                    TCEQMAIN  Texas Commission on Environmental Quality   \n",
        "...                       ...                                        ...   \n",
-       "248058                USGS-TX            USGS Texas Water Science Center   \n",
-       "248059                USGS-TX            USGS Texas Water Science Center   \n",
-       "248060                USGS-TX            USGS Texas Water Science Center   \n",
-       "248061                USGS-TX            USGS Texas Water Science Center   \n",
-       "248062                USGS-TX            USGS Texas Water Science Center   \n",
+       "249329                USGS-TX            USGS Texas Water Science Center   \n",
+       "249330                USGS-TX            USGS Texas Water Science Center   \n",
+       "249331                USGS-TX            USGS Texas Water Science Center   \n",
+       "249332                USGS-TX            USGS Texas Water Science Center   \n",
+       "249333                USGS-TX            USGS Texas Water Science Center   \n",
        "\n",
        "        ActivityIdentifier ActivityStartDate ActivityStartTime/Time  \\\n",
-       "0        TCEQMAIN-14363288        2013-10-10                    NaN   \n",
-       "1        TCEQMAIN-13702013        2013-04-29                    NaN   \n",
-       "2        TCEQMAIN-13947279        2013-07-11                    NaN   \n",
-       "3        TCEQMAIN-14117837        2013-01-28                    NaN   \n",
-       "4        TCEQMAIN-14208371        2013-07-16                    NaN   \n",
+       "0        TCEQMAIN-13702013        2013-04-29                    NaN   \n",
+       "1        TCEQMAIN-13947279        2013-07-11                    NaN   \n",
+       "2        TCEQMAIN-14329114        2013-10-08                    NaN   \n",
+       "3        TCEQMAIN-13899297        2013-08-01                    NaN   \n",
+       "4        TCEQMAIN-13702703        2013-05-14                    NaN   \n",
        "...                    ...               ...                    ...   \n",
-       "248058  nwistx.01.02302746        2023-07-18               11:45:00   \n",
-       "248059  nwistx.01.02302749        2023-07-18               12:45:00   \n",
-       "248060  nwistx.01.02302749        2023-07-18               12:45:00   \n",
-       "248061  nwistx.01.02302749        2023-07-18               12:45:00   \n",
-       "248062  nwistx.01.02302749        2023-07-18               12:45:00   \n",
+       "249329  nwistx.01.02400657        2024-01-25               08:35:00   \n",
+       "249330  nwistx.01.02400657        2024-01-25               08:35:00   \n",
+       "249331  nwistx.01.02400659        2024-01-25               12:35:00   \n",
+       "249332  nwistx.01.02400659        2024-01-25               12:35:00   \n",
+       "249333  nwistx.01.02400659        2024-01-25               12:35:00   \n",
        "\n",
        "       ActivityStartTime/TimeZoneCode MonitoringLocationIdentifier  \\\n",
-       "0                                 NaN               TCEQMAIN-11455   \n",
-       "1                                 NaN               TCEQMAIN-15224   \n",
-       "2                                 NaN               TCEQMAIN-11446   \n",
-       "3                                 NaN               TCEQMAIN-11370   \n",
-       "4                                 NaN               TCEQMAIN-16659   \n",
+       "0                                 NaN               TCEQMAIN-15224   \n",
+       "1                                 NaN               TCEQMAIN-11446   \n",
+       "2                                 NaN               TCEQMAIN-15906   \n",
+       "3                                 NaN               TCEQMAIN-11287   \n",
+       "4                                 NaN               TCEQMAIN-15216   \n",
        "...                               ...                          ...   \n",
-       "248058                            CDT                USGS-08042554   \n",
-       "248059                            CDT                USGS-08042546   \n",
-       "248060                            CDT                USGS-08042546   \n",
-       "248061                            CDT                USGS-08042546   \n",
-       "248062                            CDT                USGS-08042546   \n",
+       "249329                            CST                USGS-08042546   \n",
+       "249330                            CST                USGS-08042546   \n",
+       "249331                            CST                USGS-08042554   \n",
+       "249332                            CST                USGS-08042554   \n",
+       "249333                            CST                USGS-08042554   \n",
        "\n",
        "        ResultIdentifier  DataLoggerLine ResultDetectionConditionText  ...  \\\n",
-       "0       STORET-422883712             NaN                          NaN  ...   \n",
-       "1       STORET-422578803             NaN                          NaN  ...   \n",
-       "2       STORET-422881708             NaN                          NaN  ...   \n",
-       "3       STORET-422872173             NaN                          NaN  ...   \n",
-       "4       STORET-423043742             NaN                          NaN  ...   \n",
+       "0       STORET-422578803             NaN                          NaN  ...   \n",
+       "1       STORET-422881708             NaN                          NaN  ...   \n",
+       "2       STORET-422797456             NaN                          NaN  ...   \n",
+       "3       STORET-422829817             NaN                          NaN  ...   \n",
+       "4       STORET-422577293             NaN                          NaN  ...   \n",
        "...                  ...             ...                          ...  ...   \n",
-       "248058    NWIS-125841792             NaN                          NaN  ...   \n",
-       "248059    NWIS-125842112             NaN                          NaN  ...   \n",
-       "248060    NWIS-125842120             NaN                          NaN  ...   \n",
-       "248061    NWIS-125842125             NaN                          NaN  ...   \n",
-       "248062    NWIS-125842127             NaN                          NaN  ...   \n",
+       "249329    NWIS-126809215             NaN                          NaN  ...   \n",
+       "249330    NWIS-126809227             NaN                          NaN  ...   \n",
+       "249331    NWIS-126809095             NaN                          NaN  ...   \n",
+       "249332    NWIS-126809105             NaN                          NaN  ...   \n",
+       "249333    NWIS-126809117             NaN                          NaN  ...   \n",
+       "\n",
+       "       Carbon              Phosphorus TP_Phosphorus  TDP_Phosphorus  \\\n",
+       "0         NaN  0.09 milligram / liter           NaN             NaN   \n",
+       "1         NaN                     NaN           NaN             NaN   \n",
+       "2         NaN  0.24 milligram / liter           NaN             NaN   \n",
+       "3         NaN                     NaN           NaN             NaN   \n",
+       "4         NaN                     NaN           NaN             NaN   \n",
+       "...       ...                     ...           ...             ...   \n",
+       "249329    NaN                     NaN           NaN             NaN   \n",
+       "249330    NaN                     NaN           NaN             NaN   \n",
+       "249331    NaN                     NaN           NaN             NaN   \n",
+       "249332    NaN                     NaN           NaN             NaN   \n",
+       "249333    NaN                     NaN           NaN             NaN   \n",
        "\n",
-       "         DO Fecal_Coliform              Phosphorus  TP_Phosphorus  \\\n",
-       "0       NaN            NaN  0.19 milligram / liter            NaN   \n",
-       "1       NaN            NaN  0.09 milligram / liter            NaN   \n",
-       "2       NaN            NaN                     NaN            NaN   \n",
-       "3       NaN            NaN                     NaN            NaN   \n",
-       "4       NaN            NaN                     NaN            NaN   \n",
-       "...     ...            ...                     ...            ...   \n",
-       "248058  NaN            NaN                     NaN            NaN   \n",
-       "248059  NaN            NaN                     NaN            NaN   \n",
-       "248060  NaN            NaN                     NaN            NaN   \n",
-       "248061  NaN            NaN                     NaN            NaN   \n",
-       "248062  NaN            NaN                     NaN            NaN   \n",
+       "              Other_Phosphorus                       Salinity Sediment  \\\n",
+       "0       0.09 milligram / liter                            NaN      NaN   \n",
+       "1                          NaN                            NaN      NaN   \n",
+       "2       0.24 milligram / liter                            NaN      NaN   \n",
+       "3                          NaN                            NaN      NaN   \n",
+       "4                          NaN  28.2 Practical_Salinity_Units      NaN   \n",
+       "...                        ...                            ...      ...   \n",
+       "249329                     NaN                            NaN      NaN   \n",
+       "249330                     NaN                            NaN      NaN   \n",
+       "249331                     NaN                            NaN      NaN   \n",
+       "249332                     NaN                            NaN      NaN   \n",
+       "249333                     NaN                            NaN      NaN   \n",
        "\n",
-       "       TDP_Phosphorus        Other_Phosphorus          Temperature  \\\n",
-       "0                 NaN  0.19 milligram / liter                  NaN   \n",
-       "1                 NaN  0.09 milligram / liter                  NaN   \n",
-       "2                 NaN                     NaN                  NaN   \n",
-       "3                 NaN                     NaN                  NaN   \n",
-       "4                 NaN                     NaN                  NaN   \n",
-       "...               ...                     ...                  ...   \n",
-       "248058            NaN                     NaN                  NaN   \n",
-       "248059            NaN                     NaN  31.8 degree_Celsius   \n",
-       "248060            NaN                     NaN                  NaN   \n",
-       "248061            NaN                     NaN                  NaN   \n",
-       "248062            NaN                     NaN                  NaN   \n",
+       "                Temperature                           Turbidity  \\\n",
+       "0                       NaN                                 NaN   \n",
+       "1                       NaN                                 NaN   \n",
+       "2                       NaN                                 NaN   \n",
+       "3                       NaN                                 NaN   \n",
+       "4                       NaN                                 NaN   \n",
+       "...                     ...                                 ...   \n",
+       "249329                  NaN                                 NaN   \n",
+       "249330                  NaN  57.0 Nephelometric_Turbidity_Units   \n",
+       "249331  16.0 degree_Celsius                                 NaN   \n",
+       "249332                  NaN                                 NaN   \n",
+       "249333                  NaN  49.0 Nephelometric_Turbidity_Units   \n",
        "\n",
-       "                                 Turbidity Salinity Conductivity  \n",
-       "0                                      NaN      NaN          NaN  \n",
-       "1                                      NaN      NaN          NaN  \n",
-       "2                                      NaN      NaN          NaN  \n",
-       "3                                      NaN      NaN          NaN  \n",
-       "4                                      NaN      NaN          NaN  \n",
-       "...                                    ...      ...          ...  \n",
-       "248058  46.0 Nephelometric_Turbidity_Units      NaN          NaN  \n",
-       "248059                                 NaN      NaN          NaN  \n",
-       "248060                                 NaN      NaN          NaN  \n",
-       "248061                                 NaN      NaN          NaN  \n",
-       "248062  11.0 Nephelometric_Turbidity_Units      NaN          NaN  \n",
+       "                       pH  \n",
+       "0                     NaN  \n",
+       "1       7.9 dimensionless  \n",
+       "2                     NaN  \n",
+       "3                     NaN  \n",
+       "4                     NaN  \n",
+       "...                   ...  \n",
+       "249329  6.6 dimensionless  \n",
+       "249330                NaN  \n",
+       "249331                NaN  \n",
+       "249332  6.5 dimensionless  \n",
+       "249333                NaN  \n",
        "\n",
-       "[248063 rows x 97 columns]"
+       "[249334 rows x 98 columns]"
       ]
      },
      "execution_count": 14,
@@ -1755,7 +1780,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\dataretrieval\\utils.py:87: UserWarning: Warning: 216464 incomplete dates found, consider setting datetime_index to False.\n",
+      "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\dataretrieval\\utils.py:87: UserWarning: Warning: 217379 incomplete dates found, consider setting datetime_index to False.\n",
       "  warnings.warn(\n",
       "C:\\Users\\jbousqui\\Local_GIS\\Python\\v_envs\\jupyter-harmonize-39\\lib\\site-packages\\pandas\\core\\dtypes\\cast.py:1784: UnitStrippedWarning: The unit of the quantity is stripped when downcasting to ndarray.\n",
       "  result[:] = values\n"
@@ -1793,14 +1818,14 @@
        "      <th>DataLoggerLine</th>\n",
        "      <th>ResultDetectionConditionText</th>\n",
        "      <th>...</th>\n",
-       "      <th>Phosphorus</th>\n",
        "      <th>TP_Phosphorus</th>\n",
        "      <th>TDP_Phosphorus</th>\n",
        "      <th>Other_Phosphorus</th>\n",
+       "      <th>Salinity</th>\n",
+       "      <th>Sediment</th>\n",
        "      <th>Temperature</th>\n",
        "      <th>Turbidity</th>\n",
-       "      <th>Salinity</th>\n",
-       "      <th>Conductivity</th>\n",
+       "      <th>pH</th>\n",
        "      <th>Activity_datetime</th>\n",
        "      <th>Depth</th>\n",
        "    </tr>\n",
@@ -1810,19 +1835,19 @@
        "      <th>0</th>\n",
        "      <td>TCEQMAIN</td>\n",
        "      <td>Texas Commission on Environmental Quality</td>\n",
-       "      <td>TCEQMAIN-14363288</td>\n",
-       "      <td>2013-10-10</td>\n",
+       "      <td>TCEQMAIN-13702013</td>\n",
+       "      <td>2013-04-29</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>TCEQMAIN-11455</td>\n",
-       "      <td>STORET-422883712</td>\n",
+       "      <td>TCEQMAIN-15224</td>\n",
+       "      <td>STORET-422578803</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td>0.19 milligram / liter</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.19 milligram / liter</td>\n",
+       "      <td>0.09 milligram / liter</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -1834,23 +1859,23 @@
        "      <th>1</th>\n",
        "      <td>TCEQMAIN</td>\n",
        "      <td>Texas Commission on Environmental Quality</td>\n",
-       "      <td>TCEQMAIN-13702013</td>\n",
-       "      <td>2013-04-29</td>\n",
+       "      <td>TCEQMAIN-13947279</td>\n",
+       "      <td>2013-07-11</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>TCEQMAIN-15224</td>\n",
-       "      <td>STORET-422578803</td>\n",
+       "      <td>TCEQMAIN-11446</td>\n",
+       "      <td>STORET-422881708</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
-       "      <td>0.09 milligram / liter</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.09 milligram / liter</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>7.9 dimensionless</td>\n",
        "      <td>NaT</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
@@ -1858,18 +1883,18 @@
        "      <th>2</th>\n",
        "      <td>TCEQMAIN</td>\n",
        "      <td>Texas Commission on Environmental Quality</td>\n",
-       "      <td>TCEQMAIN-13947279</td>\n",
-       "      <td>2013-07-11</td>\n",
+       "      <td>TCEQMAIN-14329114</td>\n",
+       "      <td>2013-10-08</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>TCEQMAIN-11446</td>\n",
-       "      <td>STORET-422881708</td>\n",
+       "      <td>TCEQMAIN-15906</td>\n",
+       "      <td>STORET-422797456</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>0.24 milligram / liter</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -1882,12 +1907,12 @@
        "      <th>3</th>\n",
        "      <td>TCEQMAIN</td>\n",
        "      <td>Texas Commission on Environmental Quality</td>\n",
-       "      <td>TCEQMAIN-14117837</td>\n",
-       "      <td>2013-01-28</td>\n",
+       "      <td>TCEQMAIN-13899297</td>\n",
+       "      <td>2013-08-01</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>TCEQMAIN-11370</td>\n",
-       "      <td>STORET-422872173</td>\n",
+       "      <td>TCEQMAIN-11287</td>\n",
+       "      <td>STORET-422829817</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -1906,19 +1931,19 @@
        "      <th>4</th>\n",
        "      <td>TCEQMAIN</td>\n",
        "      <td>Texas Commission on Environmental Quality</td>\n",
-       "      <td>TCEQMAIN-14208371</td>\n",
-       "      <td>2013-07-16</td>\n",
+       "      <td>TCEQMAIN-13702703</td>\n",
+       "      <td>2013-05-14</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>TCEQMAIN-16659</td>\n",
-       "      <td>STORET-423043742</td>\n",
+       "      <td>TCEQMAIN-15216</td>\n",
+       "      <td>STORET-422577293</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
+       "      <td>28.2 Practical_Salinity_Units</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -1951,15 +1976,15 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248058</th>\n",
+       "      <th>249329</th>\n",
        "      <td>USGS-TX</td>\n",
        "      <td>USGS Texas Water Science Center</td>\n",
-       "      <td>nwistx.01.02302746</td>\n",
-       "      <td>2023-07-18</td>\n",
-       "      <td>11:45:00</td>\n",
-       "      <td>-0500</td>\n",
-       "      <td>USGS-08042554</td>\n",
-       "      <td>NWIS-125841792</td>\n",
+       "      <td>nwistx.01.02400657</td>\n",
+       "      <td>2024-01-25</td>\n",
+       "      <td>08:35:00</td>\n",
+       "      <td>-0600</td>\n",
+       "      <td>USGS-08042546</td>\n",
+       "      <td>NWIS-126809215</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -1968,22 +1993,22 @@
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>46.0 Nephelometric_Turbidity_Units</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>2023-07-18 16:45:00+00:00</td>\n",
+       "      <td>6.6 dimensionless</td>\n",
+       "      <td>2024-01-25 14:35:00+00:00</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248059</th>\n",
+       "      <th>249330</th>\n",
        "      <td>USGS-TX</td>\n",
        "      <td>USGS Texas Water Science Center</td>\n",
-       "      <td>nwistx.01.02302749</td>\n",
-       "      <td>2023-07-18</td>\n",
-       "      <td>12:45:00</td>\n",
-       "      <td>-0500</td>\n",
+       "      <td>nwistx.01.02400657</td>\n",
+       "      <td>2024-01-25</td>\n",
+       "      <td>08:35:00</td>\n",
+       "      <td>-0600</td>\n",
        "      <td>USGS-08042546</td>\n",
-       "      <td>NWIS-125842112</td>\n",
+       "      <td>NWIS-126809227</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -1991,23 +2016,23 @@
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>31.8 degree_Celsius</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>57.0 Nephelometric_Turbidity_Units</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>2023-07-18 17:45:00+00:00</td>\n",
+       "      <td>2024-01-25 14:35:00+00:00</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248060</th>\n",
+       "      <th>249331</th>\n",
        "      <td>USGS-TX</td>\n",
        "      <td>USGS Texas Water Science Center</td>\n",
-       "      <td>nwistx.01.02302749</td>\n",
-       "      <td>2023-07-18</td>\n",
-       "      <td>12:45:00</td>\n",
-       "      <td>-0500</td>\n",
-       "      <td>USGS-08042546</td>\n",
-       "      <td>NWIS-125842120</td>\n",
+       "      <td>nwistx.01.02400659</td>\n",
+       "      <td>2024-01-25</td>\n",
+       "      <td>12:35:00</td>\n",
+       "      <td>-0600</td>\n",
+       "      <td>USGS-08042554</td>\n",
+       "      <td>NWIS-126809095</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -2016,22 +2041,22 @@
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>16.0 degree_Celsius</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2023-07-18 17:45:00+00:00</td>\n",
+       "      <td>2024-01-25 18:35:00+00:00</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248061</th>\n",
+       "      <th>249332</th>\n",
        "      <td>USGS-TX</td>\n",
        "      <td>USGS Texas Water Science Center</td>\n",
-       "      <td>nwistx.01.02302749</td>\n",
-       "      <td>2023-07-18</td>\n",
-       "      <td>12:45:00</td>\n",
-       "      <td>-0500</td>\n",
-       "      <td>USGS-08042546</td>\n",
-       "      <td>NWIS-125842125</td>\n",
+       "      <td>nwistx.01.02400659</td>\n",
+       "      <td>2024-01-25</td>\n",
+       "      <td>12:35:00</td>\n",
+       "      <td>-0600</td>\n",
+       "      <td>USGS-08042554</td>\n",
+       "      <td>NWIS-126809105</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -2042,20 +2067,20 @@
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2023-07-18 17:45:00+00:00</td>\n",
+       "      <td>6.5 dimensionless</td>\n",
+       "      <td>2024-01-25 18:35:00+00:00</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248062</th>\n",
+       "      <th>249333</th>\n",
        "      <td>USGS-TX</td>\n",
        "      <td>USGS Texas Water Science Center</td>\n",
-       "      <td>nwistx.01.02302749</td>\n",
-       "      <td>2023-07-18</td>\n",
-       "      <td>12:45:00</td>\n",
-       "      <td>-0500</td>\n",
-       "      <td>USGS-08042546</td>\n",
-       "      <td>NWIS-125842127</td>\n",
+       "      <td>nwistx.01.02400659</td>\n",
+       "      <td>2024-01-25</td>\n",
+       "      <td>12:35:00</td>\n",
+       "      <td>-0600</td>\n",
+       "      <td>USGS-08042554</td>\n",
+       "      <td>NWIS-126809117</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -2064,15 +2089,15 @@
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>11.0 Nephelometric_Turbidity_Units</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>49.0 Nephelometric_Turbidity_Units</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>2023-07-18 17:45:00+00:00</td>\n",
+       "      <td>2024-01-25 18:35:00+00:00</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>248063 rows × 99 columns</p>\n",
+       "<p>249334 rows × 100 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
@@ -2083,89 +2108,89 @@
        "3                    TCEQMAIN  Texas Commission on Environmental Quality   \n",
        "4                    TCEQMAIN  Texas Commission on Environmental Quality   \n",
        "...                       ...                                        ...   \n",
-       "248058                USGS-TX            USGS Texas Water Science Center   \n",
-       "248059                USGS-TX            USGS Texas Water Science Center   \n",
-       "248060                USGS-TX            USGS Texas Water Science Center   \n",
-       "248061                USGS-TX            USGS Texas Water Science Center   \n",
-       "248062                USGS-TX            USGS Texas Water Science Center   \n",
+       "249329                USGS-TX            USGS Texas Water Science Center   \n",
+       "249330                USGS-TX            USGS Texas Water Science Center   \n",
+       "249331                USGS-TX            USGS Texas Water Science Center   \n",
+       "249332                USGS-TX            USGS Texas Water Science Center   \n",
+       "249333                USGS-TX            USGS Texas Water Science Center   \n",
        "\n",
        "        ActivityIdentifier ActivityStartDate ActivityStartTime/Time  \\\n",
-       "0        TCEQMAIN-14363288        2013-10-10                    NaN   \n",
-       "1        TCEQMAIN-13702013        2013-04-29                    NaN   \n",
-       "2        TCEQMAIN-13947279        2013-07-11                    NaN   \n",
-       "3        TCEQMAIN-14117837        2013-01-28                    NaN   \n",
-       "4        TCEQMAIN-14208371        2013-07-16                    NaN   \n",
+       "0        TCEQMAIN-13702013        2013-04-29                    NaN   \n",
+       "1        TCEQMAIN-13947279        2013-07-11                    NaN   \n",
+       "2        TCEQMAIN-14329114        2013-10-08                    NaN   \n",
+       "3        TCEQMAIN-13899297        2013-08-01                    NaN   \n",
+       "4        TCEQMAIN-13702703        2013-05-14                    NaN   \n",
        "...                    ...               ...                    ...   \n",
-       "248058  nwistx.01.02302746        2023-07-18               11:45:00   \n",
-       "248059  nwistx.01.02302749        2023-07-18               12:45:00   \n",
-       "248060  nwistx.01.02302749        2023-07-18               12:45:00   \n",
-       "248061  nwistx.01.02302749        2023-07-18               12:45:00   \n",
-       "248062  nwistx.01.02302749        2023-07-18               12:45:00   \n",
+       "249329  nwistx.01.02400657        2024-01-25               08:35:00   \n",
+       "249330  nwistx.01.02400657        2024-01-25               08:35:00   \n",
+       "249331  nwistx.01.02400659        2024-01-25               12:35:00   \n",
+       "249332  nwistx.01.02400659        2024-01-25               12:35:00   \n",
+       "249333  nwistx.01.02400659        2024-01-25               12:35:00   \n",
        "\n",
        "       ActivityStartTime/TimeZoneCode MonitoringLocationIdentifier  \\\n",
-       "0                                 NaN               TCEQMAIN-11455   \n",
-       "1                                 NaN               TCEQMAIN-15224   \n",
-       "2                                 NaN               TCEQMAIN-11446   \n",
-       "3                                 NaN               TCEQMAIN-11370   \n",
-       "4                                 NaN               TCEQMAIN-16659   \n",
+       "0                                 NaN               TCEQMAIN-15224   \n",
+       "1                                 NaN               TCEQMAIN-11446   \n",
+       "2                                 NaN               TCEQMAIN-15906   \n",
+       "3                                 NaN               TCEQMAIN-11287   \n",
+       "4                                 NaN               TCEQMAIN-15216   \n",
        "...                               ...                          ...   \n",
-       "248058                          -0500                USGS-08042554   \n",
-       "248059                          -0500                USGS-08042546   \n",
-       "248060                          -0500                USGS-08042546   \n",
-       "248061                          -0500                USGS-08042546   \n",
-       "248062                          -0500                USGS-08042546   \n",
+       "249329                          -0600                USGS-08042546   \n",
+       "249330                          -0600                USGS-08042546   \n",
+       "249331                          -0600                USGS-08042554   \n",
+       "249332                          -0600                USGS-08042554   \n",
+       "249333                          -0600                USGS-08042554   \n",
        "\n",
        "        ResultIdentifier  DataLoggerLine ResultDetectionConditionText  ...  \\\n",
-       "0       STORET-422883712             NaN                          NaN  ...   \n",
-       "1       STORET-422578803             NaN                          NaN  ...   \n",
-       "2       STORET-422881708             NaN                          NaN  ...   \n",
-       "3       STORET-422872173             NaN                          NaN  ...   \n",
-       "4       STORET-423043742             NaN                          NaN  ...   \n",
+       "0       STORET-422578803             NaN                          NaN  ...   \n",
+       "1       STORET-422881708             NaN                          NaN  ...   \n",
+       "2       STORET-422797456             NaN                          NaN  ...   \n",
+       "3       STORET-422829817             NaN                          NaN  ...   \n",
+       "4       STORET-422577293             NaN                          NaN  ...   \n",
        "...                  ...             ...                          ...  ...   \n",
-       "248058    NWIS-125841792             NaN                          NaN  ...   \n",
-       "248059    NWIS-125842112             NaN                          NaN  ...   \n",
-       "248060    NWIS-125842120             NaN                          NaN  ...   \n",
-       "248061    NWIS-125842125             NaN                          NaN  ...   \n",
-       "248062    NWIS-125842127             NaN                          NaN  ...   \n",
+       "249329    NWIS-126809215             NaN                          NaN  ...   \n",
+       "249330    NWIS-126809227             NaN                          NaN  ...   \n",
+       "249331    NWIS-126809095             NaN                          NaN  ...   \n",
+       "249332    NWIS-126809105             NaN                          NaN  ...   \n",
+       "249333    NWIS-126809117             NaN                          NaN  ...   \n",
        "\n",
-       "                    Phosphorus TP_Phosphorus TDP_Phosphorus  \\\n",
-       "0       0.19 milligram / liter           NaN            NaN   \n",
-       "1       0.09 milligram / liter           NaN            NaN   \n",
-       "2                          NaN           NaN            NaN   \n",
-       "3                          NaN           NaN            NaN   \n",
-       "4                          NaN           NaN            NaN   \n",
-       "...                        ...           ...            ...   \n",
-       "248058                     NaN           NaN            NaN   \n",
-       "248059                     NaN           NaN            NaN   \n",
-       "248060                     NaN           NaN            NaN   \n",
-       "248061                     NaN           NaN            NaN   \n",
-       "248062                     NaN           NaN            NaN   \n",
+       "       TP_Phosphorus TDP_Phosphorus        Other_Phosphorus  \\\n",
+       "0                NaN            NaN  0.09 milligram / liter   \n",
+       "1                NaN            NaN                     NaN   \n",
+       "2                NaN            NaN  0.24 milligram / liter   \n",
+       "3                NaN            NaN                     NaN   \n",
+       "4                NaN            NaN                     NaN   \n",
+       "...              ...            ...                     ...   \n",
+       "249329           NaN            NaN                     NaN   \n",
+       "249330           NaN            NaN                     NaN   \n",
+       "249331           NaN            NaN                     NaN   \n",
+       "249332           NaN            NaN                     NaN   \n",
+       "249333           NaN            NaN                     NaN   \n",
        "\n",
-       "              Other_Phosphorus          Temperature  \\\n",
-       "0       0.19 milligram / liter                  NaN   \n",
-       "1       0.09 milligram / liter                  NaN   \n",
-       "2                          NaN                  NaN   \n",
-       "3                          NaN                  NaN   \n",
-       "4                          NaN                  NaN   \n",
-       "...                        ...                  ...   \n",
-       "248058                     NaN                  NaN   \n",
-       "248059                     NaN  31.8 degree_Celsius   \n",
-       "248060                     NaN                  NaN   \n",
-       "248061                     NaN                  NaN   \n",
-       "248062                     NaN                  NaN   \n",
+       "                             Salinity Sediment          Temperature  \\\n",
+       "0                                 NaN      NaN                  NaN   \n",
+       "1                                 NaN      NaN                  NaN   \n",
+       "2                                 NaN      NaN                  NaN   \n",
+       "3                                 NaN      NaN                  NaN   \n",
+       "4       28.2 Practical_Salinity_Units      NaN                  NaN   \n",
+       "...                               ...      ...                  ...   \n",
+       "249329                            NaN      NaN                  NaN   \n",
+       "249330                            NaN      NaN                  NaN   \n",
+       "249331                            NaN      NaN  16.0 degree_Celsius   \n",
+       "249332                            NaN      NaN                  NaN   \n",
+       "249333                            NaN      NaN                  NaN   \n",
        "\n",
-       "                                 Turbidity Salinity Conductivity  \\\n",
-       "0                                      NaN      NaN          NaN   \n",
-       "1                                      NaN      NaN          NaN   \n",
-       "2                                      NaN      NaN          NaN   \n",
-       "3                                      NaN      NaN          NaN   \n",
-       "4                                      NaN      NaN          NaN   \n",
-       "...                                    ...      ...          ...   \n",
-       "248058  46.0 Nephelometric_Turbidity_Units      NaN          NaN   \n",
-       "248059                                 NaN      NaN          NaN   \n",
-       "248060                                 NaN      NaN          NaN   \n",
-       "248061                                 NaN      NaN          NaN   \n",
-       "248062  11.0 Nephelometric_Turbidity_Units      NaN          NaN   \n",
+       "                                 Turbidity                 pH  \\\n",
+       "0                                      NaN                NaN   \n",
+       "1                                      NaN  7.9 dimensionless   \n",
+       "2                                      NaN                NaN   \n",
+       "3                                      NaN                NaN   \n",
+       "4                                      NaN                NaN   \n",
+       "...                                    ...                ...   \n",
+       "249329                                 NaN  6.6 dimensionless   \n",
+       "249330  57.0 Nephelometric_Turbidity_Units                NaN   \n",
+       "249331                                 NaN                NaN   \n",
+       "249332                                 NaN  6.5 dimensionless   \n",
+       "249333  49.0 Nephelometric_Turbidity_Units                NaN   \n",
        "\n",
        "               Activity_datetime Depth  \n",
        "0                            NaT   NaN  \n",
@@ -2174,13 +2199,13 @@
        "3                            NaT   NaN  \n",
        "4                            NaT   NaN  \n",
        "...                          ...   ...  \n",
-       "248058 2023-07-18 16:45:00+00:00   NaN  \n",
-       "248059 2023-07-18 17:45:00+00:00   NaN  \n",
-       "248060 2023-07-18 17:45:00+00:00   NaN  \n",
-       "248061 2023-07-18 17:45:00+00:00   NaN  \n",
-       "248062 2023-07-18 17:45:00+00:00   NaN  \n",
+       "249329 2024-01-25 14:35:00+00:00   NaN  \n",
+       "249330 2024-01-25 14:35:00+00:00   NaN  \n",
+       "249331 2024-01-25 18:35:00+00:00   NaN  \n",
+       "249332 2024-01-25 18:35:00+00:00   NaN  \n",
+       "249333 2024-01-25 18:35:00+00:00   NaN  \n",
        "\n",
-       "[248063 rows x 99 columns]"
+       "[249334 rows x 100 columns]"
       ]
      },
      "execution_count": 15,
@@ -2219,7 +2244,7 @@
     },
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -2252,7 +2277,7 @@
     },
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -2325,39 +2350,39 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>15</th>\n",
-       "      <td>0.40</td>\n",
+       "      <th>13</th>\n",
+       "      <td>0.41</td>\n",
        "      <td>m</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.4 meter</td>\n",
+       "      <td>0.41 meter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>16</th>\n",
-       "      <td>0.37</td>\n",
+       "      <th>25</th>\n",
+       "      <td>0.91</td>\n",
        "      <td>m</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.37 meter</td>\n",
+       "      <td>0.91 meter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>20</th>\n",
-       "      <td>0.22</td>\n",
+       "      <th>43</th>\n",
+       "      <td>0.69</td>\n",
        "      <td>m</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.22 meter</td>\n",
+       "      <td>0.69 meter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>24</th>\n",
-       "      <td>0.84</td>\n",
+       "      <th>51</th>\n",
+       "      <td>0.20</td>\n",
        "      <td>m</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.84 meter</td>\n",
+       "      <td>0.2 meter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>31</th>\n",
-       "      <td>0.38</td>\n",
+       "      <th>52</th>\n",
+       "      <td>0.27</td>\n",
        "      <td>m</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.38 meter</td>\n",
+       "      <td>0.27 meter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>...</th>\n",
@@ -2367,73 +2392,60 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247654</th>\n",
-       "      <td>12.00</td>\n",
+       "      <th>249010</th>\n",
+       "      <td>21.00</td>\n",
        "      <td>in</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.30479999999999996 meter</td>\n",
+       "      <td>0.5334 meter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247680</th>\n",
-       "      <td>11.50</td>\n",
-       "      <td>in</td>\n",
+       "      <th>249019</th>\n",
+       "      <td>0.41</td>\n",
+       "      <td>m</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.29209999999999997 meter</td>\n",
+       "      <td>0.41 meter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247737</th>\n",
-       "      <td>0.46</td>\n",
-       "      <td>in</td>\n",
+       "      <th>249023</th>\n",
+       "      <td>0.20</td>\n",
+       "      <td>m</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.011684 meter</td>\n",
+       "      <td>0.2 meter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247779</th>\n",
-       "      <td>9.00</td>\n",
-       "      <td>in</td>\n",
+       "      <th>249025</th>\n",
+       "      <td>0.28</td>\n",
+       "      <td>m</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.2286 meter</td>\n",
+       "      <td>0.28 meter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247796</th>\n",
-       "      <td>10.40</td>\n",
-       "      <td>in</td>\n",
+       "      <th>249118</th>\n",
+       "      <td>14.00</td>\n",
+       "      <td>m</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.26416 meter</td>\n",
+       "      <td>14.0 meter</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>24767 rows × 4 columns</p>\n",
+       "<p>24848 rows × 4 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "        ResultMeasureValue ResultMeasure/MeasureUnitCode QA_flag  \\\n",
-       "15                    0.40                             m     NaN   \n",
-       "16                    0.37                             m     NaN   \n",
-       "20                    0.22                             m     NaN   \n",
-       "24                    0.84                             m     NaN   \n",
-       "31                    0.38                             m     NaN   \n",
-       "...                    ...                           ...     ...   \n",
-       "247654               12.00                            in     NaN   \n",
-       "247680               11.50                            in     NaN   \n",
-       "247737                0.46                            in     NaN   \n",
-       "247779                9.00                            in     NaN   \n",
-       "247796               10.40                            in     NaN   \n",
-       "\n",
-       "                           Secchi  \n",
-       "15                      0.4 meter  \n",
-       "16                     0.37 meter  \n",
-       "20                     0.22 meter  \n",
-       "24                     0.84 meter  \n",
-       "31                     0.38 meter  \n",
-       "...                           ...  \n",
-       "247654  0.30479999999999996 meter  \n",
-       "247680  0.29209999999999997 meter  \n",
-       "247737             0.011684 meter  \n",
-       "247779               0.2286 meter  \n",
-       "247796              0.26416 meter  \n",
+       "        ResultMeasureValue ResultMeasure/MeasureUnitCode QA_flag        Secchi\n",
+       "13                    0.41                             m     NaN    0.41 meter\n",
+       "25                    0.91                             m     NaN    0.91 meter\n",
+       "43                    0.69                             m     NaN    0.69 meter\n",
+       "51                    0.20                             m     NaN     0.2 meter\n",
+       "52                    0.27                             m     NaN    0.27 meter\n",
+       "...                    ...                           ...     ...           ...\n",
+       "249010               21.00                            in     NaN  0.5334 meter\n",
+       "249019                0.41                             m     NaN    0.41 meter\n",
+       "249023                0.20                             m     NaN     0.2 meter\n",
+       "249025                0.28                             m     NaN    0.28 meter\n",
+       "249118               14.00                             m     NaN    14.0 meter\n",
        "\n",
-       "[24767 rows x 4 columns]"
+       "[24848 rows x 4 columns]"
       ]
      },
      "execution_count": 19,
@@ -2480,35 +2492,35 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>11536</th>\n",
+       "      <th>11538</th>\n",
        "      <td>26.2</td>\n",
        "      <td>deg C</td>\n",
        "      <td>NaN</td>\n",
        "      <td>26.2 degree_Celsius</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>11942</th>\n",
+       "      <th>11887</th>\n",
        "      <td>25.8</td>\n",
        "      <td>deg C</td>\n",
        "      <td>NaN</td>\n",
        "      <td>25.8 degree_Celsius</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>11980</th>\n",
+       "      <th>11982</th>\n",
        "      <td>30.5</td>\n",
        "      <td>deg C</td>\n",
        "      <td>NaN</td>\n",
        "      <td>30.5 degree_Celsius</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>12130</th>\n",
+       "      <th>12056</th>\n",
        "      <td>26.0</td>\n",
        "      <td>deg C</td>\n",
        "      <td>NaN</td>\n",
        "      <td>26.0 degree_Celsius</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>12164</th>\n",
+       "      <th>12159</th>\n",
        "      <td>30.5</td>\n",
        "      <td>deg C</td>\n",
        "      <td>NaN</td>\n",
@@ -2522,73 +2534,73 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248043</th>\n",
-       "      <td>31.4</td>\n",
+       "      <th>249319</th>\n",
+       "      <td>16.7</td>\n",
        "      <td>deg C</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>31.4 degree_Celsius</td>\n",
+       "      <td>16.7 degree_Celsius</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248047</th>\n",
-       "      <td>29.1</td>\n",
+       "      <th>249322</th>\n",
+       "      <td>15.8</td>\n",
        "      <td>deg C</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>29.1 degree_Celsius</td>\n",
+       "      <td>15.8 degree_Celsius</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248051</th>\n",
-       "      <td>31.0</td>\n",
+       "      <th>249325</th>\n",
+       "      <td>16.1</td>\n",
        "      <td>deg C</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>31.0 degree_Celsius</td>\n",
+       "      <td>16.1 degree_Celsius</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248055</th>\n",
-       "      <td>32.2</td>\n",
+       "      <th>249328</th>\n",
+       "      <td>15.6</td>\n",
        "      <td>deg C</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>32.2 degree_Celsius</td>\n",
+       "      <td>15.6 degree_Celsius</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248059</th>\n",
-       "      <td>31.8</td>\n",
+       "      <th>249331</th>\n",
+       "      <td>16.0</td>\n",
        "      <td>deg C</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>31.8 degree_Celsius</td>\n",
+       "      <td>16.0 degree_Celsius</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>8290 rows × 4 columns</p>\n",
+       "<p>8435 rows × 4 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
        "        ResultMeasureValue ResultMeasure/MeasureUnitCode QA_flag  \\\n",
-       "11536                 26.2                         deg C     NaN   \n",
-       "11942                 25.8                         deg C     NaN   \n",
-       "11980                 30.5                         deg C     NaN   \n",
-       "12130                 26.0                         deg C     NaN   \n",
-       "12164                 30.5                         deg C     NaN   \n",
+       "11538                 26.2                         deg C     NaN   \n",
+       "11887                 25.8                         deg C     NaN   \n",
+       "11982                 30.5                         deg C     NaN   \n",
+       "12056                 26.0                         deg C     NaN   \n",
+       "12159                 30.5                         deg C     NaN   \n",
        "...                    ...                           ...     ...   \n",
-       "248043                31.4                         deg C     NaN   \n",
-       "248047                29.1                         deg C     NaN   \n",
-       "248051                31.0                         deg C     NaN   \n",
-       "248055                32.2                         deg C     NaN   \n",
-       "248059                31.8                         deg C     NaN   \n",
+       "249319                16.7                         deg C     NaN   \n",
+       "249322                15.8                         deg C     NaN   \n",
+       "249325                16.1                         deg C     NaN   \n",
+       "249328                15.6                         deg C     NaN   \n",
+       "249331                16.0                         deg C     NaN   \n",
        "\n",
        "                Temperature  \n",
-       "11536   26.2 degree_Celsius  \n",
-       "11942   25.8 degree_Celsius  \n",
-       "11980   30.5 degree_Celsius  \n",
-       "12130   26.0 degree_Celsius  \n",
-       "12164   30.5 degree_Celsius  \n",
+       "11538   26.2 degree_Celsius  \n",
+       "11887   25.8 degree_Celsius  \n",
+       "11982   30.5 degree_Celsius  \n",
+       "12056   26.0 degree_Celsius  \n",
+       "12159   30.5 degree_Celsius  \n",
        "...                     ...  \n",
-       "248043  31.4 degree_Celsius  \n",
-       "248047  29.1 degree_Celsius  \n",
-       "248051  31.0 degree_Celsius  \n",
-       "248055  32.2 degree_Celsius  \n",
-       "248059  31.8 degree_Celsius  \n",
+       "249319  16.7 degree_Celsius  \n",
+       "249322  15.8 degree_Celsius  \n",
+       "249325  16.1 degree_Celsius  \n",
+       "249328  15.6 degree_Celsius  \n",
+       "249331  16.0 degree_Celsius  \n",
        "\n",
-       "[8290 rows x 4 columns]"
+       "[8435 rows x 4 columns]"
       ]
      },
      "execution_count": 20,
@@ -2635,39 +2647,39 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>11071</th>\n",
+       "      <th>11084</th>\n",
        "      <td>6.70</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
        "      <td>6.7 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>12846</th>\n",
+       "      <th>12779</th>\n",
        "      <td>1.70</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
        "      <td>1.7 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>14341</th>\n",
+       "      <th>14367</th>\n",
        "      <td>1.70</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
        "      <td>1.7 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>14557</th>\n",
-       "      <td>1.30</td>\n",
+       "      <th>14585</th>\n",
+       "      <td>2.10</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>1.3 milligram / liter</td>\n",
+       "      <td>2.1 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>14623</th>\n",
-       "      <td>2.10</td>\n",
+       "      <td>1.30</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>2.1 milligram / liter</td>\n",
+       "      <td>1.3 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>...</th>\n",
@@ -2677,35 +2689,35 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247505</th>\n",
-       "      <td>5.20</td>\n",
+       "      <th>241652</th>\n",
+       "      <td>6.60</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>5.2 milligram / liter</td>\n",
+       "      <td>6.6 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247509</th>\n",
-       "      <td>8.10</td>\n",
+       "      <th>241656</th>\n",
+       "      <td>7.45</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>8.1 milligram / liter</td>\n",
+       "      <td>7.45 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247517</th>\n",
-       "      <td>5.50</td>\n",
+       "      <th>241689</th>\n",
+       "      <td>8.70</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>5.5 milligram / liter</td>\n",
+       "      <td>8.7 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247522</th>\n",
-       "      <td>7.25</td>\n",
+       "      <th>241690</th>\n",
+       "      <td>6.90</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>7.25 milligram / liter</td>\n",
+       "      <td>6.9 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247542</th>\n",
+       "      <th>241699</th>\n",
        "      <td>8.70</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
@@ -2713,37 +2725,37 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>414 rows × 4 columns</p>\n",
+       "<p>538 rows × 4 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
        "        ResultMeasureValue ResultMeasure/MeasureUnitCode QA_flag  \\\n",
-       "11071                 6.70                          mg/L     NaN   \n",
-       "12846                 1.70                          mg/L     NaN   \n",
-       "14341                 1.70                          mg/L     NaN   \n",
-       "14557                 1.30                          mg/L     NaN   \n",
-       "14623                 2.10                          mg/L     NaN   \n",
+       "11084                 6.70                          mg/L     NaN   \n",
+       "12779                 1.70                          mg/L     NaN   \n",
+       "14367                 1.70                          mg/L     NaN   \n",
+       "14585                 2.10                          mg/L     NaN   \n",
+       "14623                 1.30                          mg/L     NaN   \n",
        "...                    ...                           ...     ...   \n",
-       "247505                5.20                          mg/L     NaN   \n",
-       "247509                8.10                          mg/L     NaN   \n",
-       "247517                5.50                          mg/L     NaN   \n",
-       "247522                7.25                          mg/L     NaN   \n",
-       "247542                8.70                          mg/L     NaN   \n",
+       "241652                6.60                          mg/L     NaN   \n",
+       "241656                7.45                          mg/L     NaN   \n",
+       "241689                8.70                          mg/L     NaN   \n",
+       "241690                6.90                          mg/L     NaN   \n",
+       "241699                8.70                          mg/L     NaN   \n",
        "\n",
        "                            DO  \n",
-       "11071    6.7 milligram / liter  \n",
-       "12846    1.7 milligram / liter  \n",
-       "14341    1.7 milligram / liter  \n",
-       "14557    1.3 milligram / liter  \n",
-       "14623    2.1 milligram / liter  \n",
+       "11084    6.7 milligram / liter  \n",
+       "12779    1.7 milligram / liter  \n",
+       "14367    1.7 milligram / liter  \n",
+       "14585    2.1 milligram / liter  \n",
+       "14623    1.3 milligram / liter  \n",
        "...                        ...  \n",
-       "247505   5.2 milligram / liter  \n",
-       "247509   8.1 milligram / liter  \n",
-       "247517   5.5 milligram / liter  \n",
-       "247522  7.25 milligram / liter  \n",
-       "247542   8.7 milligram / liter  \n",
+       "241652   6.6 milligram / liter  \n",
+       "241656  7.45 milligram / liter  \n",
+       "241689   8.7 milligram / liter  \n",
+       "241690   6.9 milligram / liter  \n",
+       "241699   8.7 milligram / liter  \n",
        "\n",
-       "[414 rows x 4 columns]"
+       "[538 rows x 4 columns]"
       ]
      },
      "execution_count": 21,
@@ -2790,39 +2802,39 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>2</th>\n",
+       "      <th>1</th>\n",
        "      <td>7.9</td>\n",
        "      <td>None</td>\n",
        "      <td>NaN</td>\n",
        "      <td>7.9 dimensionless</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>7.8</td>\n",
+       "      <th>5</th>\n",
+       "      <td>8.2</td>\n",
        "      <td>None</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>7.8 dimensionless</td>\n",
+       "      <td>8.2 dimensionless</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>7.5</td>\n",
+       "      <th>6</th>\n",
+       "      <td>7.8</td>\n",
        "      <td>None</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>7.5 dimensionless</td>\n",
+       "      <td>7.8 dimensionless</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>7.4</td>\n",
+       "      <th>10</th>\n",
+       "      <td>7.3</td>\n",
        "      <td>None</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>7.4 dimensionless</td>\n",
+       "      <td>7.3 dimensionless</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>8.5</td>\n",
+       "      <th>17</th>\n",
+       "      <td>7.5</td>\n",
        "      <td>None</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>8.5 dimensionless</td>\n",
+       "      <td>7.5 dimensionless</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>...</th>\n",
@@ -2832,73 +2844,73 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248044</th>\n",
-       "      <td>8.1</td>\n",
+       "      <th>249320</th>\n",
+       "      <td>6.7</td>\n",
        "      <td>std units</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>8.1 dimensionless</td>\n",
+       "      <td>6.7 dimensionless</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248048</th>\n",
-       "      <td>7.0</td>\n",
+       "      <th>249323</th>\n",
+       "      <td>6.8</td>\n",
        "      <td>std units</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>7.0 dimensionless</td>\n",
+       "      <td>6.8 dimensionless</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248052</th>\n",
-       "      <td>7.3</td>\n",
+       "      <th>249326</th>\n",
+       "      <td>6.7</td>\n",
        "      <td>std units</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>7.3 dimensionless</td>\n",
+       "      <td>6.7 dimensionless</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248056</th>\n",
-       "      <td>7.8</td>\n",
+       "      <th>249329</th>\n",
+       "      <td>6.6</td>\n",
        "      <td>std units</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>7.8 dimensionless</td>\n",
+       "      <td>6.6 dimensionless</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248060</th>\n",
-       "      <td>7.2</td>\n",
+       "      <th>249332</th>\n",
+       "      <td>6.5</td>\n",
        "      <td>std units</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>7.2 dimensionless</td>\n",
+       "      <td>6.5 dimensionless</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>79050 rows × 4 columns</p>\n",
+       "<p>79481 rows × 4 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
        "        ResultMeasureValue ResultMeasure/MeasureUnitCode QA_flag  \\\n",
-       "2                      7.9                          None     NaN   \n",
-       "3                      7.8                          None     NaN   \n",
-       "4                      7.5                          None     NaN   \n",
-       "5                      7.4                          None     NaN   \n",
-       "7                      8.5                          None     NaN   \n",
+       "1                      7.9                          None     NaN   \n",
+       "5                      8.2                          None     NaN   \n",
+       "6                      7.8                          None     NaN   \n",
+       "10                     7.3                          None     NaN   \n",
+       "17                     7.5                          None     NaN   \n",
        "...                    ...                           ...     ...   \n",
-       "248044                 8.1                     std units     NaN   \n",
-       "248048                 7.0                     std units     NaN   \n",
-       "248052                 7.3                     std units     NaN   \n",
-       "248056                 7.8                     std units     NaN   \n",
-       "248060                 7.2                     std units     NaN   \n",
+       "249320                 6.7                     std units     NaN   \n",
+       "249323                 6.8                     std units     NaN   \n",
+       "249326                 6.7                     std units     NaN   \n",
+       "249329                 6.6                     std units     NaN   \n",
+       "249332                 6.5                     std units     NaN   \n",
        "\n",
        "                       pH  \n",
-       "2       7.9 dimensionless  \n",
-       "3       7.8 dimensionless  \n",
-       "4       7.5 dimensionless  \n",
-       "5       7.4 dimensionless  \n",
-       "7       8.5 dimensionless  \n",
+       "1       7.9 dimensionless  \n",
+       "5       8.2 dimensionless  \n",
+       "6       7.8 dimensionless  \n",
+       "10      7.3 dimensionless  \n",
+       "17      7.5 dimensionless  \n",
        "...                   ...  \n",
-       "248044  8.1 dimensionless  \n",
-       "248048  7.0 dimensionless  \n",
-       "248052  7.3 dimensionless  \n",
-       "248056  7.8 dimensionless  \n",
-       "248060  7.2 dimensionless  \n",
+       "249320  6.7 dimensionless  \n",
+       "249323  6.8 dimensionless  \n",
+       "249326  6.7 dimensionless  \n",
+       "249329  6.6 dimensionless  \n",
+       "249332  6.5 dimensionless  \n",
        "\n",
-       "[79050 rows x 4 columns]"
+       "[79481 rows x 4 columns]"
       ]
      },
      "execution_count": 22,
@@ -2945,39 +2957,39 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>11</th>\n",
+       "      <th>4</th>\n",
        "      <td>28.2</td>\n",
        "      <td>ppt</td>\n",
        "      <td>NaN</td>\n",
        "      <td>28.2 Practical_Salinity_Units</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>12</th>\n",
-       "      <td>6.8</td>\n",
+       "      <th>7</th>\n",
+       "      <td>25.6</td>\n",
        "      <td>ppt</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>6.8 Practical_Salinity_Units</td>\n",
+       "      <td>25.6 Practical_Salinity_Units</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>19</th>\n",
-       "      <td>25.6</td>\n",
+       "      <th>14</th>\n",
+       "      <td>3.8</td>\n",
        "      <td>ppt</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>25.6 Practical_Salinity_Units</td>\n",
+       "      <td>3.8 Practical_Salinity_Units</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>23</th>\n",
-       "      <td>26.7</td>\n",
+       "      <th>15</th>\n",
+       "      <td>12.0</td>\n",
        "      <td>ppt</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>26.7 Practical_Salinity_Units</td>\n",
+       "      <td>12.0 Practical_Salinity_Units</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>33</th>\n",
-       "      <td>32.4</td>\n",
+       "      <th>24</th>\n",
+       "      <td>20.3</td>\n",
        "      <td>ppt</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>32.4 Practical_Salinity_Units</td>\n",
+       "      <td>20.3 Practical_Salinity_Units</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>...</th>\n",
@@ -2987,73 +2999,73 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247530</th>\n",
-       "      <td>9.9</td>\n",
+       "      <th>243312</th>\n",
+       "      <td>18.8</td>\n",
        "      <td>ppt</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>9.9 Practical_Salinity_Units</td>\n",
+       "      <td>18.8 Practical_Salinity_Units</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247536</th>\n",
-       "      <td>3.2</td>\n",
+       "      <th>243385</th>\n",
+       "      <td>20.1</td>\n",
        "      <td>ppt</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>3.2 Practical_Salinity_Units</td>\n",
+       "      <td>20.1 Practical_Salinity_Units</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247537</th>\n",
-       "      <td>3.1</td>\n",
+       "      <th>249022</th>\n",
+       "      <td>10.9</td>\n",
        "      <td>ppt</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>3.1 Practical_Salinity_Units</td>\n",
+       "      <td>10.9 Practical_Salinity_Units</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247539</th>\n",
-       "      <td>2.8</td>\n",
+       "      <th>249026</th>\n",
+       "      <td>6.8</td>\n",
        "      <td>ppt</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>2.8 Practical_Salinity_Units</td>\n",
+       "      <td>6.8 Practical_Salinity_Units</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247541</th>\n",
-       "      <td>2.8</td>\n",
+       "      <th>249027</th>\n",
+       "      <td>12.9</td>\n",
        "      <td>ppt</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>2.8 Practical_Salinity_Units</td>\n",
+       "      <td>12.9 Practical_Salinity_Units</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>37155 rows × 4 columns</p>\n",
+       "<p>37421 rows × 4 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
        "        ResultMeasureValue ResultMeasure/MeasureUnitCode QA_flag  \\\n",
-       "11                    28.2                           ppt     NaN   \n",
-       "12                     6.8                           ppt     NaN   \n",
-       "19                    25.6                           ppt     NaN   \n",
-       "23                    26.7                           ppt     NaN   \n",
-       "33                    32.4                           ppt     NaN   \n",
+       "4                     28.2                           ppt     NaN   \n",
+       "7                     25.6                           ppt     NaN   \n",
+       "14                     3.8                           ppt     NaN   \n",
+       "15                    12.0                           ppt     NaN   \n",
+       "24                    20.3                           ppt     NaN   \n",
        "...                    ...                           ...     ...   \n",
-       "247530                 9.9                           ppt     NaN   \n",
-       "247536                 3.2                           ppt     NaN   \n",
-       "247537                 3.1                           ppt     NaN   \n",
-       "247539                 2.8                           ppt     NaN   \n",
-       "247541                 2.8                           ppt     NaN   \n",
+       "243312                18.8                           ppt     NaN   \n",
+       "243385                20.1                           ppt     NaN   \n",
+       "249022                10.9                           ppt     NaN   \n",
+       "249026                 6.8                           ppt     NaN   \n",
+       "249027                12.9                           ppt     NaN   \n",
        "\n",
        "                             Salinity  \n",
-       "11      28.2 Practical_Salinity_Units  \n",
-       "12       6.8 Practical_Salinity_Units  \n",
-       "19      25.6 Practical_Salinity_Units  \n",
-       "23      26.7 Practical_Salinity_Units  \n",
-       "33      32.4 Practical_Salinity_Units  \n",
+       "4       28.2 Practical_Salinity_Units  \n",
+       "7       25.6 Practical_Salinity_Units  \n",
+       "14       3.8 Practical_Salinity_Units  \n",
+       "15      12.0 Practical_Salinity_Units  \n",
+       "24      20.3 Practical_Salinity_Units  \n",
        "...                               ...  \n",
-       "247530   9.9 Practical_Salinity_Units  \n",
-       "247536   3.2 Practical_Salinity_Units  \n",
-       "247537   3.1 Practical_Salinity_Units  \n",
-       "247539   2.8 Practical_Salinity_Units  \n",
-       "247541   2.8 Practical_Salinity_Units  \n",
+       "243312  18.8 Practical_Salinity_Units  \n",
+       "243385  20.1 Practical_Salinity_Units  \n",
+       "249022  10.9 Practical_Salinity_Units  \n",
+       "249026   6.8 Practical_Salinity_Units  \n",
+       "249027  12.9 Practical_Salinity_Units  \n",
        "\n",
-       "[37155 rows x 4 columns]"
+       "[37421 rows x 4 columns]"
       ]
      },
      "execution_count": 23,
@@ -3100,39 +3112,39 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>8</th>\n",
+       "      <th>3</th>\n",
        "      <td>0.62</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
        "      <td>0.62 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>28</th>\n",
-       "      <td>2.50</td>\n",
+       "      <th>29</th>\n",
+       "      <td>0.69</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>2.5 milligram / liter</td>\n",
+       "      <td>0.69 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>36</th>\n",
-       "      <td>2.40</td>\n",
+       "      <th>31</th>\n",
+       "      <td>2.80</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>2.4 milligram / liter</td>\n",
+       "      <td>2.8 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>44</th>\n",
-       "      <td>2.40</td>\n",
+       "      <th>81</th>\n",
+       "      <td>2.50</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>2.4 milligram / liter</td>\n",
+       "      <td>2.5 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>69</th>\n",
-       "      <td>0.69</td>\n",
+       "      <th>86</th>\n",
+       "      <td>2.40</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.69 milligram / liter</td>\n",
+       "      <td>2.4 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>...</th>\n",
@@ -3142,73 +3154,73 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>246784</th>\n",
-       "      <td>3.53</td>\n",
+       "      <th>247796</th>\n",
+       "      <td>1.29</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>3.53 milligram / liter</td>\n",
+       "      <td>1.29 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247226</th>\n",
-       "      <td>1.57</td>\n",
+       "      <th>247966</th>\n",
+       "      <td>1.34</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>1.57 milligram / liter</td>\n",
+       "      <td>1.34 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247433</th>\n",
-       "      <td>0.95</td>\n",
+       "      <th>248200</th>\n",
+       "      <td>1.23</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.95 milligram / liter</td>\n",
+       "      <td>1.23 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247438</th>\n",
-       "      <td>0.80</td>\n",
+       "      <th>248380</th>\n",
+       "      <td>3.53</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.8 milligram / liter</td>\n",
+       "      <td>3.53 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247511</th>\n",
-       "      <td>1.37</td>\n",
+       "      <th>248812</th>\n",
+       "      <td>1.57</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>1.37 milligram / liter</td>\n",
+       "      <td>1.57 milligram / liter</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>16329 rows × 4 columns</p>\n",
+       "<p>16388 rows × 4 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
        "        ResultMeasureValue ResultMeasure/MeasureUnitCode QA_flag  \\\n",
-       "8                     0.62                          mg/L     NaN   \n",
-       "28                    2.50                          mg/L     NaN   \n",
-       "36                    2.40                          mg/L     NaN   \n",
-       "44                    2.40                          mg/L     NaN   \n",
-       "69                    0.69                          mg/L     NaN   \n",
+       "3                     0.62                          mg/L     NaN   \n",
+       "29                    0.69                          mg/L     NaN   \n",
+       "31                    2.80                          mg/L     NaN   \n",
+       "81                    2.50                          mg/L     NaN   \n",
+       "86                    2.40                          mg/L     NaN   \n",
        "...                    ...                           ...     ...   \n",
-       "246784                3.53                          mg/L     NaN   \n",
-       "247226                1.57                          mg/L     NaN   \n",
-       "247433                0.95                          mg/L     NaN   \n",
-       "247438                0.80                          mg/L     NaN   \n",
-       "247511                1.37                          mg/L     NaN   \n",
+       "247796                1.29                          mg/L     NaN   \n",
+       "247966                1.34                          mg/L     NaN   \n",
+       "248200                1.23                          mg/L     NaN   \n",
+       "248380                3.53                          mg/L     NaN   \n",
+       "248812                1.57                          mg/L     NaN   \n",
        "\n",
        "                      Nitrogen  \n",
-       "8       0.62 milligram / liter  \n",
-       "28       2.5 milligram / liter  \n",
-       "36       2.4 milligram / liter  \n",
-       "44       2.4 milligram / liter  \n",
-       "69      0.69 milligram / liter  \n",
+       "3       0.62 milligram / liter  \n",
+       "29      0.69 milligram / liter  \n",
+       "31       2.8 milligram / liter  \n",
+       "81       2.5 milligram / liter  \n",
+       "86       2.4 milligram / liter  \n",
        "...                        ...  \n",
-       "246784  3.53 milligram / liter  \n",
-       "247226  1.57 milligram / liter  \n",
-       "247433  0.95 milligram / liter  \n",
-       "247438   0.8 milligram / liter  \n",
-       "247511  1.37 milligram / liter  \n",
+       "247796  1.29 milligram / liter  \n",
+       "247966  1.34 milligram / liter  \n",
+       "248200  1.23 milligram / liter  \n",
+       "248380  3.53 milligram / liter  \n",
+       "248812  1.57 milligram / liter  \n",
        "\n",
-       "[16329 rows x 4 columns]"
+       "[16388 rows x 4 columns]"
       ]
      },
      "execution_count": 24,
@@ -3266,39 +3278,39 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>17</th>\n",
-       "      <td>20.20</td>\n",
+       "      <th>11</th>\n",
+       "      <td>50.30</td>\n",
        "      <td>ug/L</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.0202 milligram / liter</td>\n",
+       "      <td>0.0503 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>27</th>\n",
-       "      <td>6.25</td>\n",
+       "      <th>18</th>\n",
+       "      <td>16.30</td>\n",
        "      <td>ug/L</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.00625 milligram / liter</td>\n",
+       "      <td>0.016300000000000002 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>30</th>\n",
-       "      <td>50.30</td>\n",
+       "      <th>35</th>\n",
+       "      <td>1.29</td>\n",
        "      <td>ug/L</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.0503 milligram / liter</td>\n",
+       "      <td>0.0012900000000000001 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>45</th>\n",
-       "      <td>16.30</td>\n",
+       "      <th>61</th>\n",
+       "      <td>11.60</td>\n",
        "      <td>ug/L</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.016300000000000002 milligram / liter</td>\n",
+       "      <td>0.0116 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>48</th>\n",
-       "      <td>45.00</td>\n",
+       "      <th>73</th>\n",
+       "      <td>20.20</td>\n",
        "      <td>ug/L</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.045 milligram / liter</td>\n",
+       "      <td>0.0202 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>...</th>\n",
@@ -3308,73 +3320,73 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247660</th>\n",
-       "      <td>2.80</td>\n",
-       "      <td>ug/l</td>\n",
+       "      <th>241681</th>\n",
+       "      <td>3.72</td>\n",
+       "      <td>ug/L</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.0028 milligram / liter</td>\n",
+       "      <td>0.00372 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247687</th>\n",
-       "      <td>24.00</td>\n",
-       "      <td>ug/l</td>\n",
+       "      <th>246877</th>\n",
+       "      <td>1.00</td>\n",
+       "      <td>ug/L</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.024 milligram / liter</td>\n",
+       "      <td>0.001 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247744</th>\n",
-       "      <td>5.20</td>\n",
-       "      <td>ug/l</td>\n",
+       "      <th>247193</th>\n",
+       "      <td>2.00</td>\n",
+       "      <td>ug/L</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.005200000000000001 milligram / liter</td>\n",
+       "      <td>0.002 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247786</th>\n",
-       "      <td>11.00</td>\n",
+       "      <th>249104</th>\n",
+       "      <td>10.80</td>\n",
        "      <td>ug/l</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.011 milligram / liter</td>\n",
+       "      <td>0.0108 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247803</th>\n",
-       "      <td>18.30</td>\n",
+       "      <th>249125</th>\n",
+       "      <td>10.80</td>\n",
        "      <td>ug/l</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.0183 milligram / liter</td>\n",
+       "      <td>0.0108 milligram / liter</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>7392 rows × 4 columns</p>\n",
+       "<p>7451 rows × 4 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
        "        ResultMeasureValue ResultMeasure/MeasureUnitCode QA_flag  \\\n",
-       "17                   20.20                          ug/L     NaN   \n",
-       "27                    6.25                          ug/L     NaN   \n",
-       "30                   50.30                          ug/L     NaN   \n",
-       "45                   16.30                          ug/L     NaN   \n",
-       "48                   45.00                          ug/L     NaN   \n",
+       "11                   50.30                          ug/L     NaN   \n",
+       "18                   16.30                          ug/L     NaN   \n",
+       "35                    1.29                          ug/L     NaN   \n",
+       "61                   11.60                          ug/L     NaN   \n",
+       "73                   20.20                          ug/L     NaN   \n",
        "...                    ...                           ...     ...   \n",
-       "247660                2.80                          ug/l     NaN   \n",
-       "247687               24.00                          ug/l     NaN   \n",
-       "247744                5.20                          ug/l     NaN   \n",
-       "247786               11.00                          ug/l     NaN   \n",
-       "247803               18.30                          ug/l     NaN   \n",
+       "241681                3.72                          ug/L     NaN   \n",
+       "246877                1.00                          ug/L     NaN   \n",
+       "247193                2.00                          ug/L     NaN   \n",
+       "249104               10.80                          ug/l     NaN   \n",
+       "249125               10.80                          ug/l     NaN   \n",
        "\n",
-       "                                   Chlorophyll  \n",
-       "17                    0.0202 milligram / liter  \n",
-       "27                   0.00625 milligram / liter  \n",
-       "30                    0.0503 milligram / liter  \n",
-       "45      0.016300000000000002 milligram / liter  \n",
-       "48                     0.045 milligram / liter  \n",
-       "...                                        ...  \n",
-       "247660                0.0028 milligram / liter  \n",
-       "247687                 0.024 milligram / liter  \n",
-       "247744  0.005200000000000001 milligram / liter  \n",
-       "247786                 0.011 milligram / liter  \n",
-       "247803                0.0183 milligram / liter  \n",
+       "                                    Chlorophyll  \n",
+       "11                     0.0503 milligram / liter  \n",
+       "18       0.016300000000000002 milligram / liter  \n",
+       "35      0.0012900000000000001 milligram / liter  \n",
+       "61                     0.0116 milligram / liter  \n",
+       "73                     0.0202 milligram / liter  \n",
+       "...                                         ...  \n",
+       "241681                0.00372 milligram / liter  \n",
+       "246877                  0.001 milligram / liter  \n",
+       "247193                  0.002 milligram / liter  \n",
+       "249104                 0.0108 milligram / liter  \n",
+       "249125                 0.0108 milligram / liter  \n",
        "\n",
-       "[7392 rows x 4 columns]"
+       "[7451 rows x 4 columns]"
       ]
      },
      "execution_count": 26,
@@ -3421,41 +3433,41 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>29</th>\n",
-       "      <td>8.00</td>\n",
-       "      <td>mg/L</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>8.0 milligram / liter</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>34</th>\n",
+       "      <th>12</th>\n",
        "      <td>5.00</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
        "      <td>5.0 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>39</th>\n",
+       "      <th>16</th>\n",
        "      <td>7.00</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
        "      <td>7.0 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>46</th>\n",
-       "      <td>6.00</td>\n",
+       "      <th>21</th>\n",
+       "      <td>5.00</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>6.0 milligram / liter</td>\n",
+       "      <td>5.0 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>54</th>\n",
+       "      <th>36</th>\n",
        "      <td>5.00</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
        "      <td>5.0 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
+       "      <th>53</th>\n",
+       "      <td>8.00</td>\n",
+       "      <td>mg/L</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8.0 milligram / liter</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>...</th>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
@@ -3463,73 +3475,73 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247933</th>\n",
-       "      <td>5.18</td>\n",
+       "      <th>249183</th>\n",
+       "      <td>6.16</td>\n",
        "      <td>mg/l</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>5.18 milligram / liter</td>\n",
+       "      <td>6.16 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247941</th>\n",
-       "      <td>10.60</td>\n",
+       "      <th>249215</th>\n",
+       "      <td>11.80</td>\n",
        "      <td>mg/l</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>10.6 milligram / liter</td>\n",
+       "      <td>11.8 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247942</th>\n",
-       "      <td>7.37</td>\n",
+       "      <th>249216</th>\n",
+       "      <td>7.05</td>\n",
        "      <td>mg/l</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>7.37 milligram / liter</td>\n",
+       "      <td>7.05 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247947</th>\n",
-       "      <td>9.90</td>\n",
+       "      <th>249280</th>\n",
+       "      <td>10.70</td>\n",
        "      <td>mg/l</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>9.9 milligram / liter</td>\n",
+       "      <td>10.7 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247948</th>\n",
-       "      <td>6.16</td>\n",
+       "      <th>249281</th>\n",
+       "      <td>6.15</td>\n",
        "      <td>mg/l</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>6.16 milligram / liter</td>\n",
+       "      <td>6.15 milligram / liter</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>8193 rows × 4 columns</p>\n",
+       "<p>8284 rows × 4 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
        "        ResultMeasureValue ResultMeasure/MeasureUnitCode QA_flag  \\\n",
-       "29                    8.00                          mg/L     NaN   \n",
-       "34                    5.00                          mg/L     NaN   \n",
-       "39                    7.00                          mg/L     NaN   \n",
-       "46                    6.00                          mg/L     NaN   \n",
-       "54                    5.00                          mg/L     NaN   \n",
+       "12                    5.00                          mg/L     NaN   \n",
+       "16                    7.00                          mg/L     NaN   \n",
+       "21                    5.00                          mg/L     NaN   \n",
+       "36                    5.00                          mg/L     NaN   \n",
+       "53                    8.00                          mg/L     NaN   \n",
        "...                    ...                           ...     ...   \n",
-       "247933                5.18                          mg/l     NaN   \n",
-       "247941               10.60                          mg/l     NaN   \n",
-       "247942                7.37                          mg/l     NaN   \n",
-       "247947                9.90                          mg/l     NaN   \n",
-       "247948                6.16                          mg/l     NaN   \n",
+       "249183                6.16                          mg/l     NaN   \n",
+       "249215               11.80                          mg/l     NaN   \n",
+       "249216                7.05                          mg/l     NaN   \n",
+       "249280               10.70                          mg/l     NaN   \n",
+       "249281                6.15                          mg/l     NaN   \n",
        "\n",
        "                        Carbon  \n",
-       "29       8.0 milligram / liter  \n",
-       "34       5.0 milligram / liter  \n",
-       "39       7.0 milligram / liter  \n",
-       "46       6.0 milligram / liter  \n",
-       "54       5.0 milligram / liter  \n",
+       "12       5.0 milligram / liter  \n",
+       "16       7.0 milligram / liter  \n",
+       "21       5.0 milligram / liter  \n",
+       "36       5.0 milligram / liter  \n",
+       "53       8.0 milligram / liter  \n",
        "...                        ...  \n",
-       "247933  5.18 milligram / liter  \n",
-       "247941  10.6 milligram / liter  \n",
-       "247942  7.37 milligram / liter  \n",
-       "247947   9.9 milligram / liter  \n",
-       "247948  6.16 milligram / liter  \n",
+       "249183  6.16 milligram / liter  \n",
+       "249215  11.8 milligram / liter  \n",
+       "249216  7.05 milligram / liter  \n",
+       "249280  10.7 milligram / liter  \n",
+       "249281  6.15 milligram / liter  \n",
        "\n",
-       "[8193 rows x 4 columns]"
+       "[8284 rows x 4 columns]"
       ]
      },
      "execution_count": 27,
@@ -3576,35 +3588,35 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>304</th>\n",
-       "      <td>3.0</td>\n",
-       "      <td>None</td>\n",
-       "      <td>ResultMeasure/MeasureUnitCode: 'None' UNDEFINE...</td>\n",
-       "      <td>3.0 Nephelometric_Turbidity_Units</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>334</th>\n",
+       "      <th>302</th>\n",
        "      <td>28.0</td>\n",
        "      <td>NTU</td>\n",
        "      <td>NaN</td>\n",
        "      <td>28.0 Nephelometric_Turbidity_Units</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>570</th>\n",
+       "      <th>370</th>\n",
+       "      <td>3.0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>ResultMeasure/MeasureUnitCode: 'None' UNDEFINE...</td>\n",
+       "      <td>3.0 Nephelometric_Turbidity_Units</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>565</th>\n",
        "      <td>3.0</td>\n",
        "      <td>None</td>\n",
        "      <td>ResultMeasure/MeasureUnitCode: 'None' UNDEFINE...</td>\n",
        "      <td>3.0 Nephelometric_Turbidity_Units</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>621</th>\n",
+       "      <th>588</th>\n",
        "      <td>2.0</td>\n",
        "      <td>None</td>\n",
        "      <td>ResultMeasure/MeasureUnitCode: 'None' UNDEFINE...</td>\n",
        "      <td>2.0 Nephelometric_Turbidity_Units</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>679</th>\n",
+       "      <th>686</th>\n",
        "      <td>2.0</td>\n",
        "      <td>None</td>\n",
        "      <td>ResultMeasure/MeasureUnitCode: 'None' UNDEFINE...</td>\n",
@@ -3618,86 +3630,86 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248046</th>\n",
-       "      <td>9.6</td>\n",
+       "      <th>249321</th>\n",
+       "      <td>35.0</td>\n",
        "      <td>FNU</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>9.6 Nephelometric_Turbidity_Units</td>\n",
+       "      <td>35.0 Nephelometric_Turbidity_Units</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248050</th>\n",
-       "      <td>18.0</td>\n",
+       "      <th>249324</th>\n",
+       "      <td>150.0</td>\n",
        "      <td>FNU</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>18.0 Nephelometric_Turbidity_Units</td>\n",
+       "      <td>150.0 Nephelometric_Turbidity_Units</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248054</th>\n",
-       "      <td>14.0</td>\n",
+       "      <th>249327</th>\n",
+       "      <td>56.0</td>\n",
        "      <td>FNU</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>14.0 Nephelometric_Turbidity_Units</td>\n",
+       "      <td>56.0 Nephelometric_Turbidity_Units</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248058</th>\n",
-       "      <td>46.0</td>\n",
+       "      <th>249330</th>\n",
+       "      <td>57.0</td>\n",
        "      <td>FNU</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>46.0 Nephelometric_Turbidity_Units</td>\n",
+       "      <td>57.0 Nephelometric_Turbidity_Units</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248062</th>\n",
-       "      <td>11.0</td>\n",
+       "      <th>249333</th>\n",
+       "      <td>49.0</td>\n",
        "      <td>FNU</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>11.0 Nephelometric_Turbidity_Units</td>\n",
+       "      <td>49.0 Nephelometric_Turbidity_Units</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>7342 rows × 4 columns</p>\n",
+       "<p>7363 rows × 4 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
        "        ResultMeasureValue ResultMeasure/MeasureUnitCode  \\\n",
-       "304                    3.0                          None   \n",
-       "334                   28.0                           NTU   \n",
-       "570                    3.0                          None   \n",
-       "621                    2.0                          None   \n",
-       "679                    2.0                          None   \n",
+       "302                   28.0                           NTU   \n",
+       "370                    3.0                          None   \n",
+       "565                    3.0                          None   \n",
+       "588                    2.0                          None   \n",
+       "686                    2.0                          None   \n",
        "...                    ...                           ...   \n",
-       "248046                 9.6                           FNU   \n",
-       "248050                18.0                           FNU   \n",
-       "248054                14.0                           FNU   \n",
-       "248058                46.0                           FNU   \n",
-       "248062                11.0                           FNU   \n",
+       "249321                35.0                           FNU   \n",
+       "249324               150.0                           FNU   \n",
+       "249327                56.0                           FNU   \n",
+       "249330                57.0                           FNU   \n",
+       "249333                49.0                           FNU   \n",
        "\n",
        "                                                  QA_flag  \\\n",
-       "304     ResultMeasure/MeasureUnitCode: 'None' UNDEFINE...   \n",
-       "334                                                   NaN   \n",
-       "570     ResultMeasure/MeasureUnitCode: 'None' UNDEFINE...   \n",
-       "621     ResultMeasure/MeasureUnitCode: 'None' UNDEFINE...   \n",
-       "679     ResultMeasure/MeasureUnitCode: 'None' UNDEFINE...   \n",
+       "302                                                   NaN   \n",
+       "370     ResultMeasure/MeasureUnitCode: 'None' UNDEFINE...   \n",
+       "565     ResultMeasure/MeasureUnitCode: 'None' UNDEFINE...   \n",
+       "588     ResultMeasure/MeasureUnitCode: 'None' UNDEFINE...   \n",
+       "686     ResultMeasure/MeasureUnitCode: 'None' UNDEFINE...   \n",
        "...                                                   ...   \n",
-       "248046                                                NaN   \n",
-       "248050                                                NaN   \n",
-       "248054                                                NaN   \n",
-       "248058                                                NaN   \n",
-       "248062                                                NaN   \n",
+       "249321                                                NaN   \n",
+       "249324                                                NaN   \n",
+       "249327                                                NaN   \n",
+       "249330                                                NaN   \n",
+       "249333                                                NaN   \n",
        "\n",
-       "                                 Turbidity  \n",
-       "304      3.0 Nephelometric_Turbidity_Units  \n",
-       "334     28.0 Nephelometric_Turbidity_Units  \n",
-       "570      3.0 Nephelometric_Turbidity_Units  \n",
-       "621      2.0 Nephelometric_Turbidity_Units  \n",
-       "679      2.0 Nephelometric_Turbidity_Units  \n",
-       "...                                    ...  \n",
-       "248046   9.6 Nephelometric_Turbidity_Units  \n",
-       "248050  18.0 Nephelometric_Turbidity_Units  \n",
-       "248054  14.0 Nephelometric_Turbidity_Units  \n",
-       "248058  46.0 Nephelometric_Turbidity_Units  \n",
-       "248062  11.0 Nephelometric_Turbidity_Units  \n",
+       "                                  Turbidity  \n",
+       "302      28.0 Nephelometric_Turbidity_Units  \n",
+       "370       3.0 Nephelometric_Turbidity_Units  \n",
+       "565       3.0 Nephelometric_Turbidity_Units  \n",
+       "588       2.0 Nephelometric_Turbidity_Units  \n",
+       "686       2.0 Nephelometric_Turbidity_Units  \n",
+       "...                                     ...  \n",
+       "249321   35.0 Nephelometric_Turbidity_Units  \n",
+       "249324  150.0 Nephelometric_Turbidity_Units  \n",
+       "249327   56.0 Nephelometric_Turbidity_Units  \n",
+       "249330   57.0 Nephelometric_Turbidity_Units  \n",
+       "249333   49.0 Nephelometric_Turbidity_Units  \n",
        "\n",
-       "[7342 rows x 4 columns]"
+       "[7363 rows x 4 columns]"
       ]
      },
      "execution_count": 28,
@@ -3744,35 +3756,35 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>220118</th>\n",
+       "      <th>221899</th>\n",
        "      <td>0.0091</td>\n",
        "      <td>g</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>220119</th>\n",
+       "      <th>221900</th>\n",
        "      <td>0.0091</td>\n",
        "      <td>g</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>220120</th>\n",
+       "      <th>221901</th>\n",
        "      <td>0.0000</td>\n",
        "      <td>g</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>220140</th>\n",
+       "      <th>221921</th>\n",
        "      <td>0.0140</td>\n",
        "      <td>g</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>220141</th>\n",
+       "      <th>221922</th>\n",
        "      <td>0.0136</td>\n",
        "      <td>g</td>\n",
        "      <td>NaN</td>\n",
@@ -3786,35 +3798,35 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248038</th>\n",
+       "      <th>249294</th>\n",
        "      <td>0.1214</td>\n",
        "      <td>g</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248039</th>\n",
+       "      <th>249295</th>\n",
        "      <td>0.0116</td>\n",
        "      <td>g</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248040</th>\n",
+       "      <th>249296</th>\n",
        "      <td>0.1478</td>\n",
        "      <td>g</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248041</th>\n",
+       "      <th>249297</th>\n",
        "      <td>0.1410</td>\n",
        "      <td>g</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248042</th>\n",
+       "      <th>249298</th>\n",
        "      <td>0.0068</td>\n",
        "      <td>g</td>\n",
        "      <td>NaN</td>\n",
@@ -3822,24 +3834,24 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>677 rows × 4 columns</p>\n",
+       "<p>529 rows × 4 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "        ResultMeasureValue ResultMeasure/MeasureUnitCode QA_flag Sediment\n",
-       "220118              0.0091                             g     NaN      NaN\n",
-       "220119              0.0091                             g     NaN      NaN\n",
-       "220120              0.0000                             g     NaN      NaN\n",
-       "220140              0.0140                             g     NaN      NaN\n",
-       "220141              0.0136                             g     NaN      NaN\n",
-       "...                    ...                           ...     ...      ...\n",
-       "248038              0.1214                             g     NaN      NaN\n",
-       "248039              0.0116                             g     NaN      NaN\n",
-       "248040              0.1478                             g     NaN      NaN\n",
-       "248041              0.1410                             g     NaN      NaN\n",
-       "248042              0.0068                             g     NaN      NaN\n",
+       "        ResultMeasureValue ResultMeasure/MeasureUnitCode QA_flag  Sediment\n",
+       "221899              0.0091                             g     NaN       NaN\n",
+       "221900              0.0091                             g     NaN       NaN\n",
+       "221901              0.0000                             g     NaN       NaN\n",
+       "221921              0.0140                             g     NaN       NaN\n",
+       "221922              0.0136                             g     NaN       NaN\n",
+       "...                    ...                           ...     ...       ...\n",
+       "249294              0.1214                             g     NaN       NaN\n",
+       "249295              0.0116                             g     NaN       NaN\n",
+       "249296              0.1478                             g     NaN       NaN\n",
+       "249297              0.1410                             g     NaN       NaN\n",
+       "249298              0.0068                             g     NaN       NaN\n",
        "\n",
-       "[677 rows x 4 columns]"
+       "[529 rows x 4 columns]"
       ]
      },
      "execution_count": 29,
@@ -3888,35 +3900,35 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>196696</th>\n",
+       "      <th>201017</th>\n",
        "      <td>0.060</td>\n",
        "      <td>mg/l as P</td>\n",
        "      <td>NaN</td>\n",
        "      <td>0.06 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>196772</th>\n",
+       "      <th>201093</th>\n",
        "      <td>0.020</td>\n",
        "      <td>mg/l as P</td>\n",
        "      <td>NaN</td>\n",
        "      <td>0.02 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>196821</th>\n",
+       "      <th>201142</th>\n",
        "      <td>0.070</td>\n",
        "      <td>mg/l as P</td>\n",
        "      <td>NaN</td>\n",
        "      <td>0.07 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>197032</th>\n",
+       "      <th>201353</th>\n",
        "      <td>0.020</td>\n",
        "      <td>mg/l as P</td>\n",
        "      <td>NaN</td>\n",
        "      <td>0.02 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>197105</th>\n",
+       "      <th>201426</th>\n",
        "      <td>0.030</td>\n",
        "      <td>mg/l as P</td>\n",
        "      <td>NaN</td>\n",
@@ -3930,73 +3942,73 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247740</th>\n",
-       "      <td>0.049</td>\n",
+       "      <th>249121</th>\n",
+       "      <td>0.096</td>\n",
        "      <td>mg/l as P</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.049 milligram / liter</td>\n",
+       "      <td>0.096 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247767</th>\n",
-       "      <td>0.050</td>\n",
+       "      <th>249135</th>\n",
+       "      <td>0.070</td>\n",
        "      <td>mg/l as P</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.05 milligram / liter</td>\n",
+       "      <td>0.07 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247782</th>\n",
-       "      <td>0.038</td>\n",
+       "      <th>249141</th>\n",
+       "      <td>0.050</td>\n",
        "      <td>mg/l as P</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.038 milligram / liter</td>\n",
+       "      <td>0.05 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247799</th>\n",
-       "      <td>0.039</td>\n",
+       "      <th>249147</th>\n",
+       "      <td>0.090</td>\n",
        "      <td>mg/l as P</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.039 milligram / liter</td>\n",
+       "      <td>0.09 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247816</th>\n",
-       "      <td>0.040</td>\n",
+       "      <th>249153</th>\n",
+       "      <td>0.060</td>\n",
        "      <td>mg/l as P</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.04 milligram / liter</td>\n",
+       "      <td>0.06 milligram / liter</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>812 rows × 4 columns</p>\n",
+       "<p>820 rows × 4 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
        "        ResultMeasureValue ResultMeasure/MeasureUnitCode QA_flag  \\\n",
-       "196696               0.060                     mg/l as P     NaN   \n",
-       "196772               0.020                     mg/l as P     NaN   \n",
-       "196821               0.070                     mg/l as P     NaN   \n",
-       "197032               0.020                     mg/l as P     NaN   \n",
-       "197105               0.030                     mg/l as P     NaN   \n",
+       "201017               0.060                     mg/l as P     NaN   \n",
+       "201093               0.020                     mg/l as P     NaN   \n",
+       "201142               0.070                     mg/l as P     NaN   \n",
+       "201353               0.020                     mg/l as P     NaN   \n",
+       "201426               0.030                     mg/l as P     NaN   \n",
        "...                    ...                           ...     ...   \n",
-       "247740               0.049                     mg/l as P     NaN   \n",
-       "247767               0.050                     mg/l as P     NaN   \n",
-       "247782               0.038                     mg/l as P     NaN   \n",
-       "247799               0.039                     mg/l as P     NaN   \n",
-       "247816               0.040                     mg/l as P     NaN   \n",
+       "249121               0.096                     mg/l as P     NaN   \n",
+       "249135               0.070                     mg/l as P     NaN   \n",
+       "249141               0.050                     mg/l as P     NaN   \n",
+       "249147               0.090                     mg/l as P     NaN   \n",
+       "249153               0.060                     mg/l as P     NaN   \n",
        "\n",
        "                 TDP_Phosphorus  \n",
-       "196696   0.06 milligram / liter  \n",
-       "196772   0.02 milligram / liter  \n",
-       "196821   0.07 milligram / liter  \n",
-       "197032   0.02 milligram / liter  \n",
-       "197105   0.03 milligram / liter  \n",
+       "201017   0.06 milligram / liter  \n",
+       "201093   0.02 milligram / liter  \n",
+       "201142   0.07 milligram / liter  \n",
+       "201353   0.02 milligram / liter  \n",
+       "201426   0.03 milligram / liter  \n",
        "...                         ...  \n",
-       "247740  0.049 milligram / liter  \n",
-       "247767   0.05 milligram / liter  \n",
-       "247782  0.038 milligram / liter  \n",
-       "247799  0.039 milligram / liter  \n",
-       "247816   0.04 milligram / liter  \n",
+       "249121  0.096 milligram / liter  \n",
+       "249135   0.07 milligram / liter  \n",
+       "249141   0.05 milligram / liter  \n",
+       "249147   0.09 milligram / liter  \n",
+       "249153   0.06 milligram / liter  \n",
        "\n",
-       "[812 rows x 4 columns]"
+       "[820 rows x 4 columns]"
       ]
      },
      "execution_count": 30,
@@ -4043,35 +4055,35 @@
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>346</th>\n",
+       "      <th>309</th>\n",
        "      <td>0.16</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
        "      <td>0.16 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>620</th>\n",
+       "      <th>587</th>\n",
        "      <td>0.08</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
        "      <td>0.08 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>692</th>\n",
+       "      <th>693</th>\n",
        "      <td>0.81</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
        "      <td>0.81 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>729</th>\n",
+       "      <th>767</th>\n",
        "      <td>0.18</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
        "      <td>0.18 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1054</th>\n",
+       "      <th>1074</th>\n",
        "      <td>0.33</td>\n",
        "      <td>mg/L</td>\n",
        "      <td>NaN</td>\n",
@@ -4085,73 +4097,73 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247870</th>\n",
-       "      <td>0.25</td>\n",
+       "      <th>249163</th>\n",
+       "      <td>0.11</td>\n",
        "      <td>mg/l as P</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.25 milligram / liter</td>\n",
+       "      <td>0.11 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247922</th>\n",
-       "      <td>0.33</td>\n",
+       "      <th>249175</th>\n",
+       "      <td>0.18</td>\n",
        "      <td>mg/l as P</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.33 milligram / liter</td>\n",
+       "      <td>0.18 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247931</th>\n",
-       "      <td>0.11</td>\n",
+       "      <th>249181</th>\n",
+       "      <td>0.30</td>\n",
        "      <td>mg/l as P</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.11 milligram / liter</td>\n",
+       "      <td>0.3 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247940</th>\n",
-       "      <td>0.18</td>\n",
+       "      <th>249214</th>\n",
+       "      <td>0.22</td>\n",
        "      <td>mg/l as P</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.18 milligram / liter</td>\n",
+       "      <td>0.22 milligram / liter</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>247946</th>\n",
-       "      <td>0.30</td>\n",
+       "      <th>249279</th>\n",
+       "      <td>0.32</td>\n",
        "      <td>mg/l as P</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>0.3 milligram / liter</td>\n",
+       "      <td>0.32 milligram / liter</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>13677 rows × 4 columns</p>\n",
+       "<p>13760 rows × 4 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
        "        ResultMeasureValue ResultMeasure/MeasureUnitCode QA_flag  \\\n",
-       "346                   0.16                          mg/L     NaN   \n",
-       "620                   0.08                          mg/L     NaN   \n",
-       "692                   0.81                          mg/L     NaN   \n",
-       "729                   0.18                          mg/L     NaN   \n",
-       "1054                  0.33                          mg/L     NaN   \n",
+       "309                   0.16                          mg/L     NaN   \n",
+       "587                   0.08                          mg/L     NaN   \n",
+       "693                   0.81                          mg/L     NaN   \n",
+       "767                   0.18                          mg/L     NaN   \n",
+       "1074                  0.33                          mg/L     NaN   \n",
        "...                    ...                           ...     ...   \n",
-       "247870                0.25                     mg/l as P     NaN   \n",
-       "247922                0.33                     mg/l as P     NaN   \n",
-       "247931                0.11                     mg/l as P     NaN   \n",
-       "247940                0.18                     mg/l as P     NaN   \n",
-       "247946                0.30                     mg/l as P     NaN   \n",
+       "249163                0.11                     mg/l as P     NaN   \n",
+       "249175                0.18                     mg/l as P     NaN   \n",
+       "249181                0.30                     mg/l as P     NaN   \n",
+       "249214                0.22                     mg/l as P     NaN   \n",
+       "249279                0.32                     mg/l as P     NaN   \n",
        "\n",
        "                 TP_Phosphorus  \n",
-       "346     0.16 milligram / liter  \n",
-       "620     0.08 milligram / liter  \n",
-       "692     0.81 milligram / liter  \n",
-       "729     0.18 milligram / liter  \n",
-       "1054    0.33 milligram / liter  \n",
+       "309     0.16 milligram / liter  \n",
+       "587     0.08 milligram / liter  \n",
+       "693     0.81 milligram / liter  \n",
+       "767     0.18 milligram / liter  \n",
+       "1074    0.33 milligram / liter  \n",
        "...                        ...  \n",
-       "247870  0.25 milligram / liter  \n",
-       "247922  0.33 milligram / liter  \n",
-       "247931  0.11 milligram / liter  \n",
-       "247940  0.18 milligram / liter  \n",
-       "247946   0.3 milligram / liter  \n",
+       "249163  0.11 milligram / liter  \n",
+       "249175  0.18 milligram / liter  \n",
+       "249181   0.3 milligram / liter  \n",
+       "249214  0.22 milligram / liter  \n",
+       "249279  0.32 milligram / liter  \n",
        "\n",
-       "[13677 rows x 4 columns]"
+       "[13760 rows x 4 columns]"
       ]
      },
      "execution_count": 31,
@@ -4214,16 +4226,16 @@
        "      <th>DataLoggerLine</th>\n",
        "      <th>ResultDetectionConditionText</th>\n",
        "      <th>...</th>\n",
-       "      <th>QA_pH</th>\n",
-       "      <th>QA_DO</th>\n",
-       "      <th>QA_Fecal_Coliform</th>\n",
-       "      <th>QA_TP_Phosphorus</th>\n",
-       "      <th>QA_TDP_Phosphorus</th>\n",
-       "      <th>QA_Other_Phosphorus</th>\n",
-       "      <th>QA_Temperature</th>\n",
        "      <th>QA_Turbidity</th>\n",
-       "      <th>QA_Salinity</th>\n",
+       "      <th>QA_Chlorophyll</th>\n",
+       "      <th>QA_Nitrogen</th>\n",
+       "      <th>QA_DO</th>\n",
+       "      <th>QA_Sediment</th>\n",
        "      <th>QA_Conductivity</th>\n",
+       "      <th>QA_Secchi</th>\n",
+       "      <th>QA_Temperature</th>\n",
+       "      <th>QA_pH</th>\n",
+       "      <th>QA_Carbon</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
@@ -4231,12 +4243,12 @@
        "      <th>0</th>\n",
        "      <td>TCEQMAIN</td>\n",
        "      <td>Texas Commission on Environmental Quality</td>\n",
-       "      <td>TCEQMAIN-14363288</td>\n",
-       "      <td>2013-10-10</td>\n",
+       "      <td>TCEQMAIN-13702013</td>\n",
+       "      <td>2013-04-29</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>TCEQMAIN-11455</td>\n",
-       "      <td>STORET-422883712</td>\n",
+       "      <td>TCEQMAIN-15224</td>\n",
+       "      <td>STORET-422578803</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -4255,12 +4267,12 @@
        "      <th>1</th>\n",
        "      <td>TCEQMAIN</td>\n",
        "      <td>Texas Commission on Environmental Quality</td>\n",
-       "      <td>TCEQMAIN-13702013</td>\n",
-       "      <td>2013-04-29</td>\n",
+       "      <td>TCEQMAIN-13947279</td>\n",
+       "      <td>2013-07-11</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>TCEQMAIN-15224</td>\n",
-       "      <td>STORET-422578803</td>\n",
+       "      <td>TCEQMAIN-11446</td>\n",
+       "      <td>STORET-422881708</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -4279,12 +4291,12 @@
        "      <th>2</th>\n",
        "      <td>TCEQMAIN</td>\n",
        "      <td>Texas Commission on Environmental Quality</td>\n",
-       "      <td>TCEQMAIN-13947279</td>\n",
-       "      <td>2013-07-11</td>\n",
+       "      <td>TCEQMAIN-14329114</td>\n",
+       "      <td>2013-10-08</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>TCEQMAIN-11446</td>\n",
-       "      <td>STORET-422881708</td>\n",
+       "      <td>TCEQMAIN-15906</td>\n",
+       "      <td>STORET-422797456</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -4303,12 +4315,12 @@
        "      <th>3</th>\n",
        "      <td>TCEQMAIN</td>\n",
        "      <td>Texas Commission on Environmental Quality</td>\n",
-       "      <td>TCEQMAIN-14117837</td>\n",
-       "      <td>2013-01-28</td>\n",
+       "      <td>TCEQMAIN-13899297</td>\n",
+       "      <td>2013-08-01</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>TCEQMAIN-11370</td>\n",
-       "      <td>STORET-422872173</td>\n",
+       "      <td>TCEQMAIN-11287</td>\n",
+       "      <td>STORET-422829817</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -4327,12 +4339,12 @@
        "      <th>4</th>\n",
        "      <td>TCEQMAIN</td>\n",
        "      <td>Texas Commission on Environmental Quality</td>\n",
-       "      <td>TCEQMAIN-14208371</td>\n",
-       "      <td>2013-07-16</td>\n",
+       "      <td>TCEQMAIN-13702703</td>\n",
+       "      <td>2013-05-14</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>TCEQMAIN-16659</td>\n",
-       "      <td>STORET-423043742</td>\n",
+       "      <td>TCEQMAIN-15216</td>\n",
+       "      <td>STORET-422577293</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -4372,15 +4384,15 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248058</th>\n",
+       "      <th>249329</th>\n",
        "      <td>USGS-TX</td>\n",
        "      <td>USGS Texas Water Science Center</td>\n",
-       "      <td>nwistx.01.02302746</td>\n",
-       "      <td>2023-07-18</td>\n",
-       "      <td>11:45:00</td>\n",
-       "      <td>-0500</td>\n",
-       "      <td>USGS-08042554</td>\n",
-       "      <td>NWIS-125841792</td>\n",
+       "      <td>nwistx.01.02400657</td>\n",
+       "      <td>2024-01-25</td>\n",
+       "      <td>08:35:00</td>\n",
+       "      <td>-0600</td>\n",
+       "      <td>USGS-08042546</td>\n",
+       "      <td>NWIS-126809215</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -4396,15 +4408,15 @@
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248059</th>\n",
+       "      <th>249330</th>\n",
        "      <td>USGS-TX</td>\n",
        "      <td>USGS Texas Water Science Center</td>\n",
-       "      <td>nwistx.01.02302749</td>\n",
-       "      <td>2023-07-18</td>\n",
-       "      <td>12:45:00</td>\n",
-       "      <td>-0500</td>\n",
+       "      <td>nwistx.01.02400657</td>\n",
+       "      <td>2024-01-25</td>\n",
+       "      <td>08:35:00</td>\n",
+       "      <td>-0600</td>\n",
        "      <td>USGS-08042546</td>\n",
-       "      <td>NWIS-125842112</td>\n",
+       "      <td>NWIS-126809227</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -4420,15 +4432,15 @@
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248060</th>\n",
+       "      <th>249331</th>\n",
        "      <td>USGS-TX</td>\n",
        "      <td>USGS Texas Water Science Center</td>\n",
-       "      <td>nwistx.01.02302749</td>\n",
-       "      <td>2023-07-18</td>\n",
-       "      <td>12:45:00</td>\n",
-       "      <td>-0500</td>\n",
-       "      <td>USGS-08042546</td>\n",
-       "      <td>NWIS-125842120</td>\n",
+       "      <td>nwistx.01.02400659</td>\n",
+       "      <td>2024-01-25</td>\n",
+       "      <td>12:35:00</td>\n",
+       "      <td>-0600</td>\n",
+       "      <td>USGS-08042554</td>\n",
+       "      <td>NWIS-126809095</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -4444,15 +4456,15 @@
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248061</th>\n",
+       "      <th>249332</th>\n",
        "      <td>USGS-TX</td>\n",
        "      <td>USGS Texas Water Science Center</td>\n",
-       "      <td>nwistx.01.02302749</td>\n",
-       "      <td>2023-07-18</td>\n",
-       "      <td>12:45:00</td>\n",
-       "      <td>-0500</td>\n",
-       "      <td>USGS-08042546</td>\n",
-       "      <td>NWIS-125842125</td>\n",
+       "      <td>nwistx.01.02400659</td>\n",
+       "      <td>2024-01-25</td>\n",
+       "      <td>12:35:00</td>\n",
+       "      <td>-0600</td>\n",
+       "      <td>USGS-08042554</td>\n",
+       "      <td>NWIS-126809105</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -4468,15 +4480,15 @@
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>248062</th>\n",
+       "      <th>249333</th>\n",
        "      <td>USGS-TX</td>\n",
        "      <td>USGS Texas Water Science Center</td>\n",
-       "      <td>nwistx.01.02302749</td>\n",
-       "      <td>2023-07-18</td>\n",
-       "      <td>12:45:00</td>\n",
-       "      <td>-0500</td>\n",
-       "      <td>USGS-08042546</td>\n",
-       "      <td>NWIS-125842127</td>\n",
+       "      <td>nwistx.01.02400659</td>\n",
+       "      <td>2024-01-25</td>\n",
+       "      <td>12:35:00</td>\n",
+       "      <td>-0600</td>\n",
+       "      <td>USGS-08042554</td>\n",
+       "      <td>NWIS-126809117</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
@@ -4493,7 +4505,7 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>229824 rows × 114 columns</p>\n",
+       "<p>231057 rows × 115 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
@@ -4504,91 +4516,78 @@
        "3                    TCEQMAIN  Texas Commission on Environmental Quality   \n",
        "4                    TCEQMAIN  Texas Commission on Environmental Quality   \n",
        "...                       ...                                        ...   \n",
-       "248058                USGS-TX            USGS Texas Water Science Center   \n",
-       "248059                USGS-TX            USGS Texas Water Science Center   \n",
-       "248060                USGS-TX            USGS Texas Water Science Center   \n",
-       "248061                USGS-TX            USGS Texas Water Science Center   \n",
-       "248062                USGS-TX            USGS Texas Water Science Center   \n",
+       "249329                USGS-TX            USGS Texas Water Science Center   \n",
+       "249330                USGS-TX            USGS Texas Water Science Center   \n",
+       "249331                USGS-TX            USGS Texas Water Science Center   \n",
+       "249332                USGS-TX            USGS Texas Water Science Center   \n",
+       "249333                USGS-TX            USGS Texas Water Science Center   \n",
        "\n",
        "        ActivityIdentifier ActivityStartDate ActivityStartTime/Time  \\\n",
-       "0        TCEQMAIN-14363288        2013-10-10                    NaN   \n",
-       "1        TCEQMAIN-13702013        2013-04-29                    NaN   \n",
-       "2        TCEQMAIN-13947279        2013-07-11                    NaN   \n",
-       "3        TCEQMAIN-14117837        2013-01-28                    NaN   \n",
-       "4        TCEQMAIN-14208371        2013-07-16                    NaN   \n",
+       "0        TCEQMAIN-13702013        2013-04-29                    NaN   \n",
+       "1        TCEQMAIN-13947279        2013-07-11                    NaN   \n",
+       "2        TCEQMAIN-14329114        2013-10-08                    NaN   \n",
+       "3        TCEQMAIN-13899297        2013-08-01                    NaN   \n",
+       "4        TCEQMAIN-13702703        2013-05-14                    NaN   \n",
        "...                    ...               ...                    ...   \n",
-       "248058  nwistx.01.02302746        2023-07-18               11:45:00   \n",
-       "248059  nwistx.01.02302749        2023-07-18               12:45:00   \n",
-       "248060  nwistx.01.02302749        2023-07-18               12:45:00   \n",
-       "248061  nwistx.01.02302749        2023-07-18               12:45:00   \n",
-       "248062  nwistx.01.02302749        2023-07-18               12:45:00   \n",
+       "249329  nwistx.01.02400657        2024-01-25               08:35:00   \n",
+       "249330  nwistx.01.02400657        2024-01-25               08:35:00   \n",
+       "249331  nwistx.01.02400659        2024-01-25               12:35:00   \n",
+       "249332  nwistx.01.02400659        2024-01-25               12:35:00   \n",
+       "249333  nwistx.01.02400659        2024-01-25               12:35:00   \n",
        "\n",
        "       ActivityStartTime/TimeZoneCode MonitoringLocationIdentifier  \\\n",
-       "0                                 NaN               TCEQMAIN-11455   \n",
-       "1                                 NaN               TCEQMAIN-15224   \n",
-       "2                                 NaN               TCEQMAIN-11446   \n",
-       "3                                 NaN               TCEQMAIN-11370   \n",
-       "4                                 NaN               TCEQMAIN-16659   \n",
+       "0                                 NaN               TCEQMAIN-15224   \n",
+       "1                                 NaN               TCEQMAIN-11446   \n",
+       "2                                 NaN               TCEQMAIN-15906   \n",
+       "3                                 NaN               TCEQMAIN-11287   \n",
+       "4                                 NaN               TCEQMAIN-15216   \n",
        "...                               ...                          ...   \n",
-       "248058                          -0500                USGS-08042554   \n",
-       "248059                          -0500                USGS-08042546   \n",
-       "248060                          -0500                USGS-08042546   \n",
-       "248061                          -0500                USGS-08042546   \n",
-       "248062                          -0500                USGS-08042546   \n",
+       "249329                          -0600                USGS-08042546   \n",
+       "249330                          -0600                USGS-08042546   \n",
+       "249331                          -0600                USGS-08042554   \n",
+       "249332                          -0600                USGS-08042554   \n",
+       "249333                          -0600                USGS-08042554   \n",
        "\n",
        "        ResultIdentifier  DataLoggerLine ResultDetectionConditionText  ...  \\\n",
-       "0       STORET-422883712             NaN                          NaN  ...   \n",
-       "1       STORET-422578803             NaN                          NaN  ...   \n",
-       "2       STORET-422881708             NaN                          NaN  ...   \n",
-       "3       STORET-422872173             NaN                          NaN  ...   \n",
-       "4       STORET-423043742             NaN                          NaN  ...   \n",
+       "0       STORET-422578803             NaN                          NaN  ...   \n",
+       "1       STORET-422881708             NaN                          NaN  ...   \n",
+       "2       STORET-422797456             NaN                          NaN  ...   \n",
+       "3       STORET-422829817             NaN                          NaN  ...   \n",
+       "4       STORET-422577293             NaN                          NaN  ...   \n",
        "...                  ...             ...                          ...  ...   \n",
-       "248058    NWIS-125841792             NaN                          NaN  ...   \n",
-       "248059    NWIS-125842112             NaN                          NaN  ...   \n",
-       "248060    NWIS-125842120             NaN                          NaN  ...   \n",
-       "248061    NWIS-125842125             NaN                          NaN  ...   \n",
-       "248062    NWIS-125842127             NaN                          NaN  ...   \n",
-       "\n",
-       "       QA_pH QA_DO QA_Fecal_Coliform  QA_TP_Phosphorus QA_TDP_Phosphorus  \\\n",
-       "0        NaN   NaN               NaN               NaN               NaN   \n",
-       "1        NaN   NaN               NaN               NaN               NaN   \n",
-       "2        NaN   NaN               NaN               NaN               NaN   \n",
-       "3        NaN   NaN               NaN               NaN               NaN   \n",
-       "4        NaN   NaN               NaN               NaN               NaN   \n",
-       "...      ...   ...               ...               ...               ...   \n",
-       "248058   NaN   NaN               NaN               NaN               NaN   \n",
-       "248059   NaN   NaN               NaN               NaN               NaN   \n",
-       "248060   NaN   NaN               NaN               NaN               NaN   \n",
-       "248061   NaN   NaN               NaN               NaN               NaN   \n",
-       "248062   NaN   NaN               NaN               NaN               NaN   \n",
+       "249329    NWIS-126809215             NaN                          NaN  ...   \n",
+       "249330    NWIS-126809227             NaN                          NaN  ...   \n",
+       "249331    NWIS-126809095             NaN                          NaN  ...   \n",
+       "249332    NWIS-126809105             NaN                          NaN  ...   \n",
+       "249333    NWIS-126809117             NaN                          NaN  ...   \n",
        "\n",
-       "       QA_Other_Phosphorus QA_Temperature QA_Turbidity QA_Salinity  \\\n",
-       "0                      NaN            NaN          NaN         NaN   \n",
-       "1                      NaN            NaN          NaN         NaN   \n",
-       "2                      NaN            NaN          NaN         NaN   \n",
-       "3                      NaN            NaN          NaN         NaN   \n",
-       "4                      NaN            NaN          NaN         NaN   \n",
-       "...                    ...            ...          ...         ...   \n",
-       "248058                 NaN            NaN          NaN         NaN   \n",
-       "248059                 NaN            NaN          NaN         NaN   \n",
-       "248060                 NaN            NaN          NaN         NaN   \n",
-       "248061                 NaN            NaN          NaN         NaN   \n",
-       "248062                 NaN            NaN          NaN         NaN   \n",
+       "       QA_Turbidity QA_Chlorophyll QA_Nitrogen  QA_DO QA_Sediment  \\\n",
+       "0               NaN            NaN         NaN    NaN         NaN   \n",
+       "1               NaN            NaN         NaN    NaN         NaN   \n",
+       "2               NaN            NaN         NaN    NaN         NaN   \n",
+       "3               NaN            NaN         NaN    NaN         NaN   \n",
+       "4               NaN            NaN         NaN    NaN         NaN   \n",
+       "...             ...            ...         ...    ...         ...   \n",
+       "249329          NaN            NaN         NaN    NaN         NaN   \n",
+       "249330          NaN            NaN         NaN    NaN         NaN   \n",
+       "249331          NaN            NaN         NaN    NaN         NaN   \n",
+       "249332          NaN            NaN         NaN    NaN         NaN   \n",
+       "249333          NaN            NaN         NaN    NaN         NaN   \n",
        "\n",
-       "       QA_Conductivity  \n",
-       "0                  NaN  \n",
-       "1                  NaN  \n",
-       "2                  NaN  \n",
-       "3                  NaN  \n",
-       "4                  NaN  \n",
-       "...                ...  \n",
-       "248058             NaN  \n",
-       "248059             NaN  \n",
-       "248060             NaN  \n",
-       "248061             NaN  \n",
-       "248062             NaN  \n",
+       "       QA_Conductivity QA_Secchi QA_Temperature QA_pH QA_Carbon  \n",
+       "0                  NaN       NaN            NaN   NaN       NaN  \n",
+       "1                  NaN       NaN            NaN   NaN       NaN  \n",
+       "2                  NaN       NaN            NaN   NaN       NaN  \n",
+       "3                  NaN       NaN            NaN   NaN       NaN  \n",
+       "4                  NaN       NaN            NaN   NaN       NaN  \n",
+       "...                ...       ...            ...   ...       ...  \n",
+       "249329             NaN       NaN            NaN   NaN       NaN  \n",
+       "249330             NaN       NaN            NaN   NaN       NaN  \n",
+       "249331             NaN       NaN            NaN   NaN       NaN  \n",
+       "249332             NaN       NaN            NaN   NaN       NaN  \n",
+       "249333             NaN       NaN            NaN   NaN       NaN  \n",
        "\n",
-       "[229824 rows x 114 columns]"
+       "[231057 rows x 115 columns]"
       ]
      },
      "execution_count": 32,
@@ -4629,7 +4628,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "18239 fewer rows\n"
+      "18277 fewer rows\n"
      ]
     }
    ],
@@ -4719,14 +4718,15 @@
       "text/plain": [
        "Index(['OrganizationIdentifier', 'OrganizationFormalName',\n",
        "       'ActivityIdentifier', 'MonitoringLocationIdentifier', 'ProviderName',\n",
-       "       'E_coli', 'Secchi', 'Carbon', 'Speciation', 'Chlorophyll', 'Sediment',\n",
-       "       'Nitrogen', 'pH', 'DO', 'Fecal_Coliform', 'Phosphorus', 'TP_Phosphorus',\n",
-       "       'TDP_Phosphorus', 'Other_Phosphorus', 'Temperature', 'Turbidity',\n",
-       "       'Salinity', 'Conductivity', 'Activity_datetime', 'Depth', 'QA_E_coli',\n",
-       "       'QA_Secchi', 'QA_Carbon', 'QA_Chlorophyll', 'QA_Sediment',\n",
-       "       'QA_Nitrogen', 'QA_pH', 'QA_DO', 'QA_Fecal_Coliform',\n",
-       "       'QA_TP_Phosphorus', 'QA_TDP_Phosphorus', 'QA_Other_Phosphorus',\n",
-       "       'QA_Temperature', 'QA_Turbidity', 'QA_Salinity', 'QA_Conductivity'],\n",
+       "       'Chlorophyll', 'Conductivity', 'Secchi', 'DO', 'E_coli',\n",
+       "       'Fecal_Coliform', 'Nitrogen', 'Speciation',\n",
+       "       'TOTAL NITROGEN_ MIXED FORMS', 'Carbon', 'Phosphorus', 'TP_Phosphorus',\n",
+       "       'TDP_Phosphorus', 'Other_Phosphorus', 'Salinity', 'Sediment',\n",
+       "       'Temperature', 'Turbidity', 'pH', 'Activity_datetime', 'Depth',\n",
+       "       'QA_E_coli', 'QA_TP_Phosphorus', 'QA_TDP_Phosphorus',\n",
+       "       'QA_Other_Phosphorus', 'QA_Salinity', 'QA_Fecal_Coliform',\n",
+       "       'QA_Turbidity', 'QA_Chlorophyll', 'QA_Nitrogen', 'QA_DO', 'QA_Sediment',\n",
+       "       'QA_Conductivity', 'QA_Secchi', 'QA_Temperature', 'QA_pH', 'QA_Carbon'],\n",
        "      dtype='object')"
       ]
      },
@@ -4771,22 +4771,22 @@
        "      <th>ActivityIdentifier</th>\n",
        "      <th>MonitoringLocationIdentifier</th>\n",
        "      <th>ProviderName</th>\n",
-       "      <th>E_coli</th>\n",
-       "      <th>Secchi</th>\n",
-       "      <th>Carbon</th>\n",
-       "      <th>Speciation</th>\n",
        "      <th>Chlorophyll</th>\n",
+       "      <th>Conductivity</th>\n",
+       "      <th>Secchi</th>\n",
+       "      <th>DO</th>\n",
+       "      <th>E_coli</th>\n",
        "      <th>...</th>\n",
-       "      <th>QA_pH</th>\n",
-       "      <th>QA_DO</th>\n",
-       "      <th>QA_Fecal_Coliform</th>\n",
-       "      <th>QA_TP_Phosphorus</th>\n",
-       "      <th>QA_TDP_Phosphorus</th>\n",
-       "      <th>QA_Other_Phosphorus</th>\n",
-       "      <th>QA_Temperature</th>\n",
        "      <th>QA_Turbidity</th>\n",
-       "      <th>QA_Salinity</th>\n",
+       "      <th>QA_Chlorophyll</th>\n",
+       "      <th>QA_Nitrogen</th>\n",
+       "      <th>QA_DO</th>\n",
+       "      <th>QA_Sediment</th>\n",
        "      <th>QA_Conductivity</th>\n",
+       "      <th>QA_Secchi</th>\n",
+       "      <th>QA_Temperature</th>\n",
+       "      <th>QA_pH</th>\n",
+       "      <th>QA_Carbon</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
@@ -4794,13 +4794,13 @@
        "      <th>0</th>\n",
        "      <td>TCEQMAIN</td>\n",
        "      <td>Texas Commission on Environmental Quality</td>\n",
-       "      <td>TCEQMAIN-14363288</td>\n",
-       "      <td>TCEQMAIN-11455</td>\n",
+       "      <td>TCEQMAIN-13702013</td>\n",
+       "      <td>TCEQMAIN-15224</td>\n",
        "      <td>STORET</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>Phosphorus</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
@@ -4818,13 +4818,13 @@
        "      <th>1</th>\n",
        "      <td>TCEQMAIN</td>\n",
        "      <td>Texas Commission on Environmental Quality</td>\n",
-       "      <td>TCEQMAIN-13702013</td>\n",
-       "      <td>TCEQMAIN-15224</td>\n",
+       "      <td>TCEQMAIN-13947279</td>\n",
+       "      <td>TCEQMAIN-11446</td>\n",
        "      <td>STORET</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
-       "      <td>Phosphorus</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>...</td>\n",
        "      <td>NaN</td>\n",
@@ -4842,8 +4842,8 @@
        "      <th>2</th>\n",
        "      <td>TCEQMAIN</td>\n",
        "      <td>Texas Commission on Environmental Quality</td>\n",
-       "      <td>TCEQMAIN-13947279</td>\n",
-       "      <td>TCEQMAIN-11446</td>\n",
+       "      <td>TCEQMAIN-14329114</td>\n",
+       "      <td>TCEQMAIN-15906</td>\n",
        "      <td>STORET</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -4866,8 +4866,8 @@
        "      <th>3</th>\n",
        "      <td>TCEQMAIN</td>\n",
        "      <td>Texas Commission on Environmental Quality</td>\n",
-       "      <td>TCEQMAIN-14117837</td>\n",
-       "      <td>TCEQMAIN-11370</td>\n",
+       "      <td>TCEQMAIN-13899297</td>\n",
+       "      <td>TCEQMAIN-11287</td>\n",
        "      <td>STORET</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -4890,8 +4890,8 @@
        "      <th>4</th>\n",
        "      <td>TCEQMAIN</td>\n",
        "      <td>Texas Commission on Environmental Quality</td>\n",
-       "      <td>TCEQMAIN-14208371</td>\n",
-       "      <td>TCEQMAIN-16659</td>\n",
+       "      <td>TCEQMAIN-13702703</td>\n",
+       "      <td>TCEQMAIN-15216</td>\n",
        "      <td>STORET</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -4912,7 +4912,7 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>5 rows × 41 columns</p>\n",
+       "<p>5 rows × 42 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
@@ -4923,35 +4923,35 @@
        "3               TCEQMAIN  Texas Commission on Environmental Quality   \n",
        "4               TCEQMAIN  Texas Commission on Environmental Quality   \n",
        "\n",
-       "  ActivityIdentifier MonitoringLocationIdentifier ProviderName E_coli Secchi  \\\n",
-       "0  TCEQMAIN-14363288               TCEQMAIN-11455       STORET    NaN    NaN   \n",
-       "1  TCEQMAIN-13702013               TCEQMAIN-15224       STORET    NaN    NaN   \n",
-       "2  TCEQMAIN-13947279               TCEQMAIN-11446       STORET    NaN    NaN   \n",
-       "3  TCEQMAIN-14117837               TCEQMAIN-11370       STORET    NaN    NaN   \n",
-       "4  TCEQMAIN-14208371               TCEQMAIN-16659       STORET    NaN    NaN   \n",
+       "  ActivityIdentifier MonitoringLocationIdentifier ProviderName Chlorophyll  \\\n",
+       "0  TCEQMAIN-13702013               TCEQMAIN-15224       STORET         NaN   \n",
+       "1  TCEQMAIN-13947279               TCEQMAIN-11446       STORET         NaN   \n",
+       "2  TCEQMAIN-14329114               TCEQMAIN-15906       STORET         NaN   \n",
+       "3  TCEQMAIN-13899297               TCEQMAIN-11287       STORET         NaN   \n",
+       "4  TCEQMAIN-13702703               TCEQMAIN-15216       STORET         NaN   \n",
        "\n",
-       "  Carbon  Speciation Chlorophyll  ... QA_pH QA_DO QA_Fecal_Coliform  \\\n",
-       "0    NaN  Phosphorus         NaN  ...   NaN   NaN               NaN   \n",
-       "1    NaN  Phosphorus         NaN  ...   NaN   NaN               NaN   \n",
-       "2    NaN         NaN         NaN  ...   NaN   NaN               NaN   \n",
-       "3    NaN         NaN         NaN  ...   NaN   NaN               NaN   \n",
-       "4    NaN         NaN         NaN  ...   NaN   NaN               NaN   \n",
+       "  Conductivity Secchi   DO E_coli  ... QA_Turbidity QA_Chlorophyll  \\\n",
+       "0          NaN    NaN  NaN    NaN  ...          NaN            NaN   \n",
+       "1          NaN    NaN  NaN    NaN  ...          NaN            NaN   \n",
+       "2          NaN    NaN  NaN    NaN  ...          NaN            NaN   \n",
+       "3          NaN    NaN  NaN    NaN  ...          NaN            NaN   \n",
+       "4          NaN    NaN  NaN    NaN  ...          NaN            NaN   \n",
        "\n",
-       "  QA_TP_Phosphorus QA_TDP_Phosphorus QA_Other_Phosphorus QA_Temperature  \\\n",
-       "0              NaN               NaN                 NaN            NaN   \n",
-       "1              NaN               NaN                 NaN            NaN   \n",
-       "2              NaN               NaN                 NaN            NaN   \n",
-       "3              NaN               NaN                 NaN            NaN   \n",
-       "4              NaN               NaN                 NaN            NaN   \n",
+       "  QA_Nitrogen QA_DO QA_Sediment QA_Conductivity QA_Secchi QA_Temperature  \\\n",
+       "0         NaN   NaN         NaN             NaN       NaN            NaN   \n",
+       "1         NaN   NaN         NaN             NaN       NaN            NaN   \n",
+       "2         NaN   NaN         NaN             NaN       NaN            NaN   \n",
+       "3         NaN   NaN         NaN             NaN       NaN            NaN   \n",
+       "4         NaN   NaN         NaN             NaN       NaN            NaN   \n",
        "\n",
-       "  QA_Turbidity QA_Salinity QA_Conductivity  \n",
-       "0          NaN         NaN             NaN  \n",
-       "1          NaN         NaN             NaN  \n",
-       "2          NaN         NaN             NaN  \n",
-       "3          NaN         NaN             NaN  \n",
-       "4          NaN         NaN             NaN  \n",
+       "  QA_pH QA_Carbon  \n",
+       "0   NaN       NaN  \n",
+       "1   NaN       NaN  \n",
+       "2   NaN       NaN  \n",
+       "3   NaN       NaN  \n",
+       "4   NaN       NaN  \n",
        "\n",
-       "[5 rows x 41 columns]"
+       "[5 rows x 42 columns]"
       ]
      },
      "execution_count": 38,
@@ -4972,18 +4972,19 @@
     {
      "data": {
       "text/plain": [
-       "['QA_Secchi',\n",
-       " 'QA_Carbon',\n",
-       " 'QA_Sediment',\n",
-       " 'QA_Nitrogen',\n",
-       " 'QA_pH',\n",
-       " 'QA_DO',\n",
+       "['Sediment',\n",
        " 'QA_TP_Phosphorus',\n",
        " 'QA_TDP_Phosphorus',\n",
        " 'QA_Other_Phosphorus',\n",
-       " 'QA_Temperature',\n",
        " 'QA_Salinity',\n",
-       " 'QA_Conductivity']"
+       " 'QA_Nitrogen',\n",
+       " 'QA_DO',\n",
+       " 'QA_Sediment',\n",
+       " 'QA_Conductivity',\n",
+       " 'QA_Secchi',\n",
+       " 'QA_Temperature',\n",
+       " 'QA_pH',\n",
+       " 'QA_Carbon']"
       ]
      },
      "execution_count": 39,
@@ -5015,7 +5016,7 @@
     },
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]