Extract_Stations.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8b00a80b-1e9d-4a66-8111-39171dd26575",
   "metadata": {},
   "outputs": [],
   "source": [
    "station_file = \"/net/babaracus/home/benr/wqmodels/SSMC_Share/SSM_2014_v2.7hyak_chk/WQM/SSM_2014_DO_Ph_T52/outputs/ssm_station.out\"\n",
    "dest = \"model_results/stations.csv.gz\"\n",
    "\n",
    "water_vars = 52\n",
    "bottom_vars = 104\n",
    "\n",
    "from collections import deque\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from IPython.display import clear_output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1e0071e5-40d9-4b1c-8ca1-3904b7f1942d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TIME 6.75\n"
     ]
    }
   ],
   "source": [
    "with open(station_file) as fp:\n",
    "    # The first line is just a label\n",
    "    next(fp)\n",
    "    nstation, nlayer = np.loadtxt([next(fp)]).astype(int)\n",
    "    #print(\"Nstation\", nstation)\n",
    "    #print(\"Nlayer\", nlayer)\n",
    "    \n",
    "    def get_list_of_variable_names_from_line(line):\n",
    "        return line.replace(\"Variables=\", \"\").replace(\"\\\"\", \"\").rstrip().split(\",\")\n",
    "    variables_list = get_list_of_variable_names_from_line(next(fp))\n",
    "    #print(variables_list)\n",
    "    variables_list.insert(0, \"Time\")\n",
    "\n",
    "    data = {}\n",
    "    for v in variables_list:\n",
    "        data[v] = []\n",
    "    times = []\n",
    "\n",
    "    def read_block(varct, t):\n",
    "        block = []\n",
    "        for i, v in enumerate(variables_list):\n",
    "            if v == 'Time':\n",
    "                data[v].append(t)\n",
    "                continue\n",
    "            # The extra three is for the station, node, and layer\n",
    "            if i >= varct + 3:\n",
    "                # Fill in empty data that's not applicable to this layer\n",
    "                data[v].append(np.nan)\n",
    "                continue\n",
    "            if len(block) == 0:\n",
    "                block = deque(np.genfromtxt([next(fp)], missing_values='*************'))\n",
    "            data[v].append(block.popleft())\n",
    "\n",
    "    try:\n",
    "        while True:\n",
    "            # Read the number of stations/layers and the time\n",
    "            istation, ilayers, t = np.loadtxt([next(fp)])\n",
    "            istation = int(istation)\n",
    "            ilayers = int(ilayers)\n",
    "            times.append(t)\n",
    "            clear_output(wait = True)\n",
    "            print(\"TIME\", t)\n",
    "            for s in range(istation):\n",
    "                for l in range(ilayers-1):\n",
    "                    read_block(water_vars, t)\n",
    "                read_block(bottom_vars, t)\n",
    "    except StopIteration:\n",
    "        pass"
   ]
  },
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   "cell_type": "code",
   "execution_count": 3,
   "id": "1a882e74-d892-4a30-b8da-ce9e034a2472",
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   "outputs": [
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       "      <th></th>\n",
       "      <th>Time</th>\n",
       "      <th>StationID</th>\n",
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       "      <th>2</th>\n",
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       "      <td>0.003500</td>\n",
       "      <td>0.003</td>\n",
       "      <td>...</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.000463</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6151.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.263970</td>\n",
       "      <td>8.84907</td>\n",
       "      <td>0.434198</td>\n",
       "      <td>0.013402</td>\n",
       "      <td>0.003201</td>\n",
       "      <td>0.003</td>\n",
       "      <td>...</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>4</th>\n",
       "      <td>0.000463</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6151.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.197590</td>\n",
       "      <td>8.03486</td>\n",
       "      <td>0.429173</td>\n",
       "      <td>0.011206</td>\n",
       "      <td>0.003002</td>\n",
       "      <td>0.003</td>\n",
       "      <td>...</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "<p>5 rows × 108 columns</p>\n",
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      "text/plain": [
       "       Time  StationID    Node  Layer  depth(m)       DO       NO3       NH4  \\\n",
       "0  0.000463        1.0  6151.0    1.0  0.323122  9.74991  0.442787  0.018428   \n",
       "1  0.000463        1.0  6151.0    2.0  1.237050  9.71216  0.441843  0.018393   \n",
       "2  0.000463        1.0  6151.0    3.0  2.592920  9.39384  0.438833  0.016400   \n",
       "3  0.000463        1.0  6151.0    4.0  4.263970  8.84907  0.434198  0.013402   \n",
       "4  0.000463        1.0  6151.0    5.0  6.197590  8.03486  0.429173  0.011206   \n",
       "\n",
       "       Alg1   Alg2  ...  POC23  PON21  PON22  PON23  POP21  POP22  POP23  \\\n",
       "0  0.003604  0.003  ...    NaN    NaN    NaN    NaN    NaN    NaN    NaN   \n",
       "1  0.003599  0.003  ...    NaN    NaN    NaN    NaN    NaN    NaN    NaN   \n",
       "2  0.003500  0.003  ...    NaN    NaN    NaN    NaN    NaN    NaN    NaN   \n",
       "3  0.003201  0.003  ...    NaN    NaN    NaN    NaN    NaN    NaN    NaN   \n",
       "4  0.003002  0.003  ...    NaN    NaN    NaN    NaN    NaN    NaN    NaN   \n",
       "\n",
       "   POS2  H1  BEN_STR  \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",
       "[5 rows x 108 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(data)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "80a952b7-cdb5-444f-ba18-1b015c6c4cf4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "StationID\n",
       "1.0     6151.0\n",
       "2.0     7786.0\n",
       "3.0    11793.0\n",
       "4.0     4040.0\n",
       "5.0     5112.0\n",
       "Name: Node, dtype: float64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extract the station node IDs to a separate dataframe\n",
    "station_nodes = df[[\"StationID\",\"Node\"]].groupby('StationID')[\"Node\"].first()\n",
    "del df['StationID']\n",
    "station_nodes.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "52c33cd6-7d91-4fe2-8c87-69e135911aa5",
   "metadata": {},
   "outputs": [
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       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th>depth(m)</th>\n",
       "      <th>DO</th>\n",
       "      <th>NO3</th>\n",
       "      <th>NH4</th>\n",
       "      <th>Alg1</th>\n",
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       "      <th rowspan=\"5\" valign=\"top\">0.000463</th>\n",
       "      <th rowspan=\"5\" valign=\"top\">6151</th>\n",
       "      <th>1</th>\n",
       "      <td>0.323122</td>\n",
       "      <td>9.74991</td>\n",
       "      <td>0.442787</td>\n",
       "      <td>0.018428</td>\n",
       "      <td>0.003604</td>\n",
       "      <td>0.003</td>\n",
       "      <td>0.289448</td>\n",
       "      <td>0.251790</td>\n",
       "      <td>0.000200</td>\n",
       "      <td>0.000798</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.237050</td>\n",
       "      <td>9.71216</td>\n",
       "      <td>0.441843</td>\n",
       "      <td>0.018393</td>\n",
       "      <td>0.003599</td>\n",
       "      <td>0.003</td>\n",
       "      <td>0.288896</td>\n",
       "      <td>0.251310</td>\n",
       "      <td>0.000200</td>\n",
       "      <td>0.000800</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2.592920</td>\n",
       "      <td>9.39384</td>\n",
       "      <td>0.438833</td>\n",
       "      <td>0.016400</td>\n",
       "      <td>0.003500</td>\n",
       "      <td>0.003</td>\n",
       "      <td>0.285019</td>\n",
       "      <td>0.247718</td>\n",
       "      <td>0.000400</td>\n",
       "      <td>0.001400</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4.263970</td>\n",
       "      <td>8.84907</td>\n",
       "      <td>0.434198</td>\n",
       "      <td>0.013402</td>\n",
       "      <td>0.003201</td>\n",
       "      <td>0.003</td>\n",
       "      <td>0.281161</td>\n",
       "      <td>0.244453</td>\n",
       "      <td>0.000700</td>\n",
       "      <td>0.002300</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6.197590</td>\n",
       "      <td>8.03486</td>\n",
       "      <td>0.429173</td>\n",
       "      <td>0.011206</td>\n",
       "      <td>0.003002</td>\n",
       "      <td>0.003</td>\n",
       "      <td>0.274869</td>\n",
       "      <td>0.237044</td>\n",
       "      <td>0.001201</td>\n",
       "      <td>0.003903</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
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       "</table>\n",
       "<p>5 rows × 104 columns</p>\n",
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      ],
      "text/plain": [
       "                     depth(m)       DO       NO3       NH4      Alg1   Alg2  \\\n",
       "Time     Node Layer                                                           \n",
       "0.000463 6151 1      0.323122  9.74991  0.442787  0.018428  0.003604  0.003   \n",
       "              2      1.237050  9.71216  0.441843  0.018393  0.003599  0.003   \n",
       "              3      2.592920  9.39384  0.438833  0.016400  0.003500  0.003   \n",
       "              4      4.263970  8.84907  0.434198  0.013402  0.003201  0.003   \n",
       "              5      6.197590  8.03486  0.429173  0.011206  0.003002  0.003   \n",
       "\n",
       "                         LDOC      RDOC      LPOC      RPOC  ...  POC23  \\\n",
       "Time     Node Layer                                          ...          \n",
       "0.000463 6151 1      0.289448  0.251790  0.000200  0.000798  ...    NaN   \n",
       "              2      0.288896  0.251310  0.000200  0.000800  ...    NaN   \n",
       "              3      0.285019  0.247718  0.000400  0.001400  ...    NaN   \n",
       "              4      0.281161  0.244453  0.000700  0.002300  ...    NaN   \n",
       "              5      0.274869  0.237044  0.001201  0.003903  ...    NaN   \n",
       "\n",
       "                     PON21  PON22  PON23  POP21  POP22  POP23  POS2  H1  \\\n",
       "Time     Node Layer                                                       \n",
       "0.000463 6151 1        NaN    NaN    NaN    NaN    NaN    NaN   NaN NaN   \n",
       "              2        NaN    NaN    NaN    NaN    NaN    NaN   NaN NaN   \n",
       "              3        NaN    NaN    NaN    NaN    NaN    NaN   NaN NaN   \n",
       "              4        NaN    NaN    NaN    NaN    NaN    NaN   NaN NaN   \n",
       "              5        NaN    NaN    NaN    NaN    NaN    NaN   NaN NaN   \n",
       "\n",
       "                     BEN_STR  \n",
       "Time     Node Layer           \n",
       "0.000463 6151 1          NaN  \n",
       "              2          NaN  \n",
       "              3          NaN  \n",
       "              4          NaN  \n",
       "              5          NaN  \n",
       "\n",
       "[5 rows x 104 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Fix dtype for node and layer\n",
    "df['Node'] = df['Node'].astype(int)\n",
    "df['Layer'] = df['Layer'].astype(int)\n",
    "# Build the MultiIndex for time/node/layer\n",
    "mi = pd.MultiIndex.from_frame(df[[\"Time\",\"Node\",\"Layer\"]])\n",
    "del df['Time']\n",
    "del df['Node']\n",
    "del df['Layer']\n",
    "df.set_index(mi, inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a7f6d53-d193-4bee-b1f0-95ef010e480a",
   "metadata": {},
   "source": [
    "Save all of the output to a CSV, compressed.\n",
    "There is probably too much data for Excel to handle it as one gigantic file; see below if you want to get a spreadsheet of just one variable for one station."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f8f107b8-38a6-4ff1-9d4b-17f4699e59d4",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv(dest, compression=\"gzip\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "504c5893-a1db-4d81-b29a-25d973cfa070",
   "metadata": {
    "tags": []
   },
   "source": [
    "Example of how to save one station's output to Excel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "09cb9c63-0b8d-41d6-9ccf-fc02f3c10bb2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Time      Layer\n",
       "0.000463  1        8.88914\n",
       "          2        8.04703\n",
       "          3        7.08813\n",
       "          4        5.59414\n",
       "          5        5.03795\n",
       "                    ...   \n",
       "6.750000  6        4.34445\n",
       "          7        4.30333\n",
       "          8        4.24084\n",
       "          9        4.11616\n",
       "          10       3.96165\n",
       "Name: DO, Length: 280, dtype: float64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "node_to_save = 40\n",
    "var_to_save = \"DO\"\n",
    "\n",
    "# All times, just this station\n",
    "#      |         /  all layers\n",
    "#      |        /       |   just this variable\n",
    "#      |       /        |         /\n",
    "df.loc[:, node_to_save, :][var_to_save]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6669819e-b2e8-4e47-ad84-d0ae22b74b16",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.loc[:, node_to_save, :][var_to_save].to_excel(\"notebook_outs/node40_do.xlsx\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef73d996-0794-4c2a-890d-4bfa6250b39b",
   "metadata": {},
   "source": [
    "Grab the state variable output from all nodes in a single layer. The `dropna` call ensures the DataFrame will have no columns if a bottom-layer-only state variable is requested."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "2aa18bbf-7664-4fb1-9ead-3630f73a62b6",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th>Node</th>\n",
       "      <th>40</th>\n",
       "      <th>1424</th>\n",
       "      <th>4040</th>\n",
       "      <th>5112</th>\n",
       "      <th>5308</th>\n",
       "      <th>6151</th>\n",
       "      <th>6231</th>\n",
       "      <th>7294</th>\n",
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       "      <th>12166</th>\n",
       "      <th>13264</th>\n",
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       "      <th>15490</th>\n",
       "      <th>15903</th>\n",
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       "    <tr>\n",
       "      <th>Time</th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0.000463</th>\n",
       "      <td>8.88914</td>\n",
       "      <td>9.14636</td>\n",
       "      <td>8.63955</td>\n",
       "      <td>9.18824</td>\n",
       "      <td>9.07107</td>\n",
       "      <td>9.74991</td>\n",
       "      <td>8.15863</td>\n",
       "      <td>9.64832</td>\n",
       "      <td>9.64691</td>\n",
       "      <td>10.70430</td>\n",
       "      <td>...</td>\n",
       "      <td>10.05910</td>\n",
       "      <td>9.65705</td>\n",
       "      <td>9.78704</td>\n",
       "      <td>10.42120</td>\n",
       "      <td>9.41646</td>\n",
       "      <td>9.84068</td>\n",
       "      <td>9.55779</td>\n",
       "      <td>10.71930</td>\n",
       "      <td>10.25730</td>\n",
       "      <td>10.78920</td>\n",
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       "    <tr>\n",
       "      <th>0.250000</th>\n",
       "      <td>8.87130</td>\n",
       "      <td>9.07574</td>\n",
       "      <td>8.53041</td>\n",
       "      <td>8.74934</td>\n",
       "      <td>9.89064</td>\n",
       "      <td>9.37986</td>\n",
       "      <td>9.32571</td>\n",
       "      <td>9.57541</td>\n",
       "      <td>9.53682</td>\n",
       "      <td>10.23210</td>\n",
       "      <td>...</td>\n",
       "      <td>9.86172</td>\n",
       "      <td>9.53881</td>\n",
       "      <td>9.82993</td>\n",
       "      <td>10.61730</td>\n",
       "      <td>9.54964</td>\n",
       "      <td>9.63023</td>\n",
       "      <td>9.29671</td>\n",
       "      <td>10.41730</td>\n",
       "      <td>10.99670</td>\n",
       "      <td>10.86980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.500000</th>\n",
       "      <td>8.63889</td>\n",
       "      <td>8.85504</td>\n",
       "      <td>7.79561</td>\n",
       "      <td>8.52855</td>\n",
       "      <td>9.47001</td>\n",
       "      <td>9.95057</td>\n",
       "      <td>7.77888</td>\n",
       "      <td>9.45214</td>\n",
       "      <td>9.16340</td>\n",
       "      <td>9.52499</td>\n",
       "      <td>...</td>\n",
       "      <td>10.33250</td>\n",
       "      <td>9.45617</td>\n",
       "      <td>9.91140</td>\n",
       "      <td>9.51471</td>\n",
       "      <td>9.36187</td>\n",
       "      <td>9.50742</td>\n",
       "      <td>9.30183</td>\n",
       "      <td>10.18120</td>\n",
       "      <td>9.91834</td>\n",
       "      <td>10.48180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.750000</th>\n",
       "      <td>8.71468</td>\n",
       "      <td>9.03552</td>\n",
       "      <td>7.76934</td>\n",
       "      <td>9.03530</td>\n",
       "      <td>8.25365</td>\n",
       "      <td>10.33270</td>\n",
       "      <td>9.01649</td>\n",
       "      <td>9.63030</td>\n",
       "      <td>9.06807</td>\n",
       "      <td>7.92512</td>\n",
       "      <td>...</td>\n",
       "      <td>10.46710</td>\n",
       "      <td>9.40975</td>\n",
       "      <td>9.89702</td>\n",
       "      <td>9.11084</td>\n",
       "      <td>9.36636</td>\n",
       "      <td>9.18367</td>\n",
       "      <td>9.49366</td>\n",
       "      <td>10.58870</td>\n",
       "      <td>9.39015</td>\n",
       "      <td>10.33640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.000000</th>\n",
       "      <td>8.61930</td>\n",
       "      <td>8.90543</td>\n",
       "      <td>7.55615</td>\n",
       "      <td>9.15116</td>\n",
       "      <td>8.30097</td>\n",
       "      <td>10.06130</td>\n",
       "      <td>9.01233</td>\n",
       "      <td>9.51150</td>\n",
       "      <td>9.26795</td>\n",
       "      <td>9.14635</td>\n",
       "      <td>...</td>\n",
       "      <td>10.45700</td>\n",
       "      <td>9.31066</td>\n",
       "      <td>9.78804</td>\n",
       "      <td>8.38609</td>\n",
       "      <td>9.46486</td>\n",
       "      <td>9.28950</td>\n",
       "      <td>9.54329</td>\n",
       "      <td>10.38730</td>\n",
       "      <td>9.67648</td>\n",
       "      <td>10.41390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.250000</th>\n",
       "      <td>8.35042</td>\n",
       "      <td>8.61955</td>\n",
       "      <td>7.28585</td>\n",
       "      <td>8.50084</td>\n",
       "      <td>7.49276</td>\n",
       "      <td>9.65071</td>\n",
       "      <td>7.64612</td>\n",
       "      <td>9.55977</td>\n",
       "      <td>9.21367</td>\n",
       "      <td>8.83923</td>\n",
       "      <td>...</td>\n",
       "      <td>10.32750</td>\n",
       "      <td>9.22635</td>\n",
       "      <td>9.56974</td>\n",
       "      <td>8.50355</td>\n",
       "      <td>9.19299</td>\n",
       "      <td>8.90442</td>\n",
       "      <td>9.12326</td>\n",
       "      <td>9.95631</td>\n",
       "      <td>9.24615</td>\n",
       "      <td>9.15752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.500000</th>\n",
       "      <td>8.32351</td>\n",
       "      <td>8.02203</td>\n",
       "      <td>7.12841</td>\n",
       "      <td>8.54889</td>\n",
       "      <td>7.25524</td>\n",
       "      <td>8.74623</td>\n",
       "      <td>7.89922</td>\n",
       "      <td>9.46803</td>\n",
       "      <td>8.11143</td>\n",
       "      <td>8.30162</td>\n",
       "      <td>...</td>\n",
       "      <td>10.07670</td>\n",
       "      <td>8.94167</td>\n",
       "      <td>8.90907</td>\n",
       "      <td>8.21879</td>\n",
       "      <td>8.59956</td>\n",
       "      <td>8.81776</td>\n",
       "      <td>8.98322</td>\n",
       "      <td>9.42060</td>\n",
       "      <td>9.19993</td>\n",
       "      <td>9.55977</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.750000</th>\n",
       "      <td>8.34270</td>\n",
       "      <td>8.17748</td>\n",
       "      <td>7.28917</td>\n",
       "      <td>9.39997</td>\n",
       "      <td>7.67430</td>\n",
       "      <td>8.49504</td>\n",
       "      <td>8.19422</td>\n",
       "      <td>9.16735</td>\n",
       "      <td>8.23364</td>\n",
       "      <td>9.43222</td>\n",
       "      <td>...</td>\n",
       "      <td>9.73530</td>\n",
       "      <td>8.94402</td>\n",
       "      <td>8.88661</td>\n",
       "      <td>8.95248</td>\n",
       "      <td>8.48288</td>\n",
       "      <td>8.64000</td>\n",
       "      <td>8.93304</td>\n",
       "      <td>9.56404</td>\n",
       "      <td>9.46787</td>\n",
       "      <td>9.42363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.000000</th>\n",
       "      <td>8.38471</td>\n",
       "      <td>8.79249</td>\n",
       "      <td>7.58468</td>\n",
       "      <td>9.17462</td>\n",
       "      <td>7.76546</td>\n",
       "      <td>8.13759</td>\n",
       "      <td>8.64629</td>\n",
       "      <td>8.98421</td>\n",
       "      <td>8.10123</td>\n",
       "      <td>9.92250</td>\n",
       "      <td>...</td>\n",
       "      <td>9.65342</td>\n",
       "      <td>9.12748</td>\n",
       "      <td>9.14438</td>\n",
       "      <td>8.97913</td>\n",
       "      <td>8.38037</td>\n",
       "      <td>8.86621</td>\n",
       "      <td>9.17109</td>\n",
       "      <td>9.04909</td>\n",
       "      <td>9.87346</td>\n",
       "      <td>9.94183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.250000</th>\n",
       "      <td>8.35790</td>\n",
       "      <td>8.76385</td>\n",
       "      <td>8.20808</td>\n",
       "      <td>9.13733</td>\n",
       "      <td>8.14755</td>\n",
       "      <td>9.73276</td>\n",
       "      <td>8.24358</td>\n",
       "      <td>9.06128</td>\n",
       "      <td>8.77159</td>\n",
       "      <td>9.49875</td>\n",
       "      <td>...</td>\n",
       "      <td>9.57151</td>\n",
       "      <td>9.25375</td>\n",
       "      <td>9.69057</td>\n",
       "      <td>9.37932</td>\n",
       "      <td>8.72809</td>\n",
       "      <td>8.67545</td>\n",
       "      <td>8.94461</td>\n",
       "      <td>9.22267</td>\n",
       "      <td>9.40553</td>\n",
       "      <td>10.17190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.500000</th>\n",
       "      <td>8.42370</td>\n",
       "      <td>8.85784</td>\n",
       "      <td>8.52556</td>\n",
       "      <td>9.29687</td>\n",
       "      <td>8.64802</td>\n",
       "      <td>10.40400</td>\n",
       "      <td>9.16608</td>\n",
       "      <td>9.08925</td>\n",
       "      <td>8.86602</td>\n",
       "      <td>10.58900</td>\n",
       "      <td>...</td>\n",
       "      <td>9.64241</td>\n",
       "      <td>9.33477</td>\n",
       "      <td>9.62622</td>\n",
       "      <td>10.03940</td>\n",
       "      <td>9.01752</td>\n",
       "      <td>9.30258</td>\n",
       "      <td>9.50388</td>\n",
       "      <td>10.29790</td>\n",
       "      <td>10.06050</td>\n",
       "      <td>10.61060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.750000</th>\n",
       "      <td>8.48070</td>\n",
       "      <td>8.85287</td>\n",
       "      <td>7.62765</td>\n",
       "      <td>9.36207</td>\n",
       "      <td>7.96492</td>\n",
       "      <td>10.54640</td>\n",
       "      <td>8.89410</td>\n",
       "      <td>9.26189</td>\n",
       "      <td>9.37508</td>\n",
       "      <td>10.57220</td>\n",
       "      <td>...</td>\n",
       "      <td>9.57583</td>\n",
       "      <td>9.38342</td>\n",
       "      <td>9.94279</td>\n",
       "      <td>10.35490</td>\n",
       "      <td>9.00411</td>\n",
       "      <td>8.86505</td>\n",
       "      <td>8.96312</td>\n",
       "      <td>9.55833</td>\n",
       "      <td>9.61009</td>\n",
       "      <td>10.49570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.000000</th>\n",
       "      <td>8.54523</td>\n",
       "      <td>9.12029</td>\n",
       "      <td>8.24678</td>\n",
       "      <td>9.85482</td>\n",
       "      <td>8.30547</td>\n",
       "      <td>10.07120</td>\n",
       "      <td>9.44470</td>\n",
       "      <td>9.04600</td>\n",
       "      <td>9.45223</td>\n",
       "      <td>10.35230</td>\n",
       "      <td>...</td>\n",
       "      <td>9.52790</td>\n",
       "      <td>9.41386</td>\n",
       "      <td>9.99400</td>\n",
       "      <td>10.09370</td>\n",
       "      <td>9.08865</td>\n",
       "      <td>8.87843</td>\n",
       "      <td>9.14775</td>\n",
       "      <td>9.70607</td>\n",
       "      <td>9.89745</td>\n",
       "      <td>10.13140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.250000</th>\n",
       "      <td>8.40561</td>\n",
       "      <td>9.09837</td>\n",
       "      <td>8.23787</td>\n",
       "      <td>9.14327</td>\n",
       "      <td>8.51615</td>\n",
       "      <td>9.76572</td>\n",
       "      <td>8.22240</td>\n",
       "      <td>9.18798</td>\n",
       "      <td>9.38363</td>\n",
       "      <td>10.69020</td>\n",
       "      <td>...</td>\n",
       "      <td>9.39406</td>\n",
       "      <td>9.20462</td>\n",
       "      <td>9.90033</td>\n",
       "      <td>10.50830</td>\n",
       "      <td>9.05370</td>\n",
       "      <td>8.85682</td>\n",
       "      <td>9.16434</td>\n",
       "      <td>9.55209</td>\n",
       "      <td>9.63609</td>\n",
       "      <td>9.82932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.500000</th>\n",
       "      <td>8.48597</td>\n",
       "      <td>9.16795</td>\n",
       "      <td>8.20461</td>\n",
       "      <td>9.75591</td>\n",
       "      <td>8.75208</td>\n",
       "      <td>10.34790</td>\n",
       "      <td>9.30414</td>\n",
       "      <td>9.22794</td>\n",
       "      <td>8.81001</td>\n",
       "      <td>10.92590</td>\n",
       "      <td>...</td>\n",
       "      <td>9.48922</td>\n",
       "      <td>9.45625</td>\n",
       "      <td>9.42303</td>\n",
       "      <td>10.37160</td>\n",
       "      <td>9.01559</td>\n",
       "      <td>9.10258</td>\n",
       "      <td>9.24245</td>\n",
       "      <td>10.87630</td>\n",
       "      <td>9.89252</td>\n",
       "      <td>10.49880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.750000</th>\n",
       "      <td>8.52811</td>\n",
       "      <td>9.16234</td>\n",
       "      <td>8.11355</td>\n",
       "      <td>9.40480</td>\n",
       "      <td>8.22710</td>\n",
       "      <td>10.54510</td>\n",
       "      <td>8.85337</td>\n",
       "      <td>9.17795</td>\n",
       "      <td>9.37749</td>\n",
       "      <td>11.15870</td>\n",
       "      <td>...</td>\n",
       "      <td>9.46778</td>\n",
       "      <td>9.28115</td>\n",
       "      <td>9.69803</td>\n",
       "      <td>10.57580</td>\n",
       "      <td>9.22594</td>\n",
       "      <td>8.70917</td>\n",
       "      <td>9.02089</td>\n",
       "      <td>9.85601</td>\n",
       "      <td>9.66616</td>\n",
       "      <td>10.16670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.000000</th>\n",
       "      <td>8.52483</td>\n",
       "      <td>9.08724</td>\n",
       "      <td>8.12698</td>\n",
       "      <td>9.87030</td>\n",
       "      <td>8.03016</td>\n",
       "      <td>9.83401</td>\n",
       "      <td>9.33716</td>\n",
       "      <td>9.10779</td>\n",
       "      <td>9.69798</td>\n",
       "      <td>10.23810</td>\n",
       "      <td>...</td>\n",
       "      <td>9.34284</td>\n",
       "      <td>9.13453</td>\n",
       "      <td>9.51238</td>\n",
       "      <td>9.79550</td>\n",
       "      <td>9.16130</td>\n",
       "      <td>8.59782</td>\n",
       "      <td>8.94797</td>\n",
       "      <td>9.77227</td>\n",
       "      <td>9.83289</td>\n",
       "      <td>9.93971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.250000</th>\n",
       "      <td>8.50701</td>\n",
       "      <td>9.00917</td>\n",
       "      <td>7.80247</td>\n",
       "      <td>9.29552</td>\n",
       "      <td>7.70805</td>\n",
       "      <td>9.19287</td>\n",
       "      <td>8.28656</td>\n",
       "      <td>9.26824</td>\n",
       "      <td>9.33191</td>\n",
       "      <td>10.36660</td>\n",
       "      <td>...</td>\n",
       "      <td>9.22843</td>\n",
       "      <td>9.20662</td>\n",
       "      <td>9.77924</td>\n",
       "      <td>8.98677</td>\n",
       "      <td>8.90212</td>\n",
       "      <td>8.71178</td>\n",
       "      <td>8.77557</td>\n",
       "      <td>9.43094</td>\n",
       "      <td>9.60796</td>\n",
       "      <td>9.62292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.500000</th>\n",
       "      <td>8.50909</td>\n",
       "      <td>9.08203</td>\n",
       "      <td>7.69887</td>\n",
       "      <td>9.55686</td>\n",
       "      <td>7.96950</td>\n",
       "      <td>9.07993</td>\n",
       "      <td>8.99928</td>\n",
       "      <td>9.08762</td>\n",
       "      <td>9.21931</td>\n",
       "      <td>10.08200</td>\n",
       "      <td>...</td>\n",
       "      <td>9.18555</td>\n",
       "      <td>8.93609</td>\n",
       "      <td>9.21883</td>\n",
       "      <td>9.92834</td>\n",
       "      <td>8.84607</td>\n",
       "      <td>8.73749</td>\n",
       "      <td>8.92062</td>\n",
       "      <td>10.06280</td>\n",
       "      <td>9.71511</td>\n",
       "      <td>9.77698</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.750000</th>\n",
       "      <td>8.55240</td>\n",
       "      <td>8.95024</td>\n",
       "      <td>8.06793</td>\n",
       "      <td>9.19919</td>\n",
       "      <td>7.80042</td>\n",
       "      <td>9.21400</td>\n",
       "      <td>9.07687</td>\n",
       "      <td>9.25895</td>\n",
       "      <td>9.37948</td>\n",
       "      <td>9.62560</td>\n",
       "      <td>...</td>\n",
       "      <td>9.14043</td>\n",
       "      <td>8.90764</td>\n",
       "      <td>9.44871</td>\n",
       "      <td>10.09230</td>\n",
       "      <td>9.16145</td>\n",
       "      <td>9.01591</td>\n",
       "      <td>8.90860</td>\n",
       "      <td>9.84748</td>\n",
       "      <td>9.76219</td>\n",
       "      <td>9.90536</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5.000000</th>\n",
       "      <td>8.58864</td>\n",
       "      <td>8.76148</td>\n",
       "      <td>7.99798</td>\n",
       "      <td>9.99121</td>\n",
       "      <td>8.33495</td>\n",
       "      <td>9.43492</td>\n",
       "      <td>9.09255</td>\n",
       "      <td>9.23738</td>\n",
       "      <td>9.23214</td>\n",
       "      <td>9.68139</td>\n",
       "      <td>...</td>\n",
       "      <td>9.18049</td>\n",
       "      <td>9.10801</td>\n",
       "      <td>9.39726</td>\n",
       "      <td>10.13130</td>\n",
       "      <td>9.23608</td>\n",
       "      <td>8.95441</td>\n",
       "      <td>9.53873</td>\n",
       "      <td>10.11390</td>\n",
       "      <td>9.87050</td>\n",
       "      <td>10.13160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5.250000</th>\n",
       "      <td>8.51011</td>\n",
       "      <td>9.03610</td>\n",
       "      <td>8.08565</td>\n",
       "      <td>9.29914</td>\n",
       "      <td>8.69627</td>\n",
       "      <td>9.54179</td>\n",
       "      <td>8.68510</td>\n",
       "      <td>9.18237</td>\n",
       "      <td>9.22095</td>\n",
       "      <td>9.46743</td>\n",
       "      <td>...</td>\n",
       "      <td>9.34856</td>\n",
       "      <td>9.02331</td>\n",
       "      <td>9.44622</td>\n",
       "      <td>9.89291</td>\n",
       "      <td>9.38334</td>\n",
       "      <td>8.96664</td>\n",
       "      <td>9.12920</td>\n",
       "      <td>9.99205</td>\n",
       "      <td>9.83682</td>\n",
       "      <td>10.10790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5.500000</th>\n",
       "      <td>8.54190</td>\n",
       "      <td>8.48175</td>\n",
       "      <td>7.70718</td>\n",
       "      <td>9.46441</td>\n",
       "      <td>8.44475</td>\n",
       "      <td>8.96643</td>\n",
       "      <td>9.01639</td>\n",
       "      <td>9.19501</td>\n",
       "      <td>9.00821</td>\n",
       "      <td>9.41507</td>\n",
       "      <td>...</td>\n",
       "      <td>10.06230</td>\n",
       "      <td>8.98712</td>\n",
       "      <td>9.37050</td>\n",
       "      <td>9.68667</td>\n",
       "      <td>8.99786</td>\n",
       "      <td>8.80193</td>\n",
       "      <td>9.14011</td>\n",
       "      <td>9.51541</td>\n",
       "      <td>9.82372</td>\n",
       "      <td>9.86580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5.750000</th>\n",
       "      <td>8.50417</td>\n",
       "      <td>8.43276</td>\n",
       "      <td>7.48510</td>\n",
       "      <td>9.30604</td>\n",
       "      <td>7.79920</td>\n",
       "      <td>8.66999</td>\n",
       "      <td>8.60975</td>\n",
       "      <td>9.29159</td>\n",
       "      <td>8.95157</td>\n",
       "      <td>9.22216</td>\n",
       "      <td>...</td>\n",
       "      <td>9.53275</td>\n",
       "      <td>8.77008</td>\n",
       "      <td>9.34554</td>\n",
       "      <td>9.34177</td>\n",
       "      <td>8.76626</td>\n",
       "      <td>8.80554</td>\n",
       "      <td>9.01501</td>\n",
       "      <td>9.09318</td>\n",
       "      <td>10.00750</td>\n",
       "      <td>9.75914</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6.000000</th>\n",
       "      <td>8.48011</td>\n",
       "      <td>8.23556</td>\n",
       "      <td>7.56161</td>\n",
       "      <td>9.22276</td>\n",
       "      <td>7.73364</td>\n",
       "      <td>8.30631</td>\n",
       "      <td>8.71876</td>\n",
       "      <td>9.00536</td>\n",
       "      <td>8.02482</td>\n",
       "      <td>9.73725</td>\n",
       "      <td>...</td>\n",
       "      <td>9.33217</td>\n",
       "      <td>8.77147</td>\n",
       "      <td>9.17613</td>\n",
       "      <td>9.13943</td>\n",
       "      <td>8.43693</td>\n",
       "      <td>8.73602</td>\n",
       "      <td>8.96961</td>\n",
       "      <td>8.98105</td>\n",
       "      <td>10.12960</td>\n",
       "      <td>9.90102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6.250000</th>\n",
       "      <td>8.43291</td>\n",
       "      <td>8.53837</td>\n",
       "      <td>7.68979</td>\n",
       "      <td>9.27387</td>\n",
       "      <td>7.72699</td>\n",
       "      <td>8.30964</td>\n",
       "      <td>8.59529</td>\n",
       "      <td>9.00452</td>\n",
       "      <td>8.28829</td>\n",
       "      <td>9.64558</td>\n",
       "      <td>...</td>\n",
       "      <td>9.37371</td>\n",
       "      <td>8.90834</td>\n",
       "      <td>8.85390</td>\n",
       "      <td>8.85683</td>\n",
       "      <td>8.66265</td>\n",
       "      <td>8.79569</td>\n",
       "      <td>8.85690</td>\n",
       "      <td>9.09709</td>\n",
       "      <td>10.03150</td>\n",
       "      <td>9.79982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6.500000</th>\n",
       "      <td>8.46004</td>\n",
       "      <td>8.48118</td>\n",
       "      <td>8.01070</td>\n",
       "      <td>9.52979</td>\n",
       "      <td>7.91539</td>\n",
       "      <td>8.45290</td>\n",
       "      <td>8.86833</td>\n",
       "      <td>9.05055</td>\n",
       "      <td>8.20595</td>\n",
       "      <td>9.52155</td>\n",
       "      <td>...</td>\n",
       "      <td>9.05749</td>\n",
       "      <td>8.85348</td>\n",
       "      <td>9.42968</td>\n",
       "      <td>8.65829</td>\n",
       "      <td>8.50464</td>\n",
       "      <td>8.73153</td>\n",
       "      <td>8.84249</td>\n",
       "      <td>9.25542</td>\n",
       "      <td>10.04360</td>\n",
       "      <td>9.90194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6.750000</th>\n",
       "      <td>8.51117</td>\n",
       "      <td>8.79271</td>\n",
       "      <td>7.95982</td>\n",
       "      <td>9.43295</td>\n",
       "      <td>8.05897</td>\n",
       "      <td>8.73333</td>\n",
       "      <td>8.54165</td>\n",
       "      <td>9.20825</td>\n",
       "      <td>8.21958</td>\n",
       "      <td>9.51826</td>\n",
       "      <td>...</td>\n",
       "      <td>9.18412</td>\n",
       "      <td>8.97963</td>\n",
       "      <td>9.37189</td>\n",
       "      <td>9.06052</td>\n",
       "      <td>8.82228</td>\n",
       "      <td>8.83995</td>\n",
       "      <td>9.03265</td>\n",
       "      <td>9.09795</td>\n",
       "      <td>10.34080</td>\n",
       "      <td>9.84568</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>28 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Node        40       1424     4040     5112     5308      6151     6231   \\\n",
       "Time                                                                       \n",
       "0.000463  8.88914  9.14636  8.63955  9.18824  9.07107   9.74991  8.15863   \n",
       "0.250000  8.87130  9.07574  8.53041  8.74934  9.89064   9.37986  9.32571   \n",
       "0.500000  8.63889  8.85504  7.79561  8.52855  9.47001   9.95057  7.77888   \n",
       "0.750000  8.71468  9.03552  7.76934  9.03530  8.25365  10.33270  9.01649   \n",
       "1.000000  8.61930  8.90543  7.55615  9.15116  8.30097  10.06130  9.01233   \n",
       "1.250000  8.35042  8.61955  7.28585  8.50084  7.49276   9.65071  7.64612   \n",
       "1.500000  8.32351  8.02203  7.12841  8.54889  7.25524   8.74623  7.89922   \n",
       "1.750000  8.34270  8.17748  7.28917  9.39997  7.67430   8.49504  8.19422   \n",
       "2.000000  8.38471  8.79249  7.58468  9.17462  7.76546   8.13759  8.64629   \n",
       "2.250000  8.35790  8.76385  8.20808  9.13733  8.14755   9.73276  8.24358   \n",
       "2.500000  8.42370  8.85784  8.52556  9.29687  8.64802  10.40400  9.16608   \n",
       "2.750000  8.48070  8.85287  7.62765  9.36207  7.96492  10.54640  8.89410   \n",
       "3.000000  8.54523  9.12029  8.24678  9.85482  8.30547  10.07120  9.44470   \n",
       "3.250000  8.40561  9.09837  8.23787  9.14327  8.51615   9.76572  8.22240   \n",
       "3.500000  8.48597  9.16795  8.20461  9.75591  8.75208  10.34790  9.30414   \n",
       "3.750000  8.52811  9.16234  8.11355  9.40480  8.22710  10.54510  8.85337   \n",
       "4.000000  8.52483  9.08724  8.12698  9.87030  8.03016   9.83401  9.33716   \n",
       "4.250000  8.50701  9.00917  7.80247  9.29552  7.70805   9.19287  8.28656   \n",
       "4.500000  8.50909  9.08203  7.69887  9.55686  7.96950   9.07993  8.99928   \n",
       "4.750000  8.55240  8.95024  8.06793  9.19919  7.80042   9.21400  9.07687   \n",
       "5.000000  8.58864  8.76148  7.99798  9.99121  8.33495   9.43492  9.09255   \n",
       "5.250000  8.51011  9.03610  8.08565  9.29914  8.69627   9.54179  8.68510   \n",
       "5.500000  8.54190  8.48175  7.70718  9.46441  8.44475   8.96643  9.01639   \n",
       "5.750000  8.50417  8.43276  7.48510  9.30604  7.79920   8.66999  8.60975   \n",
       "6.000000  8.48011  8.23556  7.56161  9.22276  7.73364   8.30631  8.71876   \n",
       "6.250000  8.43291  8.53837  7.68979  9.27387  7.72699   8.30964  8.59529   \n",
       "6.500000  8.46004  8.48118  8.01070  9.52979  7.91539   8.45290  8.86833   \n",
       "6.750000  8.51117  8.79271  7.95982  9.43295  8.05897   8.73333  8.54165   \n",
       "\n",
       "Node        7294     7786      7796   ...     11959    12166    13264  \\\n",
       "Time                                  ...                               \n",
       "0.000463  9.64832  9.64691  10.70430  ...  10.05910  9.65705  9.78704   \n",
       "0.250000  9.57541  9.53682  10.23210  ...   9.86172  9.53881  9.82993   \n",
       "0.500000  9.45214  9.16340   9.52499  ...  10.33250  9.45617  9.91140   \n",
       "0.750000  9.63030  9.06807   7.92512  ...  10.46710  9.40975  9.89702   \n",
       "1.000000  9.51150  9.26795   9.14635  ...  10.45700  9.31066  9.78804   \n",
       "1.250000  9.55977  9.21367   8.83923  ...  10.32750  9.22635  9.56974   \n",
       "1.500000  9.46803  8.11143   8.30162  ...  10.07670  8.94167  8.90907   \n",
       "1.750000  9.16735  8.23364   9.43222  ...   9.73530  8.94402  8.88661   \n",
       "2.000000  8.98421  8.10123   9.92250  ...   9.65342  9.12748  9.14438   \n",
       "2.250000  9.06128  8.77159   9.49875  ...   9.57151  9.25375  9.69057   \n",
       "2.500000  9.08925  8.86602  10.58900  ...   9.64241  9.33477  9.62622   \n",
       "2.750000  9.26189  9.37508  10.57220  ...   9.57583  9.38342  9.94279   \n",
       "3.000000  9.04600  9.45223  10.35230  ...   9.52790  9.41386  9.99400   \n",
       "3.250000  9.18798  9.38363  10.69020  ...   9.39406  9.20462  9.90033   \n",
       "3.500000  9.22794  8.81001  10.92590  ...   9.48922  9.45625  9.42303   \n",
       "3.750000  9.17795  9.37749  11.15870  ...   9.46778  9.28115  9.69803   \n",
       "4.000000  9.10779  9.69798  10.23810  ...   9.34284  9.13453  9.51238   \n",
       "4.250000  9.26824  9.33191  10.36660  ...   9.22843  9.20662  9.77924   \n",
       "4.500000  9.08762  9.21931  10.08200  ...   9.18555  8.93609  9.21883   \n",
       "4.750000  9.25895  9.37948   9.62560  ...   9.14043  8.90764  9.44871   \n",
       "5.000000  9.23738  9.23214   9.68139  ...   9.18049  9.10801  9.39726   \n",
       "5.250000  9.18237  9.22095   9.46743  ...   9.34856  9.02331  9.44622   \n",
       "5.500000  9.19501  9.00821   9.41507  ...  10.06230  8.98712  9.37050   \n",
       "5.750000  9.29159  8.95157   9.22216  ...   9.53275  8.77008  9.34554   \n",
       "6.000000  9.00536  8.02482   9.73725  ...   9.33217  8.77147  9.17613   \n",
       "6.250000  9.00452  8.28829   9.64558  ...   9.37371  8.90834  8.85390   \n",
       "6.500000  9.05055  8.20595   9.52155  ...   9.05749  8.85348  9.42968   \n",
       "6.750000  9.20825  8.21958   9.51826  ...   9.18412  8.97963  9.37189   \n",
       "\n",
       "Node         13789    14271    14885    15199     15490     15903     15967  \n",
       "Time                                                                         \n",
       "0.000463  10.42120  9.41646  9.84068  9.55779  10.71930  10.25730  10.78920  \n",
       "0.250000  10.61730  9.54964  9.63023  9.29671  10.41730  10.99670  10.86980  \n",
       "0.500000   9.51471  9.36187  9.50742  9.30183  10.18120   9.91834  10.48180  \n",
       "0.750000   9.11084  9.36636  9.18367  9.49366  10.58870   9.39015  10.33640  \n",
       "1.000000   8.38609  9.46486  9.28950  9.54329  10.38730   9.67648  10.41390  \n",
       "1.250000   8.50355  9.19299  8.90442  9.12326   9.95631   9.24615   9.15752  \n",
       "1.500000   8.21879  8.59956  8.81776  8.98322   9.42060   9.19993   9.55977  \n",
       "1.750000   8.95248  8.48288  8.64000  8.93304   9.56404   9.46787   9.42363  \n",
       "2.000000   8.97913  8.38037  8.86621  9.17109   9.04909   9.87346   9.94183  \n",
       "2.250000   9.37932  8.72809  8.67545  8.94461   9.22267   9.40553  10.17190  \n",
       "2.500000  10.03940  9.01752  9.30258  9.50388  10.29790  10.06050  10.61060  \n",
       "2.750000  10.35490  9.00411  8.86505  8.96312   9.55833   9.61009  10.49570  \n",
       "3.000000  10.09370  9.08865  8.87843  9.14775   9.70607   9.89745  10.13140  \n",
       "3.250000  10.50830  9.05370  8.85682  9.16434   9.55209   9.63609   9.82932  \n",
       "3.500000  10.37160  9.01559  9.10258  9.24245  10.87630   9.89252  10.49880  \n",
       "3.750000  10.57580  9.22594  8.70917  9.02089   9.85601   9.66616  10.16670  \n",
       "4.000000   9.79550  9.16130  8.59782  8.94797   9.77227   9.83289   9.93971  \n",
       "4.250000   8.98677  8.90212  8.71178  8.77557   9.43094   9.60796   9.62292  \n",
       "4.500000   9.92834  8.84607  8.73749  8.92062  10.06280   9.71511   9.77698  \n",
       "4.750000  10.09230  9.16145  9.01591  8.90860   9.84748   9.76219   9.90536  \n",
       "5.000000  10.13130  9.23608  8.95441  9.53873  10.11390   9.87050  10.13160  \n",
       "5.250000   9.89291  9.38334  8.96664  9.12920   9.99205   9.83682  10.10790  \n",
       "5.500000   9.68667  8.99786  8.80193  9.14011   9.51541   9.82372   9.86580  \n",
       "5.750000   9.34177  8.76626  8.80554  9.01501   9.09318  10.00750   9.75914  \n",
       "6.000000   9.13943  8.43693  8.73602  8.96961   8.98105  10.12960   9.90102  \n",
       "6.250000   8.85683  8.66265  8.79569  8.85690   9.09709  10.03150   9.79982  \n",
       "6.500000   8.65829  8.50464  8.73153  8.84249   9.25542  10.04360   9.90194  \n",
       "6.750000   9.06052  8.82228  8.83995  9.03265   9.09795  10.34080   9.84568  \n",
       "\n",
       "[28 rows x 26 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[:, :, 1][\"DO\"].unstack(level=1).dropna(axis=1, how='all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "19c986b3-feac-47cc-91e7-84ea75326378",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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