diff --git a/notebooks/run_metrics.ipynb b/notebooks/run_metrics.ipynb
index 4899ccc..3dbefdc 100644
--- a/notebooks/run_metrics.ipynb
+++ b/notebooks/run_metrics.ipynb
@@ -1,130 +1,737 @@
 {
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "703913af",
-   "metadata": {},
-   "source": [
-    "# Creating the IOOS By The Numbers\n",
-    "\n",
-    "[Website](https://ioos.noaa.gov/about/ioos-by-the-numbers/)\n",
-    "\n",
-    "[Spreadsheet](https://docs.google.com/spreadsheets/d/1AUfXmc3OwxpVdeMNjZyTGWjyR4ku3kRD5eexNrMORnI/edit#gid=516871794)"
-   ]
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/ioos/ioos_metrics/blob/main/notebooks/run_metrics.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "703913af",
+      "metadata": {
+        "id": "703913af"
+      },
+      "source": [
+        "# Creating the IOOS By The Numbers\n",
+        "\n",
+        "[Website](https://ioos.noaa.gov/about/ioos-by-the-numbers/)\n",
+        "\n",
+        "[Spreadsheet](https://docs.google.com/spreadsheets/d/1AUfXmc3OwxpVdeMNjZyTGWjyR4ku3kRD5eexNrMORnI/edit#gid=516871794)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!pip install ioos_metrics"
+      ],
+      "metadata": {
+        "id": "c6zx3rTTK1bq",
+        "outputId": "4a626729-fb39-4cce-fefd-2bc859792c76",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        }
+      },
+      "id": "c6zx3rTTK1bq",
+      "execution_count": 1,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Collecting ioos_metrics\n",
+            "  Downloading ioos_metrics-0.5.0-py3-none-any.whl.metadata (5.1 kB)\n",
+            "Collecting bs4 (from ioos_metrics)\n",
+            "  Downloading bs4-0.0.2-py2.py3-none-any.whl.metadata (411 bytes)\n",
+            "Collecting ckanapi (from ioos_metrics)\n",
+            "  Downloading ckanapi-4.8-py3-none-any.whl.metadata (618 bytes)\n",
+            "Collecting fake-useragent (from ioos_metrics)\n",
+            "  Downloading fake_useragent-2.0.3-py3-none-any.whl.metadata (17 kB)\n",
+            "Requirement already satisfied: geopandas>=0.13.2 in /usr/local/lib/python3.11/dist-packages (from ioos_metrics) (1.0.1)\n",
+            "Collecting gliderpy (from ioos_metrics)\n",
+            "  Downloading gliderpy-0.2.2-py3-none-any.whl.metadata (3.1 kB)\n",
+            "Requirement already satisfied: html5lib in /usr/local/lib/python3.11/dist-packages (from ioos_metrics) (1.1)\n",
+            "Requirement already satisfied: joblib in /usr/local/lib/python3.11/dist-packages (from ioos_metrics) (1.4.2)\n",
+            "Requirement already satisfied: lxml in /usr/local/lib/python3.11/dist-packages (from ioos_metrics) (5.3.0)\n",
+            "Requirement already satisfied: pandas in /usr/local/lib/python3.11/dist-packages (from ioos_metrics) (2.2.2)\n",
+            "Collecting pdfminer.six (from ioos_metrics)\n",
+            "  Downloading pdfminer.six-20240706-py3-none-any.whl.metadata (4.1 kB)\n",
+            "Requirement already satisfied: pyarrow in /usr/local/lib/python3.11/dist-packages (from ioos_metrics) (17.0.0)\n",
+            "Collecting pyobis (from ioos_metrics)\n",
+            "  Downloading pyobis-1.4.1-py3-none-any.whl.metadata (5.5 kB)\n",
+            "Requirement already satisfied: requests in /usr/local/lib/python3.11/dist-packages (from ioos_metrics) (2.32.3)\n",
+            "Requirement already satisfied: numpy>=1.22 in /usr/local/lib/python3.11/dist-packages (from geopandas>=0.13.2->ioos_metrics) (1.26.4)\n",
+            "Requirement already satisfied: pyogrio>=0.7.2 in /usr/local/lib/python3.11/dist-packages (from geopandas>=0.13.2->ioos_metrics) (0.10.0)\n",
+            "Requirement already satisfied: packaging in /usr/local/lib/python3.11/dist-packages (from geopandas>=0.13.2->ioos_metrics) (24.2)\n",
+            "Requirement already satisfied: pyproj>=3.3.0 in /usr/local/lib/python3.11/dist-packages (from geopandas>=0.13.2->ioos_metrics) (3.7.0)\n",
+            "Requirement already satisfied: shapely>=2.0.0 in /usr/local/lib/python3.11/dist-packages (from geopandas>=0.13.2->ioos_metrics) (2.0.6)\n",
+            "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.11/dist-packages (from pandas->ioos_metrics) (2.8.2)\n",
+            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.11/dist-packages (from pandas->ioos_metrics) (2024.2)\n",
+            "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.11/dist-packages (from pandas->ioos_metrics) (2024.2)\n",
+            "Requirement already satisfied: beautifulsoup4 in /usr/local/lib/python3.11/dist-packages (from bs4->ioos_metrics) (4.12.3)\n",
+            "Requirement already satisfied: setuptools in /usr/local/lib/python3.11/dist-packages (from ckanapi->ioos_metrics) (75.1.0)\n",
+            "Collecting docopt (from ckanapi->ioos_metrics)\n",
+            "  Downloading docopt-0.6.2.tar.gz (25 kB)\n",
+            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "Requirement already satisfied: six<2.0,>=1.9 in /usr/local/lib/python3.11/dist-packages (from ckanapi->ioos_metrics) (1.17.0)\n",
+            "Collecting simplejson (from ckanapi->ioos_metrics)\n",
+            "  Downloading simplejson-3.19.3-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (3.2 kB)\n",
+            "Requirement already satisfied: python-slugify>=1.0 in /usr/local/lib/python3.11/dist-packages (from ckanapi->ioos_metrics) (8.0.4)\n",
+            "Collecting erddapy (from gliderpy->ioos_metrics)\n",
+            "  Downloading erddapy-2.2.3-py3-none-any.whl.metadata (6.6 kB)\n",
+            "Requirement already satisfied: httpx in /usr/local/lib/python3.11/dist-packages (from gliderpy->ioos_metrics) (0.28.1)\n",
+            "Requirement already satisfied: xarray in /usr/local/lib/python3.11/dist-packages (from gliderpy->ioos_metrics) (2025.1.1)\n",
+            "Requirement already satisfied: webencodings in /usr/local/lib/python3.11/dist-packages (from html5lib->ioos_metrics) (0.5.1)\n",
+            "Requirement already satisfied: charset-normalizer>=2.0.0 in /usr/local/lib/python3.11/dist-packages (from pdfminer.six->ioos_metrics) (3.4.1)\n",
+            "Requirement already satisfied: cryptography>=36.0.0 in /usr/local/lib/python3.11/dist-packages (from pdfminer.six->ioos_metrics) (43.0.3)\n",
+            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.11/dist-packages (from requests->ioos_metrics) (3.10)\n",
+            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.11/dist-packages (from requests->ioos_metrics) (2.3.0)\n",
+            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.11/dist-packages (from requests->ioos_metrics) (2024.12.14)\n",
+            "Requirement already satisfied: cffi>=1.12 in /usr/local/lib/python3.11/dist-packages (from cryptography>=36.0.0->pdfminer.six->ioos_metrics) (1.17.1)\n",
+            "Requirement already satisfied: text-unidecode>=1.3 in /usr/local/lib/python3.11/dist-packages (from python-slugify>=1.0->ckanapi->ioos_metrics) (1.3)\n",
+            "Requirement already satisfied: soupsieve>1.2 in /usr/local/lib/python3.11/dist-packages (from beautifulsoup4->bs4->ioos_metrics) (2.6)\n",
+            "Requirement already satisfied: anyio in /usr/local/lib/python3.11/dist-packages (from httpx->gliderpy->ioos_metrics) (3.7.1)\n",
+            "Requirement already satisfied: httpcore==1.* in /usr/local/lib/python3.11/dist-packages (from httpx->gliderpy->ioos_metrics) (1.0.7)\n",
+            "Requirement already satisfied: h11<0.15,>=0.13 in /usr/local/lib/python3.11/dist-packages (from httpcore==1.*->httpx->gliderpy->ioos_metrics) (0.14.0)\n",
+            "Requirement already satisfied: pycparser in /usr/local/lib/python3.11/dist-packages (from cffi>=1.12->cryptography>=36.0.0->pdfminer.six->ioos_metrics) (2.22)\n",
+            "Requirement already satisfied: sniffio>=1.1 in /usr/local/lib/python3.11/dist-packages (from anyio->httpx->gliderpy->ioos_metrics) (1.3.1)\n",
+            "Downloading ioos_metrics-0.5.0-py3-none-any.whl (15 kB)\n",
+            "Downloading bs4-0.0.2-py2.py3-none-any.whl (1.2 kB)\n",
+            "Downloading ckanapi-4.8-py3-none-any.whl (46 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m46.3/46.3 kB\u001b[0m \u001b[31m1.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading fake_useragent-2.0.3-py3-none-any.whl (201 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m201.1/201.1 kB\u001b[0m \u001b[31m10.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading gliderpy-0.2.2-py3-none-any.whl (7.8 kB)\n",
+            "Downloading pdfminer.six-20240706-py3-none-any.whl (5.6 MB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m5.6/5.6 MB\u001b[0m \u001b[31m31.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading pyobis-1.4.1-py3-none-any.whl (23 kB)\n",
+            "Downloading erddapy-2.2.3-py3-none-any.whl (24 kB)\n",
+            "Downloading simplejson-3.19.3-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (144 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m144.7/144.7 kB\u001b[0m \u001b[31m7.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hBuilding wheels for collected packages: docopt\n",
+            "  Building wheel for docopt (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "  Created wheel for docopt: filename=docopt-0.6.2-py2.py3-none-any.whl size=13706 sha256=147af1450e91228e95b1773c6b9d40feebe400d4ce67b4a23d1ed381a95c52bb\n",
+            "  Stored in directory: /root/.cache/pip/wheels/1a/b0/8c/4b75c4116c31f83c8f9f047231251e13cc74481cca4a78a9ce\n",
+            "Successfully built docopt\n",
+            "Installing collected packages: docopt, simplejson, fake-useragent, ckanapi, bs4, pyobis, pdfminer.six, erddapy, gliderpy, ioos_metrics\n",
+            "Successfully installed bs4-0.0.2 ckanapi-4.8 docopt-0.6.2 erddapy-2.2.3 fake-useragent-2.0.3 gliderpy-0.2.2 ioos_metrics-0.5.0 pdfminer.six-20240706 pyobis-1.4.1 simplejson-3.19.3\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "id": "2e1ac2bd",
+      "metadata": {
+        "id": "2e1ac2bd",
+        "outputId": "03ad5b08-951e-4b45-a0e2-f6f9fc2911b1",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 259
+        }
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "CPU times: user 1.88 s, sys: 412 ms, total: 2.29 s\n",
+            "Wall time: 19.1 s\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "     date_UTC Federal Partners Regional Associations HF Radar Stations  \\\n",
+              "2  2022-07-08               17                    11               165   \n",
+              "3  2022-10-05               17                    11               165   \n",
+              "4  2023-01-05               17                    11               165   \n",
+              "5  2024-01-26               17                    11               165   \n",
+              "6  2025-01-23               17                    11               165   \n",
+              "\n",
+              "  NGDAC Glider Days National Platforms Regional Platforms ATN Deployments  \\\n",
+              "2             55448                764                517            4444   \n",
+              "3             59088                390                635            4444   \n",
+              "4             62042                768                635            4444   \n",
+              "5             61990                721                886            5190   \n",
+              "6             74178                731               1081            6136   \n",
+              "\n",
+              "  MBON Projects OTT Projects HAB Pilot Projects QARTOD Manuals  \\\n",
+              "2             6            8                  9             13   \n",
+              "3             6            8                  9             13   \n",
+              "4             6            8                  9             13   \n",
+              "5             5            8                 11             13   \n",
+              "6            10           21                 11             13   \n",
+              "\n",
+              "  IOOS Core Variables Metadata Records IOOS COMT Projects  \n",
+              "2                  34             6217    1             5  \n",
+              "3                  34            24499    1             5  \n",
+              "4                  34            11840    1             5  \n",
+              "5                  34            42599    1             5  \n",
+              "6                  34            37475    1             5  "
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-a04b651d-1a0f-4785-8432-dc3066433294\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>date_UTC</th>\n",
+              "      <th>Federal Partners</th>\n",
+              "      <th>Regional Associations</th>\n",
+              "      <th>HF Radar Stations</th>\n",
+              "      <th>NGDAC Glider Days</th>\n",
+              "      <th>National Platforms</th>\n",
+              "      <th>Regional Platforms</th>\n",
+              "      <th>ATN Deployments</th>\n",
+              "      <th>MBON Projects</th>\n",
+              "      <th>OTT Projects</th>\n",
+              "      <th>HAB Pilot Projects</th>\n",
+              "      <th>QARTOD Manuals</th>\n",
+              "      <th>IOOS Core Variables</th>\n",
+              "      <th>Metadata Records</th>\n",
+              "      <th>IOOS</th>\n",
+              "      <th>COMT Projects</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>2022-07-08</td>\n",
+              "      <td>17</td>\n",
+              "      <td>11</td>\n",
+              "      <td>165</td>\n",
+              "      <td>55448</td>\n",
+              "      <td>764</td>\n",
+              "      <td>517</td>\n",
+              "      <td>4444</td>\n",
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+              "      <td>8</td>\n",
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+              "      <td>34</td>\n",
+              "      <td>6217</td>\n",
+              "      <td>1</td>\n",
+              "      <td>5</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>2022-10-05</td>\n",
+              "      <td>17</td>\n",
+              "      <td>11</td>\n",
+              "      <td>165</td>\n",
+              "      <td>59088</td>\n",
+              "      <td>390</td>\n",
+              "      <td>635</td>\n",
+              "      <td>4444</td>\n",
+              "      <td>6</td>\n",
+              "      <td>8</td>\n",
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+              "      <td>13</td>\n",
+              "      <td>34</td>\n",
+              "      <td>24499</td>\n",
+              "      <td>1</td>\n",
+              "      <td>5</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>2023-01-05</td>\n",
+              "      <td>17</td>\n",
+              "      <td>11</td>\n",
+              "      <td>165</td>\n",
+              "      <td>62042</td>\n",
+              "      <td>768</td>\n",
+              "      <td>635</td>\n",
+              "      <td>4444</td>\n",
+              "      <td>6</td>\n",
+              "      <td>8</td>\n",
+              "      <td>9</td>\n",
+              "      <td>13</td>\n",
+              "      <td>34</td>\n",
+              "      <td>11840</td>\n",
+              "      <td>1</td>\n",
+              "      <td>5</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>5</th>\n",
+              "      <td>2024-01-26</td>\n",
+              "      <td>17</td>\n",
+              "      <td>11</td>\n",
+              "      <td>165</td>\n",
+              "      <td>61990</td>\n",
+              "      <td>721</td>\n",
+              "      <td>886</td>\n",
+              "      <td>5190</td>\n",
+              "      <td>5</td>\n",
+              "      <td>8</td>\n",
+              "      <td>11</td>\n",
+              "      <td>13</td>\n",
+              "      <td>34</td>\n",
+              "      <td>42599</td>\n",
+              "      <td>1</td>\n",
+              "      <td>5</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>6</th>\n",
+              "      <td>2025-01-23</td>\n",
+              "      <td>17</td>\n",
+              "      <td>11</td>\n",
+              "      <td>165</td>\n",
+              "      <td>74178</td>\n",
+              "      <td>731</td>\n",
+              "      <td>1081</td>\n",
+              "      <td>6136</td>\n",
+              "      <td>10</td>\n",
+              "      <td>21</td>\n",
+              "      <td>11</td>\n",
+              "      <td>13</td>\n",
+              "      <td>34</td>\n",
+              "      <td>37475</td>\n",
+              "      <td>1</td>\n",
+              "      <td>5</td>\n",
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+              "  </tbody>\n",
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+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
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+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a04b651d-1a0f-4785-8432-dc3066433294')\"\n",
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+              "    </button>\n",
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+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
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+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-a04b651d-1a0f-4785-8432-dc3066433294 button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-a04b651d-1a0f-4785-8432-dc3066433294');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "\n",
+              "<div id=\"df-ffe5f2ae-ac14-436a-aae6-fd6df518211c\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-ffe5f2ae-ac14-436a-aae6-fd6df518211c')\"\n",
+              "            title=\"Suggest charts\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "     width=\"24px\">\n",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "  </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-ffe5f2ae-ac14-436a-aae6-fd6df518211c button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "dataframe",
+              "repr_error": "0"
+            }
+          },
+          "metadata": {},
+          "execution_count": 2
+        }
+      ],
+      "source": [
+        "%%time\n",
+        "from ioos_metrics.ioos_metrics import update_metrics\n",
+        "\n",
+        "ioos_btn_df = update_metrics()\n",
+        "ioos_btn_df.tail()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "for field in ioos_btn_df:\n",
+        "  print('{}: {}'.format(field,ioos_btn_df[field].iloc[-1]))"
+      ],
+      "metadata": {
+        "id": "OCTpQcT_K3ym",
+        "outputId": "8d87c859-8ce7-4ce0-8173-1b385c71dd31",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        }
+      },
+      "id": "OCTpQcT_K3ym",
+      "execution_count": 4,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "date_UTC: 2025-01-23\n",
+            "Federal Partners: 17\n",
+            "Regional Associations: 11\n",
+            "HF Radar Stations: 165\n",
+            "NGDAC Glider Days: 74178\n",
+            "National Platforms: 731\n",
+            "Regional Platforms: 1081\n",
+            "ATN Deployments: 6136\n",
+            "MBON Projects: 10\n",
+            "OTT Projects: 21\n",
+            "HAB Pilot Projects: 11\n",
+            "QARTOD Manuals: 13\n",
+            "IOOS Core Variables: 34\n",
+            "Metadata Records: 37475\n",
+            "IOOS: 1\n",
+            "COMT Projects: 5\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "96f4afd3",
+      "metadata": {
+        "id": "96f4afd3"
+      },
+      "source": [
+        "## Analysis\n",
+        "\n",
+        "Now we have the opportunity to do some analysis on the metrics we've captured.\n",
+        "\n",
+        "Below is an attempt to draw some comparisons between the metrics in the previous iteration and subsequent runs."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 5,
+      "id": "b9248cf3",
+      "metadata": {
+        "id": "b9248cf3",
+        "outputId": "da06ee18-1702-40bf-f94f-0db4e8a2817c",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 487
+        }
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "import matplotlib.pyplot as plt\n",
+        "import numpy as np\n",
+        "import pandas as pd\n",
+        "\n",
+        "pd.set_option(\"future.no_silent_downcasting\", True)\n",
+        "\n",
+        "ioos_btn_df[\"date_UTC\"] = pd.to_datetime(ioos_btn_df[\"date_UTC\"])\n",
+        "ioos_btn_df = ioos_btn_df.fillna(np.nan)\n",
+        "\n",
+        "labels = ioos_btn_df.drop(columns=[\"date_UTC\"]).columns.tolist()\n",
+        "\n",
+        "x = np.arange(len(labels))\n",
+        "width = 0.35\n",
+        "\n",
+        "fig, ax = plt.subplots()\n",
+        "\n",
+        "for _, row in ioos_btn_df.iterrows():\n",
+        "    means = row.drop(index=[\"date_UTC\"]).to_numpy()\n",
+        "    rects = ax.bar(\n",
+        "        x - width / 2,\n",
+        "        means,\n",
+        "        width,\n",
+        "        label=row[\"date_UTC\"].strftime(\"%Y-%m-%d\"),\n",
+        "    )\n",
+        "    width = width * -1\n",
+        "\n",
+        "# Add some text for labels, title and custom x-axis tick labels, etc.\n",
+        "ax.set_ylabel(\"Count\")\n",
+        "ax.set_title(\"Metric by year and type\")\n",
+        "ax.set_xticks(x, labels)\n",
+        "ax.legend()\n",
+        "\n",
+        "ax.xaxis.set_ticklabels(labels, rotation=90)\n",
+        "fig.tight_layout()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 6,
+      "id": "2a27e08d",
+      "metadata": {
+        "id": "2a27e08d",
+        "outputId": "b43d1116-a8df-46e6-8b27-7a220ba7cec1",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 853
+        }
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<matplotlib.collections.LineCollection at 0x7a3a9518b190>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 6
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 1200x800 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "inc_df = ioos_btn_df.drop(columns=[\"date_UTC\"])\n",
+        "\n",
+        "increase = inc_df.iloc[-1] - inc_df.iloc[-2]\n",
+        "pcnt_increase = (increase / inc_df.iloc[-2]) * 100\n",
+        "\n",
+        "fig, ax = plt.subplots(figsize=(12, 8))\n",
+        "width = 0.35\n",
+        "pcnt_increase.plot(kind=\"bar\", ax=ax, ylabel=\"% change\")\n",
+        "\n",
+        "plt.grid(visible=True, linestyle=\":\")\n",
+        "ax.set_ylim(-100, 100)\n",
+        "ax.set_title(\n",
+        "    f\"% change of IOOS BTN metrics between {ioos_btn_df['date_UTC'].iloc[-2]} and {ioos_btn_df['date_UTC'].iloc[-1]}.\",\n",
+        ")\n",
+        "plt.hlines(0, xmin=0, xmax=len(pcnt_increase), linestyles=\"solid\")"
+      ]
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3 (ipykernel)",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.12.1"
+    },
+    "colab": {
+      "provenance": [],
+      "include_colab_link": true
+    }
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "2e1ac2bd",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "%%time\n",
-    "from ioos_metrics.ioos_metrics import update_metrics\n",
-    "\n",
-    "ioos_btn_df = update_metrics()\n",
-    "ioos_btn_df.tail()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "96f4afd3",
-   "metadata": {},
-   "source": [
-    "## Analysis\n",
-    "\n",
-    "Now we have the opportunity to do some analysis on the metrics we've captured.\n",
-    "\n",
-    "Below is an attempt to draw some comparisons between the metrics in the previous iteration and subsequent runs."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b9248cf3",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import matplotlib.pyplot as plt\n",
-    "import numpy as np\n",
-    "import pandas as pd\n",
-    "\n",
-    "pd.set_option(\"future.no_silent_downcasting\", True)\n",
-    "\n",
-    "ioos_btn_df[\"date_UTC\"] = pd.to_datetime(ioos_btn_df[\"date_UTC\"])\n",
-    "ioos_btn_df = ioos_btn_df.fillna(np.nan)\n",
-    "\n",
-    "labels = ioos_btn_df.drop(columns=[\"date_UTC\"]).columns.tolist()\n",
-    "\n",
-    "x = np.arange(len(labels))\n",
-    "width = 0.35\n",
-    "\n",
-    "fig, ax = plt.subplots()\n",
-    "\n",
-    "for _, row in ioos_btn_df.iterrows():\n",
-    "    means = row.drop(index=[\"date_UTC\"]).to_numpy()\n",
-    "    rects = ax.bar(\n",
-    "        x - width / 2,\n",
-    "        means,\n",
-    "        width,\n",
-    "        label=row[\"date_UTC\"].strftime(\"%Y-%m-%d\"),\n",
-    "    )\n",
-    "    width = width * -1\n",
-    "\n",
-    "# Add some text for labels, title and custom x-axis tick labels, etc.\n",
-    "ax.set_ylabel(\"Count\")\n",
-    "ax.set_title(\"Metric by year and type\")\n",
-    "ax.set_xticks(x, labels)\n",
-    "ax.legend()\n",
-    "\n",
-    "ax.xaxis.set_ticklabels(labels, rotation=90)\n",
-    "fig.tight_layout()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "2a27e08d",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "inc_df = ioos_btn_df.drop(columns=[\"date_UTC\"])\n",
-    "\n",
-    "increase = inc_df.iloc[-1] - inc_df.iloc[-2]\n",
-    "pcnt_increase = (increase / inc_df.iloc[-2]) * 100\n",
-    "\n",
-    "fig, ax = plt.subplots(figsize=(12, 8))\n",
-    "width = 0.35\n",
-    "pcnt_increase.plot(kind=\"bar\", ax=ax, ylabel=\"% change\")\n",
-    "\n",
-    "plt.grid(visible=True, linestyle=\":\")\n",
-    "ax.set_ylim(-100, 100)\n",
-    "ax.set_title(\n",
-    "    f\"% change of IOOS BTN metrics between {ioos_btn_df['date_UTC'].iloc[-2]} and {ioos_btn_df['date_UTC'].iloc[-1]}.\",\n",
-    ")\n",
-    "plt.hlines(0, xmin=0, xmax=len(pcnt_increase), linestyles=\"solid\")"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.12.1"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
+  "nbformat": 4,
+  "nbformat_minor": 5
+}
\ No newline at end of file