Built site for gh-pages

.nojekyll

@@ -1 +1 @@
-c4d7f91c
+84e28e2c

search.json

@@ -37,7 +37,7 @@
     "href": "index.html#latest-open-source-statistics",
     "title": "Open-source Healthcare Statistics",
     "section": "Latest open-source statistics",
-    "text": "Latest open-source statistics\n\n\nShow code\nimport pandas as pd\nimport plotly.graph_objects as go\nimport datetime\nfrom dateutil.relativedelta import relativedelta\nfrom IPython.display import display, Markdown\nfrom tabulate import tabulate\n\n# Load data\ndf = pd.read_csv(\"../data/org_repos_agg.csv\")\n\n# Convert the \"Date\" column to a datetime dtype\ndf['Date'] = pd.to_datetime(df['Date'])\n\n# Filter the latest date for each organization\nlatest_dates = df.groupby('Organisation')['Date'].idxmax()\nlatest_df = df.loc[latest_dates]\n\n# Create a new column with hyperlinks for the \"Organisation\" column\nlatest_df['Organisation'] = latest_df.apply(lambda x: f\"[{x['Organisation']}]({x['URL']})\", axis=1)\n\n# Drop the \"Date\" column and sort by \"Open Repositories\"\nlatest_df = latest_df.drop(['Date', 'URL'], axis=1).sort_values('Open Repositories', ascending=False)\n\n# Calculate date data was rendered\ntoday = datetime.date.today()\nformatted_date = today.strftime(\"%d %B %Y\")\ndisplay(Markdown('Data updated as of: `%s`.' % formatted_date))\n\nMarkdown(tabulate(latest_df, headers='keys', tablefmt='pipe', showindex=False))\n\n\n\n\nTable 1: open-source statistics\n\n\n\nData updated as of: 15 December 2024.\n\n\n\n\n\n\n\n\n\n\n\nOrganisation\nOpen Repositories\nTop Language\nTop License\n\n\n\n\nNHSDigital\n347\nPython\nMIT License\n\n\nopensafely\n277\nPython\nMIT License\n\n\nnhsconnect\n196\nHTML\nApache License 2.0\n\n\nnhsuk\n191\nHTML\nMIT License\n\n\nebmdatalab\n145\nPython\nMIT License\n\n\nnhsbsa\n144\nHTML\nMIT License\n\n\nnhsengland\n111\nPython\nMIT License\n\n\nnhsx\n87\nPython\nMIT License\n\n\nukhsa-collaboration\n80\nPython\nMIT License\n\n\nHFAnalyticsLab\n76\nR\nMIT License\n\n\nBHFDSC\n68\nPython\nApache License 2.0\n\n\nnice-digital\n66\nJavaScript\nMIT License\n\n\nnhs-r-community\n60\nR\nCreative Commons Zero v1.0 Universal\n\n\nHealth-Education-England\n58\nJava\nMIT License\n\n\nopensafely-core\n54\nPython\nOther\n\n\nThe-Strategy-Unit\n53\nR\nMIT License\n\n\nnhs-bnssg-analytics\n38\nR\nGNU General Public License v3.0\n\n\nUKHSA-Internal\n34\nPython\nMIT License\n\n\nCDU-data-science-team\n31\nR\nOther\n\n\nNHSLeadership\n19\nHTML\nOther\n\n\nnhs-pycom\n14\nPython\nMIT License\n\n\n111Online\n12\nC#\nApache License 2.0\n\n\nNottingham-and-Nottinghamshire-ICS\n7\nR\nMIT License\n\n\nCQCDigital\n5\nC#\nMIT License\n\n\nMHRA\n5\nJavaScript\nMIT License\n\n\nNHS-Blood-and-Transplant\n1\nC#\nGNU General Public License v3.0",
+    "text": "Latest open-source statistics\n\n\nShow code\nimport pandas as pd\nimport plotly.graph_objects as go\nimport datetime\nfrom dateutil.relativedelta import relativedelta\nfrom IPython.display import display, Markdown\nfrom tabulate import tabulate\n\n# Load data\ndf = pd.read_csv(\"../data/org_repos_agg.csv\")\n\n# Convert the \"Date\" column to a datetime dtype\ndf['Date'] = pd.to_datetime(df['Date'])\n\n# Filter the latest date for each organization\nlatest_dates = df.groupby('Organisation')['Date'].idxmax()\nlatest_df = df.loc[latest_dates]\n\n# Create a new column with hyperlinks for the \"Organisation\" column\nlatest_df['Organisation'] = latest_df.apply(lambda x: f\"[{x['Organisation']}]({x['URL']})\", axis=1)\n\n# Drop the \"Date\" column and sort by \"Open Repositories\"\nlatest_df = latest_df.drop(['Date', 'URL'], axis=1).sort_values('Open Repositories', ascending=False)\n\n# Calculate date data was rendered\ntoday = datetime.date.today()\nformatted_date = today.strftime(\"%d %B %Y\")\ndisplay(Markdown('Data updated as of: `%s`.' % formatted_date))\n\nMarkdown(tabulate(latest_df, headers='keys', tablefmt='pipe', showindex=False))\n\n\n\n\nTable 1: open-source statistics\n\n\n\nData updated as of: 22 December 2024.\n\n\n\n\n\n\n\n\n\n\n\nOrganisation\nOpen Repositories\nTop Language\nTop License\n\n\n\n\nNHSDigital\n347\nPython\nMIT License\n\n\nopensafely\n277\nPython\nMIT License\n\n\nnhsconnect\n196\nHTML\nApache License 2.0\n\n\nnhsuk\n191\nHTML\nMIT License\n\n\nebmdatalab\n145\nPython\nMIT License\n\n\nnhsbsa\n144\nHTML\nMIT License\n\n\nnhsengland\n111\nPython\nMIT License\n\n\nnhsx\n87\nPython\nMIT License\n\n\nukhsa-collaboration\n80\nPython\nMIT License\n\n\nHFAnalyticsLab\n76\nR\nMIT License\n\n\nBHFDSC\n68\nPython\nApache License 2.0\n\n\nnice-digital\n66\nJavaScript\nMIT License\n\n\nnhs-r-community\n60\nR\nCreative Commons Zero v1.0 Universal\n\n\nHealth-Education-England\n58\nJava\nMIT License\n\n\nopensafely-core\n54\nPython\nOther\n\n\nThe-Strategy-Unit\n53\nR\nMIT License\n\n\nnhs-bnssg-analytics\n38\nR\nGNU General Public License v3.0\n\n\nUKHSA-Internal\n34\nPython\nMIT License\n\n\nCDU-data-science-team\n31\nR\nOther\n\n\nNHSLeadership\n19\nHTML\nOther\n\n\nnhs-pycom\n14\nPython\nMIT License\n\n\n111Online\n12\nC#\nApache License 2.0\n\n\nNottingham-and-Nottinghamshire-ICS\n7\nR\nMIT License\n\n\nCQCDigital\n5\nC#\nMIT License\n\n\nMHRA\n5\nJavaScript\nMIT License\n\n\nNHS-Blood-and-Transplant\n1\nC#\nGNU General Public License v3.0",
     "crumbs": [
       "opensource-health-stats v0.2.0",
       "Homepage"

sitemap.xml

@@ -2,14 +2,14 @@
 <urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9">
   <url>
     <loc>https://nhs-pycom.github.io/opensource-health-statistics/index.html</loc>
-    <lastmod>2024-12-15T00:56:34.839Z</lastmod>
+    <lastmod>2024-12-22T00:52:14.828Z</lastmod>
   </url>
   <url>
     <loc>https://nhs-pycom.github.io/opensource-health-statistics/about.html</loc>
-    <lastmod>2024-12-15T00:56:34.839Z</lastmod>
+    <lastmod>2024-12-22T00:52:14.828Z</lastmod>
   </url>
   <url>
     <loc>https://nhs-pycom.github.io/opensource-health-statistics/pages/github_api_call.html</loc>
-    <lastmod>2024-12-15T00:56:34.839Z</lastmod>
+    <lastmod>2024-12-22T00:52:14.828Z</lastmod>
   </url>
 </urlset>