Built site for gh-pages

.nojekyll

@@ -1 +1 @@
-bc4360ed
+ba550089

search.json

@@ -95,7 +95,7 @@
     "href": "index.html#latest-open-source-statistics",
     "title": "Open-source Healthcare Statistics",
     "section": "Latest open-source statistics",
-    "text": "Latest open-source statistics\n\n\nCode\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\nData updated as of: 14 January 2024.\n\n\n\n\nTable 1: open-source statistics\n\n\n\n\n\n\n\n\nOrganisation\nOpen Repositories\nTop Language\nTop License\n\n\n\n\nnhsconnect\n195\nHTML\nApache License 2.0\n\n\nopensafely\n188\nPython\nMIT License\n\n\nNHSDigital\n182\nPython\nMIT License\n\n\nnhsuk\n173\nHTML\nMIT License\n\n\nebmdatalab\n131\nPython\nMIT License\n\n\nnhsbsa\n117\nHTML\nMIT License\n\n\nnhsx\n90\nPython\nMIT License\n\n\nHFAnalyticsLab\n59\nR\nMIT License\n\n\nukhsa-collaboration\n58\nPython\nMIT License\n\n\nnice-digital\n57\nJavaScript\nMIT License\n\n\nHealth-Education-England\n50\nJava\nMIT License\n\n\nopensafely-core\n50\nPython\nOther\n\n\nnhsengland\n41\nPython\nMIT License\n\n\nnhs-r-community\n38\nR\nCreative Commons Zero v1.0 Universal\n\n\nCDU-data-science-team\n33\nR\nOther\n\n\nUKHSA-Internal\n30\nPython\nMIT License\n\n\nBHFDSC\n30\nPython\nApache License 2.0\n\n\nnhs-bnssg-analytics\n25\nR\nGNU General Public License v3.0\n\n\nThe-Strategy-Unit\n24\nR\nOther\n\n\nNHSLeadership\n17\nHTML\nOther\n\n\n111Online\n13\nC#\nApache License 2.0\n\n\nnhs-pycom\n11\nPython\nMIT License\n\n\nCQCDigital\n5\nC#\nMIT License\n\n\nMHRA\n5\nJavaScript\nMIT License\n\n\nNottingham-and-Nottinghamshire-ICS\n4\nR\nMIT License\n\n\nNHS-Blood-and-Transplant\n1\nC#\nGNU General Public License v3.0"
+    "text": "Latest open-source statistics\n\n\nCode\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\nData updated as of: 21 January 2024.\n\n\n\n\nTable 1: open-source statistics\n\n\n\n\n\n\n\n\nOrganisation\nOpen Repositories\nTop Language\nTop License\n\n\n\n\nnhsconnect\n195\nHTML\nApache License 2.0\n\n\nopensafely\n188\nPython\nMIT License\n\n\nNHSDigital\n182\nPython\nMIT License\n\n\nnhsuk\n173\nHTML\nMIT License\n\n\nebmdatalab\n131\nPython\nMIT License\n\n\nnhsbsa\n117\nHTML\nMIT License\n\n\nnhsx\n90\nPython\nMIT License\n\n\nHFAnalyticsLab\n59\nR\nMIT License\n\n\nukhsa-collaboration\n58\nPython\nMIT License\n\n\nnice-digital\n57\nJavaScript\nMIT License\n\n\nHealth-Education-England\n50\nJava\nMIT License\n\n\nopensafely-core\n50\nPython\nOther\n\n\nnhsengland\n41\nPython\nMIT License\n\n\nnhs-r-community\n38\nR\nCreative Commons Zero v1.0 Universal\n\n\nCDU-data-science-team\n33\nR\nOther\n\n\nUKHSA-Internal\n30\nPython\nMIT License\n\n\nBHFDSC\n30\nPython\nApache License 2.0\n\n\nnhs-bnssg-analytics\n25\nR\nGNU General Public License v3.0\n\n\nThe-Strategy-Unit\n24\nR\nOther\n\n\nNHSLeadership\n17\nHTML\nOther\n\n\n111Online\n13\nC#\nApache License 2.0\n\n\nnhs-pycom\n11\nPython\nMIT License\n\n\nCQCDigital\n5\nC#\nMIT License\n\n\nMHRA\n5\nJavaScript\nMIT License\n\n\nNottingham-and-Nottinghamshire-ICS\n4\nR\nMIT License\n\n\nNHS-Blood-and-Transplant\n1\nC#\nGNU General Public License v3.0"
   },
   {
     "objectID": "index.html#nhs-python-community-slack",

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/pages/github_api_call.html</loc>
-    <lastmod>2024-01-14T00:42:07.614Z</lastmod>
+    <lastmod>2024-01-21T00:41:41.998Z</lastmod>
   </url>
   <url>
     <loc>https://nhs-pycom.github.io/opensource-health-statistics/about.html</loc>
-    <lastmod>2024-01-14T00:42:03.270Z</lastmod>
+    <lastmod>2024-01-21T00:41:37.730Z</lastmod>
   </url>
   <url>
     <loc>https://nhs-pycom.github.io/opensource-health-statistics/index.html</loc>
-    <lastmod>2024-01-14T00:42:07.294Z</lastmod>
+    <lastmod>2024-01-21T00:41:41.690Z</lastmod>
   </url>
 </urlset>