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# Metrics
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Last Updated: 2025-04-28 01:12:26.971822
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Last Updated: 2025-04-28 19:26:44.182602
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This metrics page provides an overview of user activity collected by Google Analytics across the three pillars of Project Pythia: our portal which includes information about the project as well as our resource gallery, our Foundations book, and our Cookbooks gallery. Information is either all-time (from a pre-project start date of March 2020) or year-to-date as indicated and is updated nightly to provide real-time and automated insights into our engagement, impact, and audience reach. If you would like to request a different metrics analysis, timeframe, or view, please [open a GitHub issue](https://github.com/ProjectPythia/projectpythia.github.io/issues/new/choose).
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| Project | All-Time Users |
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| ----- | ----- |
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| Portal | 19.1K |
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| Foundations | 75.6K|
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| Foundations | 75.7K|
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| Cookbooks | 22.0K |
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## Chart of Active Users by Project Since Year Start
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Paleoclimate observations obtained from tree rings or the geochemical composition of speleothems, ice and sediments provide an out-of-sample validation of climate models. However, comparing the output of climate models directly with the paleoclimate observations is difficult: (1) they are often expressed in different quantities (i.e., temperature vs ring width), (2) paleoclimate observations have large time uncertainties, (3) paleoclimate observations often incorporate more than one environmental signal (i.e., temperature AND moisture).
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Recently, [Steinman et al. (2022)](https://doi.org/10.1073/pnas.2120015119) used PCA analysis to compare model and data output. Here, we use a similar approach with the [CESM Last Millennium simulation](https://www2.cesm.ucar.edu/models/cesm1.2/) and proxy records stored on the [LiPDverse](https://lipdverse.org). This repository contains paleoclimate datasets that have been curated by the community and are archived in a standard format, facilitating analysis.
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Recently, [Steinman et al. (2022)](https://doi.org/10.1073/pnas.2120015119) used PCA analysis to compare model and data output. Here, we use a similar approach with the [CESM Last Millennium simulation](https://www.cesm.ucar.edu/community-projects/lme) and proxy records stored on the [LiPDverse](https://lipdverse.org). This repository contains paleoclimate datasets that have been curated by the community and are archived in a standard format, facilitating analysis.
<ahref="https://youtu.be/kstc-6uz7AQ"class="text-decoration-none"><h4class="display-4 p-0">Python Tutorial Seminar Series - Numpy</h4></a>
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<pclass="card-subtitle"><strong>Author:</strong> A Kootz, Project Pythia<br/><strong>Affiliation:</strong> <ahref="https://ncar.ucar.edu/">NCAR</a></p>
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<pclass="card-subtitle"><strong>Author:</strong> Project Pythia, A Kootz<br/><strong>Affiliation:</strong> <ahref="https://ncar.ucar.edu/">NCAR</a></p>
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<pclass="my-2">Recording from the Python Tutorial Seminar Series introducing the Python Package `numpy`. The content to follow along with this video is hosted on this <Ahref="https://colab.research.google.com/drive/1zcjaGXofLzUXkQzJKnANE9Z3yFUt0q7E?">Numpy Google Collab</A>.
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</p>
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<ahref="https://youtu.be/GEFnL8C62u8"class="text-decoration-none"><h4class="display-4 p-0">Python Tutorial Seminar Series - Object Oriented Programming</h4></a>
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<pclass="card-subtitle"><strong>Author:</strong> A Kootz, Project Pythia<br/><strong>Affiliation:</strong> <ahref="https://ncar.ucar.edu/">NCAR</a></p>
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<pclass="card-subtitle"><strong>Author:</strong> Project Pythia, A Kootz<br/><strong>Affiliation:</strong> <ahref="https://ncar.ucar.edu/">NCAR</a></p>
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<pclass="my-2">Recording from the Python Tutorial Seminar Series introducing Object Oriented Programming. The content to follow along with this video is hosted in this <Ahref="https://github.com/pilotchute/oop_hrrr_tutorial">Object Oriented Programming Tutorial GitHub Repository</A>.
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</p>
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<pclass="my-2">Recording from the Python Tutorial Seminar Series introducing the Python Package `cartopy`. The content to follow along with this video is hosted in this <Ahref="https://github.com/michaelavs/cartopy_tutorial">Cartopy Tutorial GitHub Repository</A>.
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</p>
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<ahref="https://youtu.be/fYkPn0Nttlg"class="text-decoration-none"><h4class="display-4 p-0">Python Tutorial Seminar Series - Git and GitHub</h4></a>
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<pclass="card-subtitle"><strong>Author:</strong> Kevin Paul, Project Pythia<br/><strong>Affiliation:</strong> <ahref="https://ncar.ucar.edu/">NCAR</a></p>
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<pclass="card-subtitle"><strong>Author:</strong> Project Pythia, Kevin Paul<br/><strong>Affiliation:</strong> <ahref="https://ncar.ucar.edu/">NCAR</a></p>
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<pclass="my-2">Recording from the Python Tutorial Seminar Series introducing the tools Git and GitHub. The content to follow along with this tutorial is hosted in this <Ahref="https://github.com/NCAR/git-github-demo">Git and GitHub Demo GitHub Repository</A>.
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</p>
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<ahref="https://youtu.be/BsV3ek7qsiM"class="text-decoration-none"><h4class="display-4 p-0">Python Tutorial Seminar Series - Pandas</h4></a>
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<pclass="card-subtitle"><strong>Author:</strong> Project Pythia, Drew Camron, Max Grover<br/><strong>Affiliation:</strong> <ahref="https://ncar.ucar.edu/">NCAR</a></p>
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<pclass="card-subtitle"><strong>Author:</strong> Max Grover, Project Pythia, Drew Camron<br/><strong>Affiliation:</strong> <ahref="https://ncar.ucar.edu/">NCAR</a></p>
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<pclass="my-2">Recording from the Python Tutorial Seminar Series introducing the Python Package `pandas`. The content to follow along with this video is hosted in this <Ahref="https://github.com/mgrover1/ncar_pandas_tutorial">Pandas Tutorial GitHub Repository</A>.
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</p>
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<ahref="https://www.youtube.com/watch?v=uiWDQKI8YTQ&t=6s"class="text-decoration-none"><h4class="display-4 p-0">Python Tutorial Seminar Series - GeoCAT-Comp</h4></a>
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<pclass="card-subtitle"><strong>Author:</strong> A Kootz, Project Pythia<br/><strong>Affiliation:</strong> <ahref="https://ncar.ucar.edu/">NCAR</a></p>
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<pclass="card-subtitle"><strong>Author:</strong> Project Pythia, A Kootz<br/><strong>Affiliation:</strong> <ahref="https://ncar.ucar.edu/">NCAR</a></p>
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<pclass="my-2">Recording from the Python Tutorial Seminar Series introducing `geocat-comp`. The content to follow along with this video is hosted in this <Ahref="https://github.com/pilotchute/geocat_comp_tutorial">GeoCat-Comp GitHub Repository</A>.
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<h1>Metrics<aclass="headerlink" href="#metrics" title="Link to this heading"><iclass="fas fa-link"></i></a></h1>
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<p>Last Updated: 2025-04-28 01:12:26.971822</p>
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<p>Last Updated: 2025-04-28 19:26:44.182602</p>
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<p>This metrics page provides an overview of user activity collected by Google Analytics across the three pillars of Project Pythia: our portal which includes information about the project as well as our resource gallery, our Foundations book, and our Cookbooks gallery. Information is either all-time (from a pre-project start date of March 2020) or year-to-date as indicated and is updated nightly to provide real-time and automated insights into our engagement, impact, and audience reach. If you would like to request a different metrics analysis, timeframe, or view, please <aclass="reference external" href="https://github.com/ProjectPythia/projectpythia.github.io/issues/new/choose">open a GitHub issue</a>.</p>
<h2>Table of Total Active Users by Project<aclass="headerlink" href="#table-of-total-active-users-by-project" title="Link to this heading"><iclass="fas fa-link"></i></a></h2>
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<p>This Cookbook covers paleoclimate model-data comparison using spatio-temporal pattern obtained using Principal Component Analysis (PCA).</p>
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<p>Paleoclimate observations obtained from tree rings or the geochemical composition of speleothems, ice and sediments provide an out-of-sample validation of climate models. However, comparing the output of climate models directly with the paleoclimate observations is difficult: (1) they are often expressed in different quantities (i.e., temperature vs ring width), (2) paleoclimate observations have large time uncertainties, (3) paleoclimate observations often incorporate more than one environmental signal (i.e., temperature AND moisture).</p>
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<p>Recently, <aclass="reference external" href="https://doi.org/10.1073/pnas.2120015119">Steinman et al. (2022)</a> used PCA analysis to compare model and data output. Here, we use a similar approach with the <aclass="reference external" href="https://www2.cesm.ucar.edu/models/cesm1.2/">CESM Last Millennium simulation</a> and proxy records stored on the <aclass="reference external" href="https://lipdverse.org">LiPDverse</a>. This repository contains paleoclimate datasets that have been curated by the community and are archived in a standard format, facilitating analysis.</p>
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<p>Recently, <aclass="reference external" href="https://doi.org/10.1073/pnas.2120015119">Steinman et al. (2022)</a> used PCA analysis to compare model and data output. Here, we use a similar approach with the <aclass="reference external" href="https://www.cesm.ucar.edu/community-projects/lme">CESM Last Millennium simulation</a> and proxy records stored on the <aclass="reference external" href="https://lipdverse.org">LiPDverse</a>. This repository contains paleoclimate datasets that have been curated by the community and are archived in a standard format, facilitating analysis.</p>
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