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  <title>Data Learning Cohorts Portal</title>
  <subtitle>A gallery of team projects produced by participants in our data learning cohorts, with methods, dashboards and posters.</subtitle>
  <id>https://crypticpy.github.io/phct/examples/cohort-portal/catalog/</id>
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  <updated>2026-08-05T00:00:00-05:00</updated>
  <entry>
    <title>How soon does a critical violation come back?</title>
    <id>https://crypticpy.github.io/phct/examples/cohort-portal/catalog/repeat-violation-risk/</id>
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    <published>2026-07-02T00:00:00-05:00</published>
    <updated>2026-08-05T00:00:00-05:00</updated>
    <summary>Measured how long facilities go after a critical inspection violation before the next one, and whether an early re-inspection changes that.</summary>
    <category term="2026" label="2026"/>
    <category term="environmental-health" label="Environmental Health"/>
    <category term="civic-analytics" label="Civic Analytics"/>
    <category term="survival-analysis" label="Survival analysis"/>
    <category term="python" label="Python"/>
    <category term="pandas" label="pandas"/>
    <category term="lifelines" label="lifelines"/>
    <category term="statistics" label="Statistics"/>
    <category term="data-cleaning" label="Data cleaning"/>
    <category term="visualization" label="Visualization"/>
    <category term="food-safety" label="food safety"/>
    <category term="inspections" label="inspections"/>
    <category term="prioritization" label="prioritization"/>
  </entry>
  <entry>
    <title>Which languages our front counters actually need</title>
    <id>https://crypticpy.github.io/phct/examples/cohort-portal/catalog/language-access-front-counter/</id>
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    <published>2026-07-21T00:00:00-05:00</published>
    <updated>2026-07-21T00:00:00-05:00</updated>
    <summary>Turned two years of interpreter request logs into a dashboard that shows which languages are asked for, at which counters, and at which hours.</summary>
    <category term="2026" label="2026"/>
    <category term="communications" label="Communications"/>
    <category term="data-storytelling" label="Data Storytelling"/>
    <category term="tableau" label="Tableau"/>
    <category term="sql" label="SQL"/>
    <category term="survey-coding" label="Survey coding"/>
    <category term="stakeholder-workshops" label="Stakeholder workshops"/>
    <category term="visualization" label="Visualization"/>
    <category term="stakeholder-interviews" label="Stakeholder interviews"/>
    <category term="data-cleaning" label="Data cleaning"/>
    <category term="language-access" label="language access"/>
    <category term="equity" label="equity"/>
    <category term="front-line-services" label="front-line services"/>
  </entry>
  <entry>
    <title>Booking lead time and missed appointments</title>
    <id>https://crypticpy.github.io/phct/examples/cohort-portal/catalog/appointment-lead-time/</id>
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    <published>2026-06-24T00:00:00-05:00</published>
    <updated>2026-06-24T00:00:00-05:00</updated>
    <summary>Tested whether how far ahead an appointment is booked predicts whether it is kept, using two years of de-identified scheduling counts from three community clinics.</summary>
    <category term="2026" label="2026"/>
    <category term="community-programs" label="Community Programs"/>
    <category term="data-science-essentials" label="Data Science Essentials"/>
    <category term="logistic-regression" label="Logistic regression"/>
    <category term="r" label="R"/>
    <category term="tidymodels" label="tidymodels"/>
    <category term="quarto" label="Quarto"/>
    <category term="data-cleaning" label="Data cleaning"/>
    <category term="statistics" label="Statistics"/>
    <category term="visualization" label="Visualization"/>
    <category term="access" label="access"/>
    <category term="scheduling" label="scheduling"/>
    <category term="clinic-operations" label="clinic operations"/>
  </entry>
  <entry>
    <title>Forecasting the permit review backlog</title>
    <id>https://crypticpy.github.io/phct/examples/cohort-portal/catalog/permit-backlog-forecast/</id>
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    <published>2025-07-08T00:00:00-05:00</published>
    <updated>2026-02-11T00:00:00-06:00</updated>
    <summary>Built a weekly forecast of the permit review queue so the licensing team can see a backlog forming instead of discovering it two months later.</summary>
    <category term="2025" label="2025"/>
    <category term="permitting-licensing" label="Permitting &amp; Licensing"/>
    <category term="data-science-essentials" label="Data Science Essentials"/>
    <category term="time-series" label="Time series"/>
    <category term="python" label="Python"/>
    <category term="statsmodels" label="statsmodels"/>
    <category term="scheduled-job" label="Scheduled job"/>
    <category term="statistics" label="Statistics"/>
    <category term="automation" label="Automation"/>
    <category term="visualization" label="Visualization"/>
    <category term="operations" label="operations"/>
    <category term="forecasting" label="forecasting"/>
    <category term="backlog" label="backlog"/>
  </entry>
  <entry>
    <title>Reading 1,800 survey comments without reading 1,800 comments</title>
    <id>https://crypticpy.github.io/phct/examples/cohort-portal/catalog/survey-open-ends/</id>
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    <published>2025-09-30T00:00:00-05:00</published>
    <updated>2025-09-30T00:00:00-05:00</updated>
    <summary>Coded two years of open-ended community survey answers into a small set of themes, and published the codebook so the next survey can be compared with this one.</summary>
    <category term="2025" label="2025"/>
    <category term="community-programs" label="Community Programs"/>
    <category term="data-storytelling" label="Data Storytelling"/>
    <category term="qualitative-coding" label="Qualitative coding"/>
    <category term="python" label="Python"/>
    <category term="scikit-learn" label="scikit-learn"/>
    <category term="inter-rater-reliability" label="Inter-rater reliability"/>
    <category term="data-cleaning" label="Data cleaning"/>
    <category term="stakeholder-interviews" label="Stakeholder interviews"/>
    <category term="visualization" label="Visualization"/>
    <category term="survey" label="survey"/>
    <category term="community-engagement" label="community engagement"/>
    <category term="qualitative" label="qualitative"/>
  </entry>
  <entry>
    <title>Where the two weeks go in a records request</title>
    <id>https://crypticpy.github.io/phct/examples/cohort-portal/catalog/records-request-turnaround/</id>
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    <published>2025-06-26T00:00:00-05:00</published>
    <updated>2025-06-26T00:00:00-05:00</updated>
    <summary>Reconstructed the full path of a mailed-in vital records request from timestamps and found that most of the wait happened in a queue nobody owned.</summary>
    <category term="2025" label="2025"/>
    <category term="vital-records" label="Vital Records"/>
    <category term="civic-analytics" label="Civic Analytics"/>
    <category term="process-mining" label="Process mining"/>
    <category term="sql" label="SQL"/>
    <category term="r" label="R"/>
    <category term="ggplot2" label="ggplot2"/>
    <category term="data-cleaning" label="Data cleaning"/>
    <category term="automation" label="Automation"/>
    <category term="visualization" label="Visualization"/>
    <category term="stakeholder-interviews" label="Stakeholder interviews"/>
    <category term="process-improvement" label="process improvement"/>
    <category term="service-delivery" label="service delivery"/>
    <category term="records" label="records"/>
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