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  • Getting Started
  • Data Handling
  • Desing Policy
  • Visualization
  • Model Fitting
  • Geographic Analyses
  • Model Comparison
  • Sensitivity
  • Surrogating Functions
  • Testing
  • Realtime Data Incorporation
  • Model Development Workflow
  • Wrapper EMAWorkbench
  • Data Used in this Cookbook
    • Baby Name Data
    • Collecting US decennial census data
    • Carbon Data Sources
    • Manufacturing Defects Synthetic Data
    • Ebola Data Loader
    • Parse gmail .mbox file
    • Town Formatter
    • Prepare georeferenced data for artificial disease outbreak in Europe
  • Chapters to be Written
  • End Notes
PySD-Cookbook
  • Data Used in this Cookbook
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Data Used in this Cookbook

All of the data used in these notebooks was either gathered from public sources, or is created synthetically for the purpose of this cookbook. The notebooks listed here show how each set was collected or generated.

  • Baby Name Data
  • Collecting US decennial census data
    • Collect data on male population by age, county
    • Align the datasets
  • Carbon Data Sources
    • Carbon Emissions
    • Atmospheric Carbon
    • World Population
  • Manufacturing Defects Synthetic Data
  • Ebola Data Loader
  • Parse gmail .mbox file
    • Step 1: extract relevant information from mbox file
    • Step 2: group the messages by thread
    • Step 3: find relevant timestamps
    • Step 4: Calculate the time delta
    • Step 5: Filter out threads started by the account holder
    • Step 6: Save to csv
  • Town Formatter
  • Prepare georeferenced data for artificial disease outbreak in Europe
    • Attributes in shapefile
    • Take only European countries and exclude Russia
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