Clinical DataFrame Generator

{   "id": "INTEGER",
    "description": "STRING" }

• "repeat": 2

  or

  "repeat": {"Min": 1, "Max": 2}

  
  Specifies the number of times this element should be repeated. The other values are repeated meanwhile.

• "Columns": {"ColumnA": "INTEGER", "ColumnB": "STRING"}

  
  Sub-Columns (for the generation of repeating elements in a LONG format way).

• "type": "INTEGER"

  
  Datatype of the element to generate. Is inferred by the datatype of distribution if present.

• "missingProbability": 0.2

  
  Probability, that element in this column will be null.

• "UniformDistribution": {"min": "2010-01-01", "max": "2011-12-31"}

  
  Sample the values for this column from a UniformDistribution.

• "GaussianDistribution": {"min": "2010-01-01", "max": "2011-12-31", "mean": "2011-06-01", "sigma": "P20D"}

  
  Sample the values for this column from a GaussianDistribution.

• "ValueDistribution": {"male": 0.52, "female": 0.45, "other": 0.03}

  
  Generate the given values with the given probability.
  Please note that also numbers and booleans must be quoted due to JSON format limitations. E.g. you have to use

  {"1": 0.5, "2": 0.25, "3": 0.25}

  instead of

  {1: 0.5, 2: 0.25, 3: 0.25}

• "FakerDistribution": "name.fullName"

  or

  "FakerDistribution": {"expression": "name.fullName", "locale": "de"}

  
  Use the Java Faker library to generate a value. Trigger auto-completion using Ctrl+Space to see available options!
• "XegerDistribution": "[A-Za-z0-9]{2,5}"
  Use Xeger to generate strings matching a specific regular expression.