What are column datatypes in the Engine?
This article summarizes the different column datatypes in the AI & Analytics Engine.
In a dataset, values in the same column must be of the same datatype. The Engine currently supports the following datatypes:
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Datatype
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Description
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Corresponding Type
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Examples
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Numeric
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Whole numbers (Integers) and fractional numbers (real)
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Julia: Float32, Float64, Int, Int32, Int64, BigInt
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Python: double, int
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R: numeric, double, int, bigint
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-8, -5, -3, 0, 1, 3, 5, 8
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-8.53, -0.001, 1.358
|
|
Boolean
|
True or False
|
|
|
|
Text
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- Free-form text
- Category labels
- JSON strings of attribute-value pairs
- JSON string representation of arrays/lists
|
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Julia: String, CategoricalVector
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Python: str, object (pandas)
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R: character
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John Doe
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New York
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sunny, cloudy, windy
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{"shape": "circle", "color": "blue", "size": 5}
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[1, 2, "a", true, null]
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[{"height": 183, "weight": 80}, {"height": 159, "weight": 60}]
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|
DateTime
|
Timestamp indicating date and time
|
|
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2015-04-03 12:34:56
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2015-04-03
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