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When [ ` DataFrame ` ] ( DataFrame.md ) is used within Jupyter/Kotlin Notebook or Datalore with the Kotlin Kernel,
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something special happens:
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- After every cell execution, all new global variables of type DataFrame are analyzed and replaced
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+ After every cell execution, all new global variables of type DataFrame are analyzed and replaced
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with a typed [ ` DataFrame ` ] ( DataFrame.md ) wrapper along with auto-generated extension properties for data access.
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For instance, say we run:
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@@ -16,7 +16,11 @@ val df /* : AnyFrame */ = DataFrame.read("titanic.csv")
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<!-- -END-->
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- In normal Kotlin code, we would now have a variable of type [ ` AnyFrame ` (=` DataFrame<*> ` )] ( DataFrame.md ) that doesn't have any
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+ TODO make df <dataFrame >
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+
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+
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+ In normal Kotlin code, we would now have a variable of type [ ` AnyFrame ` (=` DataFrame<*> ` )] ( DataFrame.md ) that doesn't
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+ have any
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extension properties to access its columns. We would either have to define them manually or use the
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[ ` @DataSchema ` ] ( schemas.md ) annotation to [ generate them] ( schemasGradle.md#configuration ) .
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@@ -39,7 +43,8 @@ df.add("lastName") { name.split(",").last() }
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The ` titanic.csv ` file could be found [ here] ( https://github.com/Kotlin/dataframe/blob/master/data/titanic.csv ) .
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- Extension properties can be generated in IntelliJ IDEA using the [ Kotlin Dataframe Gradle plugin] ( schemasGradle.md#configuration ) .
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+ Extension properties can be generated in IntelliJ IDEA using
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+ the [ Kotlin Dataframe Gradle plugin] ( schemasGradle.md#configuration ) .
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<warning >
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In notebooks generated properties won't appear and be updated until the cell has been executed.
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