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Kotlin Dataframe aims to reconcile Kotlin static typing with dynamic nature of data by utilizing both the full power of Kotlin language and opportunities provided by intermittent code execution in Jupyter notebooks and REPL.
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Kotlin Dataframe aims to reconcile Kotlin's static typing with the dynamic nature of data by utilizing both the full power of the Kotlin language and the opportunities provided by intermittent code execution in Jupyter notebooks and REPL.
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***Hierarchical** — represents hierarchical data structures, such as JSON or a tree of JVM objects.
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***Functional** — data processing pipeline is organized in a chain of `DataFrame` transformation operations. Every operation returns a new instance of `DataFrame` reusing underlying storage wherever it's possible.
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***Readable** — data transformation operations are defined in DSL close to natural language.
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***Practical** — provides simple solutions for common problems and ability to perform complex tasks.
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***Practical** — provides simple solutions for common problems and the ability to perform complex tasks.
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***Minimalistic** — simple, yet powerful data model of three column kinds.
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***Interoperable** — convertable with Kotlin data classes and collections.
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***Generic** — can store objects of any type, not only numbers or strings.
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