DownloadIndexedTables provides tabular data structures where some of the columns form a sorted index. It provides the backend to JuliaDB, but can be used on its own for efficient in-memory data processing and analytics.
Features
- Both types store data in columns
- IndexedTable and NDSparse differ mainly in how data is accessed
- Both types have equal performance for Table operations (select, filter, etc.)
- Data is accessed as an N-dimensional sparse array with arbitrary indexes
- Data is accessed as a Vector of NamedTuples
- Documentation available
Project Samples
Categories
Data VisualizationLicense
MIT LicenseFollow IndexedTables.jl
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