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CurrentModule = JuliaDB
DocTestSetup = quote
    using JuliaDB

JuliaDB API Reference

Data structures

Core data structures and indexing.

  • Table - JuliaDB's table datastructure
  • NDSparse - N-dimensional sparse array datastructure
  • reindex - set a different index for a dataset
  • rechunk - re-distribute a distributed dataset


Select subsets of columns, map, and filter.

  • select - select and transform a column or a subset of columns
  • map - apply a function row-wise
  • filter - filter rows
  • dropna - drop rows with NA values
  • columns - extract struct of column vectors
  • rows - extract vector of structs
  • keys - vector of keys of an NDSparse
  • values - vector of values of an NDSparse

Derivatives of select that are convenient for modifying a table's columns.

Special selectors to select a subset of columns.

  • All - select all columns
  • Not - select complementary
  • Keys - select primary columns
  • Between - select columns between two extremes


Grouping and reduction with functions or Online statistics.

  • reduce - aggregate a dataset using functions or OnlineStats
  • groupreduce - aggregate groups of rows using functions or OnlineStats
  • groupby - collect groups of rows together
  • summarize - apply summary functions to selected columns
  • reducedim - drop a dimension in NDSparse and aggregate


Combine two or more tables in various join and merge operations.

  • join - join two datasets
  • groupjoin - join two datasets by grouping (no nullables!)
  • merge - merge two datasets
  • asofjoin - time series asof-join


Reshape a table.

  • stack - reshape a table from the wide to the long format
  • unstack - Reshape a table from the long to the wide format

Loading and saving

  • loadtable - load a Table from CSV or binary data
  • loadndsparse - load an NDSparse from CSV or binary data
  • save - save a Table or NDSparse to in an efficient format