Computation with Structured Datasets

The symbolic character of the Wolfram Language allows it to support an unprecedentedly flexible and general approach to structured datasets. Unifying both relational (SQL-like) and hierarchical (no-SQL) approaches, the Wolfram Language incorporates a new kind of uniquely powerful data query languagewith seamless scaling from direct in-memory computation to computations backed by external files or databases.

ReferenceReference

Dataset a general hierarchical dataset containing nested lists and associations

a list of values (List)

an association of keys and values (Association)

dataset[] transform a dataset, yielding a dataset as the result

dataset[[]] extract parts and apply operations to a dataset

Explicit Parts of Datasets

dataset[[,part,]] a numbered or named part at any level

All all parts at a given level

Span (;;) a span of parts at a given level

Keys, Values keys, values in associations

Selections and Transformations

Select parts selected to satisfy a criterion

SelectFirst  ▪  Count  ▪  Counts  ▪  CountsBy  ▪  GroupBy

Catenate merge all parts at a particular level

Sort  ▪  SortBy  ▪  Union  ▪  DeleteDuplicates

Custom Query Construction

Function

Data Computations

Total  ▪  Mean  ▪  Median  ▪  Min  ▪  Max  ▪  ...

Basic Structural Operations

Insert  ▪  Delete  ▪  Append  ▪  Take  ▪  Drop  ▪  ...

Updating Datasets

AppendTo  ▪  PrependTo  ▪  Increment  ▪  Decrement  ▪  AddTo

Dataset Presentation

Grid  ▪  Column  ▪  Multicolumn  ▪  TabView  ▪  MenuView