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 language—with seamless scaling from direct in-memory computation to computations backed by external files or databases.

Tabular — general representation of 2D table data

Dataset — a general hierarchical dataset containing nested lists and associations

Query — represent a hierarchical query on a dataset or other expression

{e₁,e₂,…} — a list of values (List)

<|key₁->e₁,key₂->e₂,…|> — an association of keys and values (Association)

dataset[…] — apply transformations to a dataset

dataset[[…]] — extract parts from 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

Sort  ▪  SortBy  ▪  Union  ▪  DeleteDuplicates

TakeLargest  ▪  TakeSmallest  ▪  TakeLargestBy  ▪  TakeSmallestBy

Lookup — look up sets of values from associations

Missing Values

Missing — represent a missing value

DeleteMissing — delete missing values

MissingBehavior — control computations with missing values

Relational Data

JoinAcross — combine tables by column

Merge — combine associations by key

Custom Query Construction

Function  ▪  Query

Data Computations

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

Basic Structural Operations

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

Dataset Presentation

Grid  ▪  Column  ▪  Multicolumn  ▪  TabView  ▪  MenuView

Creating Associations

Association — turn a list of rules into an association

AssociationMap — create an association by applying a function to a list of keys

AssociationThread — create an association from a list of keys and a list of values

Counts, CountsBy — associate values with the number of times they occur

GroupBy — group values by collecting those sharing a criterion

PositionIndex — build an index of positions at which values occur

Creating Datasets

SemanticImport — import a file as a Dataset

EntityValue — obtain data from the Wolfram Knowledgebase in the form of a Dataset

ResourceData — get data from the Wolfram Data Repository, often as a Dataset

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