Tables

Tableaux dont les colonnes nommées peuvent être de différents types

Le type de données table convient aux données orientées colonnes ou tabulaires qui sont souvent stockées sous forme de colonnes dans un fichier texte ou une feuille de calcul. Les tables se composent de lignes et de variables orientées colonnes. Les variables d’une table peuvent être de différents types de données et de différentes tailles mais elles doivent toutes comporter le même nombre de lignes. Pour plus d’informations, consultez Créer des tables et leur affecter des données ou regardez la vidéo Tables and Categorical Arrays (Tables et tableaux catégoriels).

Fonctions

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Créer des tables et convertir le type

`table`	Table array with named variables that can contain different types
`array2table`	Convert homogeneous array to table
`cell2table`	Convert cell array to table
`struct2table`	Convert structure array to table
`table2array`	Convert table to homogeneous array
`table2cell`	Convert table to cell array
`table2struct`	Convert table to structure array
`table2timetable`	Convert table to timetable
`timetable2table`	Convert timetable to table
`vartype`	Subscript into table or timetable by variable type
`convertvars`	Convert table or timetable variables to specified data type

Lire et écrire des fichiers

Importation et exportation de base

`readtable`	Create table from file
`writetable`	Write table to file

Définir des règles d’importation

`detectImportOptions`	Create import options based on file content
`spreadsheetImportOptions`	Import options object for Spreadsheets
`getvaropts`	Get variable import options
`setvaropts`	Set variable import options
`setvartype`	Set variable data types
`preview`	Preview eight rows from file using import options

Fichiers Parquet

`parquetread`	Read columnar data from a Parquet file
`parquetwrite`	Write columnar data to Parquet file
`parquetinfo`	Get information about Parquet file

Informations récapitulatives et diagramme à barres empilées

`summary`	Data summary
`height`	Number of table rows
`width`	Number of table variables
`istable`	Determine if input is table
`istabular`	Determine if input is table or timetable (depuis R2021b)
`head`	Get top rows of array or table
`tail`	Get bottom rows of array or table
`stackedplot`	Stacked plot of several variables with common x-axis

Trier, filtrer et réorganiser

Trier

`sortrows`	Sort rows of matrix or table
`unique`	Unique values
`issortedrows`	Determine if matrix or table rows are sorted
`topkrows`	Top rows in sorted order

Filtrer les lignes et les variables

`rowfilter`	Selectively import rows of interest (depuis R2022a)
`vartype`	Subscript into table or timetable by variable type

Réorganiser les variables

`addvars`	Add variables to table or timetable
`renamevars`	Rename variables in table or timetable
`movevars`	Move variables in table or timetable
`removevars`	Delete variables from table or timetable
`splitvars`	Split multicolumn variables in table or timetable
`mergevars`	Combine table or timetable variables into multicolumn variable
`convertvars`	Convert table or timetable variables to specified data type

Transformer

`rows2vars`	Reorient table or timetable so that rows become variables
`stack`	Stack data from input table or timetable into one variable of output table or timetable
`unstack`	Unstack data from input table or timetable into multiple variables of output table or timetable
`inner2outer`	Invert nested table-in-table hierarchy in tables or timetables

Personnaliser les propriétés

`addprop`	Add custom properties to table or timetable
`rmprop`	Remove custom properties from table or timetable

Opérations sur des ensembles et opérations de jointure

Joindre en utilisant des variables clés

`join`	Combine two tables or timetables by rows using key variables
`innerjoin`	Inner join between two tables or timetables
`outerjoin`	Outer join between two tables or timetables

Opérations sur des ensembles

`union`	Union of two sets of data
`intersect`	Intersection of two sets of data
`ismember`	Find set members of data
`setdiff`	Difference of two sets of data
`setxor`	Exclusive OR of two sets of data

Valeurs manquantes

`anymissing`	Determine if any array element is missing (depuis R2022a)
`ismissing`	Find missing values
`standardizeMissing`	Insert standard missing values
`rmmissing`	Remove missing entries
`fillmissing`	Fill missing entries

Appliquer des fonctions au contenu d’une table

`pivot`	Summarize tabular data in pivoted table (depuis R2023a)
`groupcounts`	Number of group elements
`groupfilter`	Filter by group
`groupsummary`	Compute summary statistics by group
`grouptransform`	Transform by group
`findgroups`	Find groups and return group numbers
`splitapply`	Split data into groups and apply function
`rowfun`	Apply function to table or timetable rows
`varfun`	Apply function to table or timetable variables
`vartype`	Subscript into table or timetable by variable type
`convertvars`	Convert table or timetable variables to specified data type

Applications

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Nettoyer et organiser des tables

Data Cleaner

Preprocess and organize column-oriented data (depuis R2022a)

Tâches du Live Editor

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Créer un tableau croisé dynamique et joindre ou empiler des tables

Compute by Group	Summarize, transform, or filter by group in the Live Editor (depuis R2021b)
Pivot Table	Summarize tabular data in pivoted table in the Live Editor (depuis R2023b)
Join Tables	Combine two tables using key variables in the Live Editor
Stack Table Variables	Combine values from multiple table variables into one table variable in the Live Editor
Unstack Table Variables	Distribute values from one table variable to multiple table variables in the Live Editor

Rubriques

Créer des tables et leur affecter des données
Il existe différents moyens de créer des tables et de leur affecter des données. Vous pouvez créer des tables à partir de tableaux en entrée, préallouer des tables pour les remplir par la suite ou importer des tables à partir de fichiers texte ou de feuilles de calcul.
Control How MATLAB Imports Your Data
If you want to control the import process beyond the options provided by the readtable function, such as defining how to handle missing data or errors, then create an import options object before importing the data.
Access Data in Tables

Indexing into tables with parentheses, dot notation, and curly braces accesses table data in different ways. You can use indexing to create a table that is a subset of a larger table or to create an array from data in a table.
Direct Calculations on Tables and Timetables

You can perform calculations directly on tables and timetables without indexing to extract their data. All the variables in your tables and timetables must have data types that support calculations. (depuis R2023a)
Plots That Support Tables
Create plots by passing tables directly to plotting functions.
Tables of Mixed Data
Use tables to store mixed-type data conveniently, access data with numeric or named indexing, and to store metadata.

Sélection d՚exemples

Data Cleaning and Calculations in Tables

Clean data stored in a table or timetable. Perform computations by using the numeric and categorical data that the table contains.

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Grouped Calculations in Tables and Timetables

Perform in-place calculations on groups of data in tables and timetables.

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