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 Create Tables and Assign Data to Them ou regardez la vidéo Tables and Categorical Arrays (Tables et tableaux catégoriels).
Fonctions
développer tout
Créer des tables et convertir le type
table | Table array with named variables that can contain different types |
array2table | Convert hom*ogeneous array to table |
cell2table | Convert cell array to table |
struct2table | Convert structure array to table |
table2array | Convert table to hom*ogeneous 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 | Print summary of table, timetable, or categorical array |
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 in array |
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 (depuis R2020a) |
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 in output table or timetable |
unstack | Unstack data from one variable into multiple variables |
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 | Set union of two arrays |
intersect | Set intersection of two arrays |
ismember | Array elements that are members of set array |
setdiff | Set difference of two arrays |
setxor | Set exclusive OR of two arrays |
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 (depuis R2019b) |
groupsummary | Group summary computations |
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
Data Cleaner | Preprocess and organize column-oriented data (depuis R2022a) |
Tâches du Live Editor
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 (depuis R2019b) |
Stack Table Variables | Combine values from multiple table variables into one table variable in the Live Editor (depuis R2020a) |
Unstack Table Variables | Distribute values from one table variable to multiple table variables in the Live Editor (depuis R2020a) |
Rubriques
- Create Tables and Assign Data to Them
There are several ways to create tables and assign data to them. You can create tables from input arrays, preallocate tables and fill them in later, or import tables from text files or spreadsheets.
- 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.
- Rename and Describe Table Variables
- Add, Delete, and Rearrange Table Variables
- Add and Delete Table Rows
- Clean Messy and Missing Data in Tables
- Using Row Labels in Table and Timetable Operations
- Convert Text in Table Variables to Categorical
- Add Custom Properties to Tables and Timetables
- 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.
- Calculations When Tables Have Both Numeric and Nonnumeric Data
- Summarize or Pivot Data in Tables Using Groups
- Perform Calculations by Group in Table
- Rules for Table and Timetable Mathematics
- 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.
- Changes to DimensionNames Property in R2016b
Tables can raise compatibility warnings, and changedimension names, when you modify the DimensionNames property.
Exemples présentés
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