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그룹화 변수, categorical형 데이터, dataset형 배열

Statistics and Machine Learning Toolbox™는 두 가지 추가 데이터형을 제공합니다. nominal 데이터형과 ordinal 데이터형을 사용하여 순서가 있는 비수치적 이산 데이터와 순서가 없는 비수치적 이산 데이터를 다룹니다. dataset 배열 데이터형을 사용하여 데이터형이 각각 다른 변수를 포함한 여러 변수를 단일 객체에 저장합니다. 그러나, 이러한 데이터형은 Statistics and Machine Learning Toolbox만의 고유한 데이터형입니다. 더 나은 제품 간 호환성을 제공하기 위해, 각각 MATLAB®에서 제공되는 categorical 데이터형 또는 table 데이터형을 사용하십시오. 자세한 내용을 보려면 categorical형 배열 생성하기 항목과 테이블을 생성하고 사용하기 항목을 참조하거나 테이블과 categorical형 배열 비디오를 참조하십시오.


모두 확장

nominal(Not Recommended) Arrays for nominal data
ordinal(Not Recommended) Arrays for ordinal data
dummyvarCreate dummy variables
gplotmatrixMatrix of scatter plots by group
grp2idxCreate index vector from grouping variable
gscatter그룹별 산점도 플롯
mat2dataset(Not Recommended) Convert matrix to dataset array
cell2dataset(Not Recommended) Convert cell array to dataset array
struct2dataset(Not Recommended) Convert structure array to dataset array
table2dataset(Not Recommended) Convert table to dataset array
dataset2cell(Not Recommended) Convert dataset array to cell array
dataset2struct(Not Recommended) Convert dataset array to structure
dataset2tableConvert dataset array to table
export(Not Recommended) Write dataset array to file
ismissing(Not Recommended) Find dataset array elements with missing values
join(Not Recommended) Merge dataset array observations


dataset(Not Recommended) Arrays for statistical data

도움말 항목

categorical형 데이터

Nominal and Ordinal Arrays

Nominal and ordinal arrays store data that have a finite set of discrete levels, which might or might not have a natural order.

Advantages of Using Nominal and Ordinal Arrays

Easily manipulate category levels, carry out statistical analysis, and reduce memory requirements.

Grouping Variables

Grouping variables are utility variables used to group or categorize observations.

Dummy Variables

Dummy variables let you adapt categorical data for use in classification and regression analysis.

Other MATLAB Functions Supporting Nominal and Ordinal Arrays

Learn about MATLAB functions that support nominal and ordinal arrays.

Create Nominal and Ordinal Arrays

Create nominal and ordinal arrays using nominal and ordinal, respectively.

Categorize Numeric Data

Categorize numeric data into a categorical ordinal array using ordinal.

Change Category Labels

Change the labels for category levels in nominal or ordinal arrays using setlabels.

Add and Drop Category Levels

Add and drop levels from a nominal or ordinal array.

Merge Category Levels

Merge categories in a nominal or ordinal array using mergelevels.

Reorder Category Levels

Reorder the category levels in nominal or ordinal arrays using reorderlevels.

Sort Ordinal Arrays

Determine sorting order for ordinal arrays.

Plot Data Grouped by Category

Plot data grouped by the levels of a categorical variable.

Summary Statistics Grouped by Category

Compute summary statistics grouped by levels of a categorical variable.

Test Differences Between Category Means

Test for significant differences between category (group) means using a t-test, two-way ANOVA (analysis of variance), and ANOCOVA (analysis of covariance) analysis.

Index and Search Using Nominal and Ordinal Arrays

Index and search data by its category, or group.

Linear Regression with Categorical Covariates

Perform a regression with categorical covariates using categorical arrays and fitlm.

dataset형 배열

Dataset Arrays

Dataset arrays store data with heterogeneous types.

Create a Dataset Array from Workspace Variables

Create a dataset array from a numeric array or heterogeneous variables existing in the MATLAB workspace.

Create a Dataset Array from a File

Create a dataset array from the contents of a tab-delimited or a comma-separated text, or an Excel file.

Add and Delete Observations

Add and delete observations in a dataset array.

Add and Delete Variables

Add and delete variables in a dataset array.

dataset형 배열 변수의 데이터에 액세스하기

dataset형 배열 변수와 변수의 데이터를 사용해서 작업을 수행합니다.

Select Subsets of Observations

Select an observation or subset of observations from a dataset array.

Sort Observations in Dataset Arrays

Sort observations (rows) in a dataset array using the command line.

Merge Dataset Arrays

Merge dataset arrays using join.

Stack or Unstack Dataset Arrays

Reformat dataset arrays using stack and unstack.

Clean Messy and Missing Data

Find, clean, and delete observations with missing data in a dataset array.

Calculations on Dataset Arrays

Perform calculations on dataset arrays, including averaging and summarizing with a grouping variable.

Export Dataset Arrays

Export a dataset array from the MATLAB workspace to a text or spreadsheet file.

Dataset Arrays in the Variables Editor

The MATLAB Variables editor provides a convenient interface for viewing, modifying, and plotting dataset arrays.

Index and Search Dataset Arrays

Learn the many ways to index into dataset arrays.

Regression Using Dataset Arrays

This example shows how to perform linear and stepwise regression analyses using dataset arrays.