Importing Data into MATLAB: CSV, Excel, and Text Files

MATLAB is a powerful tool for engineering and scientific research, and a crucial first step in any analysis is importing your data. This module will guide you through the common methods for bringing data from CSV, Excel, and plain text files into your MATLAB workspace.

Understanding Data Import Functions

MATLAB provides a suite of built-in functions designed to handle various data file formats. Understanding these functions is key to efficiently loading your datasets for analysis and visualization.

MATLAB offers specialized functions for importing common data file types.

MATLAB's import functions simplify the process of loading data from files like CSV, Excel, and text files into the workspace, making it ready for analysis.

The primary functions for data import in MATLAB are readtable for tabular data (like CSV and Excel) and readmatrix for numerical matrices. readtable is particularly useful as it preserves column headers and data types, creating a table object that is easy to work with. readmatrix is ideal for purely numerical data where you want a matrix output. For more general text files, readlines can be used to read the file line by line.

Importing CSV Files

Comma Separated Values (CSV) files are a ubiquitous format for storing tabular data. MATLAB's

code

readtable

function is the recommended way to import them.

What is the primary MATLAB function for importing CSV files?

readtable

When using

code

readtable

, you can specify various options to handle delimiters, headers, and data types. For example,

code

T = readtable('mydata.csv');

will import 'mydata.csv' into a table named T.

Importing Excel Files

Excel files (.xlsx, .xls) are another common format. Similar to CSVs,

code

readtable

is the go-to function for importing data from Excel spreadsheets.

You can specify which sheet to read from and a range of cells. For instance,

code

T_excel = readtable('sensor_data.xlsx', 'Sheet', 'Sheet1', 'Range', 'A1:F100');

imports data from the first sheet, cells A1 to F100, into a table named T_excel.

For Excel files, readtable automatically detects headers and data types, making it very convenient for structured data.

Importing Plain Text Files

Plain text files (.txt) can contain various types of data, from simple lists to delimited columns. MATLAB offers flexibility in how you import these.

If your text file contains purely numerical data arranged in columns,

code

readmatrix

is efficient:

code

M = readmatrix('numerical_data.txt');

. If the file has mixed data types or requires more control over parsing,

code

readtable

can often be used by specifying the delimiter. For reading line by line,

code

lines = readlines('log_file.txt');

is useful.

The process of importing data can be visualized as a funnel. Raw data from files (CSV, Excel, TXT) enters the MATLAB import functions (readtable, readmatrix). These functions parse and structure the data, transforming it into MATLAB data types like tables or matrices, which are then ready for analysis within the MATLAB workspace.

📚

Text-based content

Library pages focus on text content

Best Practices and Tips

Always inspect your imported data to ensure it loaded correctly. Check data types, missing values, and the overall structure. Using the

code

head()

function on a table can quickly show you the first few rows.

What function can you use to quickly view the first few rows of an imported table?

head()

For large files, consider specifying data types during import to optimize memory usage. MATLAB's import options are extensive and can be explored through the documentation.

Summary of Import Functions

File Type	Primary MATLAB Function	Output Data Type	Key Features
CSV (.csv)	readtable	table	Handles headers, mixed data types, delimiters
Excel (.xlsx, .xls)	readtable	table	Reads specific sheets/ranges, detects headers/types
Text (.txt) - Numerical	readmatrix	matrix	Efficient for purely numerical data
Text (.txt) - General/Mixed	readtable	table	Requires specifying delimiter, flexible parsing

Learning Resources

Import Data from Text Files - MATLAB(documentation)

Official MathWorks documentation detailing various methods for importing data from text files, including CSV and fixed-width formats.

readtable - MATLAB(documentation)

Comprehensive reference page for the `readtable` function, covering its syntax, options, and examples for importing tabular data.

readmatrix - MATLAB(documentation)

Detailed documentation for the `readmatrix` function, explaining how to import numerical data into MATLAB matrices.

Importing Data into MATLAB - MATLAB Academy(tutorial)

A free online tutorial from MathWorks that covers the fundamentals of importing various data types into MATLAB.

Working with Tables in MATLAB(blog)

A blog post explaining the benefits and usage of MATLAB tables, which are commonly used when importing data.

MATLAB Data Import and Export - YouTube(video)

A video tutorial demonstrating how to import and export data in MATLAB, with practical examples.

MATLAB File I/O Functions(documentation)

An overview of MATLAB's file input/output capabilities, providing links to various file handling functions.

Data Import and Preparation in MATLAB(video)

Another helpful video tutorial focusing on the data import and preparation stages within MATLAB for analysis.

MATLAB Table Data Type(documentation)

Official documentation explaining the MATLAB `table` data type, its properties, and how to manipulate it.

Handling Missing Data in MATLAB Tables(documentation)

Guidance on how to identify and handle missing data within MATLAB tables, a common task after importing data.

Importing Data: CSV, Excel, Text Files

Importing Data into MATLAB: CSV, Excel, and Text Files

Understanding Data Import Functions

MATLAB offers specialized functions for importing common data file types.

Importing CSV Files

Importing Excel Files

Importing Plain Text Files

Best Practices and Tips

Summary of Import Functions

Learning Resources