Importing and Exporting Data

Overview

Importing and exporting data is one of the most common reasons to use MATLAB. You rarely work only with numbers that you type by hand. Instead, you usually load data from files, process it in MATLAB, then save results so other tools or people can use them.

In this chapter you will get a high level picture of how MATLAB works with external data. Later chapters in this section will go into specific formats such as text files, Excel, images, and audio. Here we focus on the general ideas that are common to all of them and the basic workflow from file to workspace and back to file again.

The Basic Data Workflow

The typical workflow around data in MATLAB follows three main steps. First you bring data from some external source into MATLAB, which is called importing. Next you process or analyze the data using MATLAB code, which you will learn in other parts of this course. Finally you save the results back to some external format, which is called exporting.

The basic picture is:

$$\text{File on disk} \rightarrow \text{MATLAB workspace} \rightarrow \text{File on disk}$$

Files on disk can have many formats, such as .txt, .csv, .xlsx, .mat, or specialized formats for images and audio. The MATLAB workspace contains variables in MATLAB data types such as numeric arrays, tables, or cell arrays. Import functions read a file and create variables in the workspace. Export functions take variables from the workspace and write them into files.

It is important to understand that importing copies data from the file into memory. Changing a variable in the workspace does not change the original file unless you explicitly export or save the modified data.

File Formats You Will Encounter

MATLAB can work with many kinds of files. In this course you will meet some of the most common categories.

Text based data files store data as readable text. Typical examples are plain text files with extension .txt and comma separated values files with extension .csv. These are often used to move data between different programs and are easy to inspect in a simple text editor.

Spreadsheet files such as Microsoft Excel workbooks use the .xls or .xlsx extension. They can contain multiple sheets, column headers, and mixed data types. MATLAB can read and write these files directly, which is helpful when you receive data from people who prefer Excel.

MAT files are MATLAB’s own binary data format, usually with extension .mat. These are created by MATLAB and are optimized for saving MATLAB variables exactly, including their types and structure. MAT files are the best choice when you want to pause work and later resume in MATLAB with the same variables.

There are also specialized formats for multimedia such as images and audio, for example .png, .jpg, .wav, or .mp3. MATLAB has functions that read these files into appropriate array forms that you can process.

In the following chapters each of these file types will be discussed in more detail. For now it is enough to recognize that different formats often require different import and export commands.

From Files to Variables: Importing Concepts

When you import data into MATLAB, there are three key questions. First, where is the file located. Second, what function should you use to read it. Third, how will MATLAB represent the data as variables.

File location is important because MATLAB needs to know which folder to read from. You can either change the current folder in MATLAB, or provide a full path to the file like C:\data\measurements.csv on Windows or /home/user/data/measurements.csv on Linux. If you see file not found errors, it is often a path or current folder issue.

The function you choose to import depends mainly on the file type. For example, text and CSV files can be handled by text specific readers, Excel files by Excel specific functions, and MAT files by load. You will see concrete functions in later sections, so in this chapter you only need the idea that MATLAB has specialized readers for different formats.

The variable representation determines how you will work with the imported data. MATLAB can store table like data as numeric matrices or as tables that keep column names and different types. Time based data can be imported into timetable objects. Images become numeric arrays where each element represents pixel values. Knowing how MATLAB represents your data lets you apply the right analysis functions.

From Variables to Files: Exporting Concepts

Exporting data from MATLAB is the reverse process. You start with variables in the workspace and write them to a file so that MATLAB or other programs can read them later.

Again, there are three important decisions. First, which variables you want to export. Second, which file format and function you will use. Third, where you want to save the file.

Choosing variables can be as simple as saving everything, or more selective if you only need specific results. You will learn to organize your workspace in other chapters, which helps you decide what to export.

The file format choice depends on who or what will use the exported file. If you plan to continue work in MATLAB and want to preserve all details, MAT files are ideal. If someone needs to open the data in a spreadsheet program, an Excel file or CSV file is more appropriate. When you plan to include plots in a report, you might export images of figures.

The save location is controlled by the current folder or a path that you specify when you export. If you give a simple file name like results.csv, MATLAB writes it to the current folder. If you give a full path, it writes to that directory. It is often helpful to organize your projects into subfolders, for example a data folder for raw data and a results folder for outputs.

Basic Import and Export Functions in Practice

Even though later chapters give full details for each data type, it is useful to see the general pattern of using import and export functions in code.

For importing, you typically call a function that returns one or more variables. For example, a generic pattern looks like:

data = someImportFunction("filename.ext");

Here someImportFunction could be a reader for text, spreadsheets, or other formats. The string "filename.ext" is the name of the file you want to read. After this call you work with the variable data like any other MATLAB variable.

For exporting, you pass variables and a target file name to a function, for example:

someExportFunction("output.ext", data);

The details, such as whether you include options for delimiters or sheet names, will appear in later sections. For now you only need to recognize the general pattern of reading from and writing to files.

MAT files follow a slightly different style because they store multiple variables by name. The basic idea is that save writes workspace variables into a MAT file and load brings them back. Their use in real projects is treated in the chapter on MAT files and importing external data.

Using the Import Tool and Interactive Workflows

MATLAB provides both command based and interactive ways to import data. The interactive approach is especially helpful for beginners or when you are not sure how the file is structured.

The Import Tool lets you visually inspect a file, detect column separators, choose which rows or columns to import, and decide how columns should be interpreted. When you finish, MATLAB can generate equivalent import code for you. This code can be reused later for similar files so you do not have to repeat the manual steps.

This mixture of interactive exploration and generated code is a common workflow in MATLAB. You interactively discover how to read your data, then you save the commands as a script so that next time the process is automatic. The later chapter on importing data with the Import Tool will focus on these details.

Thinking About Data Organization

Before you start importing and exporting, it is worth thinking briefly about how your data is organized, both on disk and inside MATLAB. Good habits here will save time as your projects grow.

On disk it is often helpful to separate raw data files from processed results. Raw data are the original files you received or recorded. Processed results are files that come from your MATLAB analysis, such as cleaned data tables or figures. Keeping these in different folders makes it easier to see what is original and what was produced by your code.

Inside MATLAB, think of your workspace as a temporary environment that should be reproducible from your files and scripts. Instead of manually editing variables, try to rely on a clear sequence of import commands and processing steps. If you can close MATLAB, clear your workspace, and rebuild everything by running your scripts, your project is on a solid foundation.

When exporting, consider whether you can regenerate a result later. If you can, there is less need to save many intermediate files. If a result takes a long time to compute, then exporting it as a file can save time in future sessions.

Common Issues When Moving Data In and Out

Working with external data can lead to a few common issues. One frequent problem is file paths that are incorrect or rely on a specific computer. For example, using absolute paths that only exist on one machine can make your scripts fail on another. Later in the course you will learn to use relative paths and manage the MATLAB path to avoid this.

Another issue arises from mismatched expectations about data formats. For example, a CSV file might use a semicolon instead of a comma as separator, or decimal commas instead of decimal points. Column headers might be present or absent. MATLAB import functions usually have options to handle these cases, and the Import Tool can help you detect them visually.

Data type differences are also common. A column that looks numeric might contain some non numeric entries, such as labels or missing markers, so MATLAB might import it as text or as a mix of types. Understanding strings, numeric types, and categorical data from other parts of this course will help you interpret what you see.

Finally, when exporting for other people or systems, be clear about what they expect. For example, do they need a specific text encoding, delimiter, or decimal separator. Knowing the target environment helps you choose appropriate export options.

Summary

Importing and exporting data in MATLAB is about moving information between external files and your workspace. You import to bring data into MATLAB, process it using MATLAB tools, and export to share or preserve results.

Different file formats need different functions, and MATLAB offers both command based and interactive methods to handle them. By thinking about file locations, formats, and target users, and by keeping your projects organized, you can build reliable and repeatable data workflows.

The following chapters will give concrete instructions for specific file types such as text and CSV files, spreadsheets, MAT files, images, and audio.