Excel file reading and writing in MATLAB - Deep Dive

Overview - Excel file reading and writing

What is it?

Excel file reading and writing in MATLAB means opening Excel files to get data into MATLAB and saving MATLAB data back into Excel files. This allows you to work with spreadsheets, which are common for storing tables of numbers and text. You can read data like numbers, text, or dates from Excel sheets and write your results back to Excel for sharing or further use. It makes MATLAB and Excel work together smoothly.

Why it matters

Many people use Excel to store and share data because it is easy and familiar. Without the ability to read and write Excel files, you would have to manually copy data or use complicated conversions. This wastes time and can cause errors. Being able to read and write Excel files in MATLAB lets you automate data analysis and reporting, saving effort and reducing mistakes.

Where it fits

Before learning this, you should know basic MATLAB commands and how to work with variables and arrays. After this, you can learn more about data cleaning, visualization, and advanced file formats like CSV or databases. This topic is a bridge between MATLAB programming and real-world data stored in Excel.

Mental Model

Core Idea

Reading and writing Excel files in MATLAB is like opening and saving spreadsheets so MATLAB can understand and change the data inside.

Think of it like...

Imagine Excel files as paper notebooks full of tables. Reading is like copying the tables into your notebook (MATLAB), and writing is like updating the original notebook with your new notes.

┌─────────────┐       read       ┌─────────────┐
│ Excel File  │ ──────────────▶ │ MATLAB Data │
└─────────────┘                 └─────────────┘
       ▲                               │
       │          write                │
       └───────────────────────────────┘

Build-Up - 7 Steps

1

Foundation

Basic reading with readtable

Concept: Learn how to read Excel data into MATLAB using the readtable function.

Use readtable('filename.xlsx') to load data from the first sheet of an Excel file into a table variable in MATLAB. This table holds rows and columns like the Excel sheet, with headers as variable names.

Result

A MATLAB table variable containing the Excel sheet data.

Understanding how readtable imports Excel data as a table lets you work with spreadsheet data naturally in MATLAB.

2

Foundation

Basic writing with writetable

Concept: Learn how to save MATLAB table data back into an Excel file using writetable.

Use writetable(yourTable, 'filename.xlsx') to write the MATLAB table data into an Excel file. This creates or overwrites the file with your data, including headers.

Result

An Excel file saved with the MATLAB table data.

Knowing how to export data back to Excel enables sharing and further use of your MATLAB results.

3

Intermediate

Reading specific sheets and ranges

🤔Before reading on: do you think readtable reads all sheets by default or just one? Commit to your answer.

Concept: Learn to read data from specific sheets or cell ranges in Excel files.

Use readtable('filename.xlsx', 'Sheet', 'SheetName') to read a specific sheet. Use 'Range', 'A1:C10' to read only a part of the sheet. This helps when Excel files have multiple sheets or extra data.

Result

A MATLAB table with data from the chosen sheet or range.

Knowing how to target specific parts of Excel files prevents loading unnecessary data and speeds up processing.

4

Intermediate

Writing to specific sheets and appending data

🤔Before reading on: do you think writetable overwrites the whole Excel file or can it add data to existing sheets? Commit to your answer.

Concept: Learn to write data to specific sheets and append data without deleting existing content.

Use writetable(yourTable, 'filename.xlsx', 'Sheet', 'SheetName') to write to a specific sheet. Use 'WriteMode', 'append' to add data below existing data instead of overwriting.

Result

Excel file updated with new data in the chosen sheet, preserving existing data if appending.

Being able to write selectively and append data helps manage complex Excel files without losing information.

5

Intermediate

Handling different data types in Excel

Concept: Understand how MATLAB reads and writes numbers, text, dates, and empty cells in Excel files.

MATLAB automatically converts Excel data types: numbers become numeric arrays, text becomes strings or categorical, dates become datetime objects. Empty cells become missing or NaN. You can control this with options in readtable and writetable.

Result

Correct MATLAB data types matching Excel content for accurate analysis.

Recognizing data type conversions prevents errors and ensures your data stays meaningful after import/export.

6

Advanced

Using xlsread and xlswrite for legacy support

🤔Before reading on: do you think xlsread and xlswrite are recommended for new MATLAB code? Commit to your answer.

Concept: Learn about older functions xlsread and xlswrite for Excel interaction and their limitations.

xlsread reads numeric and text data but is less flexible than readtable. xlswrite writes numeric and text data but cannot write tables directly. These functions rely on Excel being installed and are slower. They are kept for backward compatibility.

Result

Ability to work with legacy MATLAB code that uses xlsread/xlswrite.

Knowing legacy functions helps maintain old projects but encourages moving to newer, more robust functions.

7

Expert

Performance and compatibility considerations

🤔Before reading on: do you think reading large Excel files is always fast and reliable in MATLAB? Commit to your answer.

Concept: Understand how MATLAB interacts with Excel files under the hood and how file size, format, and Excel installation affect performance.

MATLAB uses different methods depending on the OS and Excel installation. Reading large files can be slow or cause memory issues. Using binary XLSB files or CSV alternatives can improve speed. Also, some Excel features like formulas or charts are not imported.

Result

Better decisions on file formats and methods for efficient Excel data handling.

Knowing internal behavior helps avoid slowdowns and data loss, guiding you to best practices for real projects.

Under the Hood

MATLAB reads Excel files by calling underlying system libraries or Excel itself (on Windows). It parses the spreadsheet structure, extracts cell data, and converts it into MATLAB data types. Writing reverses this process, converting MATLAB data into Excel's file format and saving it. On systems without Excel, MATLAB uses Java-based or other libraries to read/write XLSX files.

Why designed this way?

Excel files are complex with many features. MATLAB uses system Excel when available for full compatibility and falls back to libraries for portability. This hybrid approach balances accuracy, speed, and cross-platform support. Older functions like xlsread/xlswrite were designed before modern table support, so newer functions improve usability.

┌─────────────┐       ┌───────────────┐       ┌─────────────┐
│ Excel File  │──────▶│ System Excel  │──────▶│ MATLAB Data │
│ (.xlsx/.xls)│       │ or Java Libs  │       │ (tables etc)│
└─────────────┘       └───────────────┘       └─────────────┘
       ▲                                            │
       │                                            │
       │                                            ▼
┌─────────────┐       ┌───────────────┐       ┌─────────────┐
│ MATLAB Data │──────▶│ System Excel  │──────▶│ Excel File  │
│ (tables etc)│       │ or Java Libs  │       │ (.xlsx/.xls)│
└─────────────┘       └───────────────┘       └─────────────┘

Myth Busters - 4 Common Misconceptions

Quick: Does readtable read all sheets in an Excel file by default? Commit to yes or no.

Common Belief: readtable reads all sheets in an Excel file automatically.

Reality: readtable reads only the first sheet by default unless you specify a different sheet.

Why it matters: Assuming all sheets are read can cause missing data and incorrect analysis if you forget to specify the sheet.

Quick: Can writetable append data to an existing Excel sheet by default? Commit to yes or no.

Common Belief: writetable always appends data to existing Excel sheets.

Reality: writetable overwrites the sheet by default; you must specify 'WriteMode', 'append' to add data.

Why it matters: Overwriting data unintentionally can cause loss of important information.

Quick: Does MATLAB preserve Excel formulas when reading and writing files? Commit to yes or no.

Common Belief: MATLAB keeps Excel formulas intact when reading and writing Excel files.

Reality: MATLAB reads the calculated values, not formulas, and writing overwrites formulas with values.

Why it matters: Losing formulas can break Excel workflows relying on dynamic calculations.

Quick: Are xlsread and xlswrite the best functions to use for Excel files in MATLAB now? Commit to yes or no.

Common Belief: xlsread and xlswrite are the recommended functions for Excel file operations.

Reality: readtable and writetable are preferred for modern MATLAB code due to better features and flexibility.

Why it matters: Using legacy functions limits functionality and may cause compatibility issues.

Expert Zone

1

readtable can automatically detect variable types but sometimes misclassifies mixed data columns, requiring manual type specification.

2

writetable can write to Excel files without Excel installed by using Java libraries, but this may limit support for some Excel features.

3

Appending data with writetable requires careful management of ranges to avoid overwriting or gaps, especially with complex sheets.

When NOT to use

For very large datasets or when Excel features like formulas, charts, or macros must be preserved, using MATLAB's Excel reading/writing is not ideal. Instead, use database connections, CSV files, or specialized Excel automation tools like ActiveX or COM interfaces on Windows.

Production Patterns

Professionals often automate data pipelines by reading raw Excel reports with readtable, processing data in MATLAB, and writing cleaned summaries back to Excel for business users. They schedule scripts to run regularly and handle errors when Excel files are locked or corrupted.

Connections

CSV file reading and writing

Similar pattern of importing and exporting tabular data but simpler format.

Understanding Excel file I/O helps grasp CSV handling since both involve reading tables, but CSV is faster and more portable without Excel-specific features.

Database connectivity

Builds on Excel I/O by connecting to larger, structured data sources for scalable data management.

Knowing Excel file reading prepares you for databases where data is also tabular but accessed via queries, enabling more powerful data workflows.

Document editing automation (e.g., Word macros)

Opposite domain but shares concept of programmatically reading and writing structured documents.

Recognizing that Excel I/O is a form of document automation helps appreciate automation principles across different file types.

Common Pitfalls

#1 Trying to read an Excel file without specifying the sheet when data is not on the first sheet.

Wrong approach:

data = readtable('data.xlsx');

Correct approach:

data = readtable('data.xlsx', 'Sheet', 'DataSheet');

Root cause:

Assuming readtable reads all sheets or the correct sheet by default.

#2 Overwriting an Excel sheet when intending to add data.

Wrong approach:

writetable(newData, 'results.xlsx', 'Sheet', 'Summary');

Correct approach:

writetable(newData, 'results.xlsx', 'Sheet', 'Summary', 'WriteMode', 'append');

Root cause:

Not knowing writetable overwrites sheets unless append mode is specified.

#3 Expecting MATLAB to preserve Excel formulas after reading and writing.

Wrong approach:

data = readtable('file.xlsx'); writetable(data, 'file.xlsx');

Correct approach:

Use Excel directly or automation tools to preserve formulas; MATLAB reads values only.

Root cause:

Misunderstanding that MATLAB reads cell values, not formulas.

Key Takeaways

Reading and writing Excel files in MATLAB lets you move data between spreadsheets and MATLAB tables easily.

Use readtable and writetable for modern, flexible Excel file operations, specifying sheets and ranges as needed.

MATLAB converts Excel data types automatically but be aware of how text, numbers, and dates are handled.

Legacy functions xlsread and xlswrite exist but are less powerful and slower than newer functions.

Understanding performance and compatibility helps avoid common pitfalls with large files or missing Excel installations.