CSV file handling in MATLAB - Time & Space Complexity

Time Complexity: CSV file handling

O(n)

Understanding Time Complexity

When working with CSV files in MATLAB, it's important to know how the time to read or write data changes as the file size grows.

We want to understand how the program's running time grows when handling bigger CSV files.

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

filename = 'data.csv';
data = readmatrix(filename);

for i = 1:size(data, 1)
    disp(data(i, :));
end

This code reads a CSV file into a matrix and then prints each row one by one.

Identify Repeating Operations

• Primary operation: Looping through each row of the data matrix to display it.
• How many times: Once for every row in the CSV file (n times, where n is number of rows).

How Execution Grows With Input

As the number of rows in the CSV file increases, the number of times the loop runs also increases directly.

Input Size (n)	Approx. Operations
10	About 10 times loop runs
100	About 100 times loop runs
1000	About 1000 times loop runs

Pattern observation: The work grows in a straight line with the number of rows.

Final Time Complexity

Time Complexity: O(n)

This means the time to process the CSV file grows directly in proportion to the number of rows.

Common Mistake

[X] Wrong: "Reading a CSV file always takes the same time no matter how big it is."

[OK] Correct: The bigger the file, the more rows there are to read and process, so it takes longer.

Interview Connect

Understanding how file size affects processing time helps you write efficient code and explain your reasoning clearly in real projects or interviews.

Self-Check

"What if we used readtable instead of readmatrix? How would the time complexity change?"