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?"

Practice

1. Which MATLAB function is best suited to read numeric data from a CSV file into a matrix?

easy

A. csvread

B. readtable

C. readmatrix

D. load

Solution

1. Step 1: Understand the data type

   Numeric data is best handled as a matrix in MATLAB.

2. Step 2: Choose the appropriate function

   readmatrix is designed to read numeric CSV data directly into a matrix.

3. Final Answer:

   readmatrix -> Option C

4. Quick Check:

   Numeric CSV data = readmatrix [OK]

Hint: Use readmatrix for numeric CSV files quickly [OK]

Common Mistakes:

• Using readtable for purely numeric data
• Using load which is for MAT files
• Confusing csvread with readmatrix (csvread is older)

2. Which of the following is the correct syntax to write a matrix A to a CSV file named data.csv in MATLAB?

easy

A. writetable('data.csv', A);

B. writecsv(A, 'data.csv');

C. csvwrite(A, 'data.csv');

D. writematrix(A, 'data.csv');

Solution

1. Step 1: Identify the correct function for matrix writing

   writematrix is the modern function to write numeric matrices to CSV files.

2. Step 2: Check syntax correctness

   The syntax writematrix(A, 'data.csv'); correctly specifies the matrix and filename.

3. Final Answer:

   writematrix(A, 'data.csv'); -> Option D

4. Quick Check:

   Write matrix to CSV = writematrix [OK]

Hint: Use writematrix(matrix, filename) to save numeric CSV [OK]

Common Mistakes:

• Using non-existent function writecsv
• Using csvwrite which is outdated
• Using writetable for numeric matrix without conversion

3. What will be the output of the following MATLAB code?

A = [1, 2; 3, 4];
writematrix(A, 'test.csv');
B = readmatrix('test.csv');
disp(B);

medium

A. [1 2; 3 4]

B. [1 2 3 4]

C. [1; 2; 3; 4]

D. Error: File not found

Solution

1. Step 1: Write matrix to CSV

   The matrix A is saved as a 2x2 CSV file with rows [1,2] and [3,4].

2. Step 2: Read matrix from CSV

   readmatrix reads the CSV back into the same 2x2 numeric matrix.

3. Final Answer:

   [1 2; 3 4] -> Option A

4. Quick Check:

   Write and read matrix preserves shape [OK]

Hint: writematrix and readmatrix keep matrix shape intact [OK]

Common Mistakes:

• Expecting a single row vector output
• Confusing disp output format with array shape
• Assuming file read error without saving first

4. Consider this MATLAB code snippet:

T = readtable('data.csv');
writetable(T, 'output.csv');

If data.csv contains mixed numeric and text data, what is a common error to watch for?

medium

A. Using csvwrite to write tables causes incorrect output

B. Using writetable on a numeric matrix causes syntax error

C. Forgetting to close the file after reading causes runtime error

D. Using readmatrix instead of readtable causes syntax error

Solution

1. Step 1: Understand data type in CSV

   Mixed numeric and text data require table format to preserve all data correctly.

2. Step 2: Identify correct write function

   csvwrite only supports numeric data and will fail or produce incorrect output for tables.

3. Final Answer:

   Using csvwrite to write tables causes incorrect output -> Option A

4. Quick Check:

   csvwrite not for tables = error [OK]

Hint: Use writetable for mixed data, not csvwrite [OK]

Common Mistakes:

• Using readmatrix for mixed data losing text
• Assuming file must be closed manually in MATLAB
• Using writetable on numeric matrix without conversion

5. You have a CSV file with columns: Name (text), Age (numeric), and Score (numeric). You want to read it, increase all Score values by 10%, and save the updated data back to a CSV file. Which MATLAB code snippet correctly does this?

hard

A. data = csvread('file.csv');
data(:,3) = data(:,3) * 1.1;
csvwrite('file.csv', data);

B. T = readtable('file.csv');
T.Score = T.Score * 1.1;
writetable(T, 'file.csv');

C. T = readtable('file.csv');
T(:,3) = T(:,3) * 1.1;
writetable(T, 'file.csv');

D. A = readmatrix('file.csv');
A(:,3) = A(:,3) * 1.1;
writematrix(A, 'file.csv');

Solution

1. Step 1: Read mixed data correctly

   Use readtable to read CSV with text and numeric columns preserving all data types.

2. Step 2: Update the numeric Score column

   Access the Score column by name and multiply by 1.1 to increase by 10%.

3. Step 3: Save updated table back to CSV

   Use writetable to save the modified table preserving text and numeric data.

4. Final Answer:

   T = readtable('file.csv'); T.Score = T.Score * 1.1; writetable(T, 'file.csv'); -> Option B

5. Quick Check:

   Mixed data update = readtable + modify column + writetable [OK]

Hint: Use readtable and writetable for mixed data updates [OK]

Common Mistakes:

• Using readmatrix loses text column
• Trying to multiply table columns by index incorrectly
• Using csvread/csvwrite which don't support text