Overview
Introduction
Transposing a matrix, swapping its rows and columns, is one of the most basic operations in linear algebra, used constantly in everything from statistics to computer graphics.
This tool handles it for a matrix of any size, including non-square ones and matrices with decimal values.
What Is Transpose a Matrix?
The transpose of a matrix is a new matrix where the original's rows become columns (and vice versa). If the original is M rows by N columns, the transpose is N rows by M columns.
It's usually written with a superscript T, so the transpose of matrix A is written A^T.
How Transpose a Matrix Works
The input is split into rows on newlines and values on commas, with each value parsed as a floating-point number. Blank lines are ignored, and every row must have the same number of values.
The value originally at row i, column j is placed at row j, column i in the output, which is then formatted back into the site's standard matrix notation.
When To Use Transpose a Matrix
Use it whenever you need to reorient a matrix, for example to make a matrix multiplication's dimensions line up, or to convert a set of row vectors into column vectors.
It's also useful for double-checking a transpose you've computed by hand.
Often used alongside Find the Determinant of a Matrix, Generate an Identity Matrix and Generate Random Matrices.
Features
Advantages
- Works on matrices of any dimensions, not just square ones.
- Preserves decimal precision exactly since no arithmetic is performed, only repositioning.
Limitations
- Every row in the input must have the same number of values, a ragged input is rejected with an error.
Examples
Best Practices & Notes
Best Practices
- Double-check the input has one row per line and consistent comma-separated values before submitting.
Developer Notes
transposeMatrix() builds the result with Array.from() over the column count for the outer loop and the row count for the inner loop. Each value at `matrix[row][col]` is placed at `[col][row]`, a direct index swap with no matrix arithmetic involved.
Transpose a Matrix Use Cases
- Aligning matrix dimensions before a multiplication
- Converting between row-vector and column-vector representations
- Checking a hand-computed transpose for a linear algebra assignment
Common Mistakes
- Assuming the transpose of a non-square matrix keeps the same dimensions, an M by N matrix becomes N by M, not M by N.
- Leaving a row with a different number of values than the others, which the parser flags as an error rather than silently padding.
Tips
- Transposing a matrix twice returns the original matrix, a quick way to sanity-check the tool.