# Column Space (Range) > The **span** of the columns in a matrix represents the **column space**. It simply represents the set of all possible outputs. Below we see that the span of the columns of our matrix (again, the columns represent where the transformation takes our basis vectors) is one dimensional. In other words, the transformed basis vectors are [Linearly Dependent](Linear%20Dependence.md).  Note: Because the column space represents our set of all possible outputs, it is sometimes referred to as the **range** of the matrix. ### Another perspective Here we see that we have a linear transformation that can be represented by *where the basis vectors* are transformed to: %20really%20look%20like%207-34%20screenshot.png) In this case, they end up being [linearly dependent](Linear%20Dependence.md), lying a 2d plane embedded in 3 dimensions: %20really%20look%20like%207-40%20screenshot.png) This plane is referred to as the **column space**. ### Compared to the [Row Space](Row%20Space.md) The column space and row space tend to look very different. We see the row space considered here as well (the green plane): %20really%20look%20like%208-17%20screenshot%20(1).png) --- Date: 20211229 Links to: [Linear Algebra MOC](Linear%20Algebra%20MOC.md) Tags: References: * [3b1b Video](https://youtu.be/uQhTuRlWMxw?t=556)