# Understending \`dims\` kwarg
**URL:** https://discourse.julialang.org/t/understending-dims-kwarg/81121
**Category:** General Usage
**Tags:** question
**Created:** [May 15, 2022, 11:36pm UTC](https://discourse.julialang.org/t/understending-dims-kwarg/81121 "2022-05-15T23:36:34Z")
**Posts on this page:** 2
**Page:** 1
### Author:  [@eliascarv](https://discourse.julialang.org/u/eliascarv)
#### Post date: [May 15, 2022, 11:36pm UTC](https://discourse.julialang.org/t/understending-dims-kwarg/81121/1 "2022-05-15T23:36:34Z")
When I use mean function with `dims=1` (the row dimension) in a matrix, the mean of each column is returned.
Example:
```julia-repl
julia> using Statistics
julia> a = [3 5 4 5
9 8 4 9
9 9 5 6]
3×4 Matrix{Int64}:
3 5 4 5
9 8 4 9
9 9 5 6
julia> mean(a, dims=1)
1×4 Matrix{Float64}:
7.0 7.33333 4.33333 6.66667
```
Why does it happen? How does `dims` kwarg work?
---
### Author:  [@suavesito](https://discourse.julialang.org/u/suavesito)
#### Post date: [May 15, 2022, 11:55pm UTC](https://discourse.julialang.org/t/understending-dims-kwarg/81121/2 "2022-05-15T23:55:51Z")
The `dim` keyword argument specify in which dimension the n-dimensional array is going to be reduced. `dims=1` means that the mean is going to be taken reducing over rows. `dims=2` means reducing over columns.
For a 3D array, you can see how it works with this example
```julia
julia> a = [3; 5;; 4; 5;;;
9; 8;; 4; 9;;;
9; 9;; 5; 6]
2×2×3 Array{Int64, 3}:
[:, :, 1] =
3 4
5 5
[:, :, 2] =
9 4
8 9
[:, :, 3] =
9 5
9 6
julia> size(a) # rows, columns, depth
(2, 2, 3)
julia> mean(a; dims=1) # reduced over rows
1×2×3 Array{Float64, 3}:
[:, :, 1] =
4.0 4.5
[:, :, 2] =
8.5 6.5
[:, :, 3] =
9.0 5.5
julia> mean(a; dims=2) # reduced over columns
2×1×3 Array{Float64, 3}:
[:, :, 1] =
3.5
5.0
[:, :, 2] =
6.5
8.5
[:, :, 3] =
7.0
7.5
julia> mean(a; dims=3) # reduced over depth
2×2×1 Array{Float64, 3}:
[:, :, 1] =
7.0 4.33333
7.33333 6.66667
```
Hope it makes it clear. 😅