**Euclidean Distance** is the most commonly used distance formula. To find the Euclidean distance between two points, we first calculate the squared distance between each dimension. If we add up all of these squared differences and take the square root, we’ve computed the Euclidean distance.

Let’s take a look at the equation that represents what we just learned:

`$\sqrt{(a_1-b_1)^2+(a_2-b_2)^2+\ldots+(a_n - b_n)^2}$`

The image below shows a visual of Euclidean distance being calculated:

`$d = \sqrt{(a_1-b_1)^2+(a_2-b_2)^2}$`

### Instructions

**1.**

Create a function named `euclidean_distance()`

that takes two lists as parameters named `pt1`

and `pt2`

.

In the function, create a variable named `distance`

, set it equal to `0`

, and return `distance`

.

**2.**

After defining `distance`

, create a `for`

loop to loop through the dimensions of each point.

Add the squared difference between each dimension to `distance`

.

Remember, in Python, you can square the variable `num`

by using `num ** 2`

.

**3.**

Outside of the `for`

loop, take the square root of `distance`

and return that value.

**4.**

Print the Euclidean distance between `[1, 2]`

and `[4, 0]`

.

Print the Euclidean distance between `[5, 4, 3]`

and `[1, 7, 9]`

.

Why can’t you find the difference between `[2, 3, 4]`

and `[1, 2]`

?