Question: def helper _ distance ( coord 1 , coord 2 ) : Calculate the Euclidean distance between two points represented by coordinates.

def helper_distance(coord1, coord2): """ Calculate the Euclidean distance between two points represented by coordinates. Parameters: - coord1(list of str): Coordinates of the first point as [x1, y1].- coord2(list of str): Coordinates of the second point as [x2, y2]. Returns: - float: Euclidean distance between the two points. The Euclidean distance (d) between two points (x1, y1) and (x2, y2) is given by: d = sqrt((x1- x2)^2+(y1- y2)^2) Examples: >>> helper_distance(['1','2'],['4','6'])5.0>>> round(helper_distance(['3','2'],['40','6']),3)37.216 Additional doctests: >>> helper_distance(['0','0'],['0','0'])0.0>>> helper_distance(['-1','-2'],['2','4'])5.0>>> helper_distance(['5','10'],['-2','-8'])18.384>>> helper_distance(['0','0'],['-3','-4'])5.0>>> helper_distance(['0','0'],['3','4'])5.0>>> helper_distance(['-5','-5'],['5','5'])14.142""" x1, y1= map(float, coord1) x2, y2= map(float, coord2) distance = math.sqrt((x1- x2)**2+(y1- y2)**2) return distance In this example, I've added three more doctests with different coordinate pairs to showcase the versatility of the function. You can customize the examples based on the specific requirements or behavior of your function.

Step by Step Solution

There are 3 Steps involved in it

1 Expert Approved Answer
Step: 1 Unlock blur-text-image
Question Has Been Solved by an Expert!

Get step-by-step solutions from verified subject matter experts

Step: 2 Unlock
Step: 3 Unlock

Students Have Also Explored These Related Databases Questions!