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4. Numpy drones We are going to start with the same array we did way up above: But this time, instead of Uber drivers, think

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4. Numpy drones We are going to start with the same array we did way up above: But this time, instead of Uber drivers, think of these as positions of Alphabet's Wing delivery drones. Now we would like to find the closest drone to a customer who is at 7,1 . With the previous example we used Manhattan Distance. With drones, we can compute the distance as the crow flies -- or Euclidean Distance. We probably learned how to do this way back in 7 th grade when we learned the Pythagorean Theorem which states: c2=a2+b2 Where c is the hypotenuse and a and b are the two other sides. So, if we want to find c : c=a2+b2 If we want to find the distance between the drone and a customer, x and y in the formula becomes Distxy=(x1y1)2+(x2y2)2 and for wing_1a who is at [4,5] and our customer who is at [7,1] then the formula becomes: Distxy=(x1y1)2+(x2y2)2=(47)2+(51)2=32+42=9+16=25=5 Sweet! And to generalize this distance formula: Distxy=(x1y1)2+(x2y2)2 to n-dimensions: Distxy=i=1n(xiyi)2 Can you write a function euclidean that takes 3 arguments: droneLocation, droneNames, and an array representing one customer's position and returns the name of the closest drone

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