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SciPydata~30 mins

Distance matrix computation in SciPy - Mini Project: Build & Apply

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Distance matrix computation
📖 Scenario: You work as a data analyst for a delivery company. You have a list of locations represented by their coordinates. Your task is to calculate the distances between each pair of locations to help plan efficient delivery routes.
🎯 Goal: Build a program that computes the distance matrix between multiple points using the scipy library.
📋 What You'll Learn
Create a list of points with exact coordinates
Set up a variable to specify the distance metric
Use scipy.spatial.distance_matrix to compute the distance matrix
Print the resulting distance matrix
💡 Why This Matters
🌍 Real World
Delivery companies and logistics planners use distance matrices to find the shortest routes and optimize travel times.
💼 Career
Data analysts and data scientists often compute distance matrices when working with geographic data or clustering tasks.
Progress0 / 4 steps
1
Create the list of points
Create a variable called points that is a list containing these exact coordinate pairs: [0, 0], [3, 4], and [6, 8].
SciPy
Need a hint?

Use a list of lists to represent the points. Each inner list is a coordinate pair.

2
Set the distance metric
Create a variable called metric and set it to the string 'euclidean' to specify the distance type.
SciPy
Need a hint?

The metric variable is a string that tells the function which distance formula to use.

3
Compute the distance matrix
Import distance_matrix from scipy.spatial. Then create a variable called dist_matrix that stores the distance matrix computed by calling distance_matrix(points, points).
SciPy
Need a hint?

Use from scipy.spatial import distance_matrix to import the function.

4
Print the distance matrix
Write a print statement to display the variable dist_matrix.
SciPy
Need a hint?

The printed matrix shows distances between each pair of points.