Pokémon sightings: k-means clustering

We are going to continue the investigation into the sightings of legendary Pokémon from the previous exercise. Just like the previous exercise, we will use the same example of Pokémon sightings. In this exercise, you will form clusters of the sightings using k-means clustering.

x and y are columns of X and Y coordinates of the locations of sightings, stored in a pandas DataFrame, df. The following are available for use: matplotlib.pyplot as plt, seaborn as sns, and pandas as pd.

Import the kmeans and vq functions.
Use the kmeans() function to compute cluster centers by defining two clusters.
Assign cluster labels to each data point using vq() function.
Plot the points with seaborn and assign a different color to each cluster

Exercise

Pokémon sightings: k-means clustering

Instructions