I am trying to create a KMeans clustering model based on a csv data set that I have compiled. The data set is organized as such:
population longitude latitude
Atlanta, GA
Austin, TX
...
I tried just plotting the data, which isn't working, if produces a scatter plot where you can't see the axis or the data points, and I can't really tell of the Kmeans algorithim is working.
import numpy as np
import matplotlib.pyplot as plt
from sklearn.cluster import KMeans
from sklearn import datasets
import pandas as pd
import csv
data = pd.read_csv("data.csv")
print (data.head())
plt.scatter(x=data['Population'].astype(bytes), y=data['Longitude'].astype(bytes), z=data["Latitude"].astype(bytes))
plt.xlim(0,1000000)
plt.ylim(0,5000)
plt.zlim(0,5000)
plt.xlabel('Population')
plt.ylabel('Longitude')
plt.zlabel('Latitude')
plt.title('KMeans Clustering for Population vs. Latitude and Longitude', fontsize = 10)
plt.show()
x = data.iloc[:,1:3] #selecting features
#Clustering
kmeans = KMeans(3)
kmeans.fit(x)
#Clustering Results
indentified_clusters = kmeans.fit_predict(x)
indentified_clusters
array([1,1,0.0,2])
data_with_clusters = data.copy()
data_with_clusters['Clusters'] = identified_clusters
plt.scatter(data_with_clusters['Population'],data_with_clusters['Longitude'],data_with_clusters['Latitude']c=data_with_clusters['Clusters'],cmap='rainbow')
