如何绘制KMeans？

Question

我正在尝试使用MiniBatchKMeans和更大的数据集，并绘制2种不同的属性。我收到了一个Keyerror: 2，我相信我在for循环中出错了，但是我不知道在哪里。有人能帮我看出我的错误是什么吗？我正在运行以下代码：

import numpy as np ##Import necessary packages
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib import style
style.use("ggplot")
from pandas.plotting import scatter_matrix
from sklearn.preprocessing import *
from sklearn.cluster import MiniBatchKMeans 


url2="http://archive.ics.uci.edu/ml/machine-learning-databases/adult/adult.data" #Reading in Data from a freely and easily available source on the internet
Adult = pd.read_csv(url2, header=None, skipinitialspace=True) #Decoding data by removing extra spaces in cplumns with skipinitialspace=True
##Assigning reasonable column names to the dataframe
Adult.columns = ["age","workclass","fnlwgt","education","educationnum","maritalstatus","occupation",  
                 "relationship","race","sex","capitalgain","capitalloss","hoursperweek","nativecountry",
                 "less50kmoreeq50kn"]

print("reviewing dataframe:")
print(Adult.head()) #Getting an overview of the data
print(Adult.shape)
print(Adult.dtypes)

np.median(Adult['fnlwgt']) #Calculating median for final weight column
TooLarge = Adult.loc[:,'fnlwgt'] > 748495 #Setting a value to replace outliers from final weight column with median
Adult.loc[TooLarge,'fnlwgt']=np.median(Adult['fnlwgt']) #replacing values from final weight Column with the median of the final weight column
Adult.loc[:,'fnlwgt']


X = pd.DataFrame()
X.loc[:,0] = Adult.loc[:,'age']
X.loc[:,1] = Adult.loc[:,'hoursperweek']

kmeans = MiniBatchKMeans(n_clusters = 2)
kmeans.fit(X)

centroids = kmeans.cluster_centers_
labels = kmeans.labels_

print(centroids)
print(labels)

colors = ["g.","r."]

for i in range(len(X)):
    print("coordinate:",X[i], "label:", labels[i])
    plt.plot(X.loc[:,0][i],X.loc[:,1][i], colors[labels[i]], markersize = 10)

plt.scatter(centroids[:, 0], centroids[:, 1], marker = "x", s=150, linewidths = 5, zorder = 10)
plt.show()

当我运行for循环时，我只看到在散射矩阵中绘制的两个数据点。我是否需要与创建的数据框架不同地调用这些点？

Answer 1

您可以避免这个问题，不运行一个循环来分别绘制32,000个点中的每个点，这是错误的做法，也是不必要的。您可以简单地将两个数组传递给plt.scatter()来绘制这个散点图，不需要一个循环。使用以下几行：

colors = ["green","red"]

plt.scatter(X.iloc[:,0], X.iloc[:,1], c=np.array(colors)[labels], 
    s = 10, alpha=.1)

plt.scatter(centroids[:, 0], centroids[:, 1], marker = "x", s=150, 
    linewidths = 5, zorder = 10, c=['green', 'red'])
plt.show()

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你最初的错误是由于对熊猫索引使用不当造成的。通过这样做，您可以复制错误：

df = pd.DataFrame(list('dasdasas'))
df[1]