Unalignable boolean Series provided as indexer (index of the boolean Series and of the indexed objec

Posted 2020-10-20 yuanninesuns

　　最近在用python做数据挖掘，在聚类的时候遇到了一个非常恶心的问题。话不多说，直接上代码：

 1 from sklearn.cluster import KMeans
 2 from sklearn.decomposition import PCA
 3 import matplotlib.pyplot as plt  
 4 #kmeans算法
 5 df1=df23
 6 kmeans = KMeans(n_clusters=5, random_state=10).fit(df1)
 7 #贴上每个样本对应的簇类别标签
 8 df1[\'level\']=kmeans.labels_
 9 #df1.to_csv(\'new_df.csv\')
10 
11 df2=df1.groupby(\'level\',as_index=False)[\'level\'].agg({\'num\': np.size})
12 print(df2.head())
13 
14 #将用于聚类的数据的特征的维度降至2维
15 pca = PCA(n_components=2)
16 new_pca = pd.DataFrame(pca.fit_transform(df1))
17 print(new_pca.head())
18  
19 #可视化
20 d = new_pca[df1[\'level\'] == 0]
21 plt.plot(d[0], d[1], \'gv\')
22 d = new_pca[df1[\'level\'] == 1]
23 plt.plot(d[0], d[1], \'ko\')
24 d = new_pca[df1[\'level\'] == 2]
25 plt.plot(d[0], d[1], \'b*\')
26 d = new_pca[df1[\'level\'] == 3]
27 plt.plot(d[0], d[1], \'y+\')
28 d = new_pca[df1[\'level\'] == 4]
29 plt.plot(d[0], d[1], \'c.\')
30 
31 plt.title(\'the result of polymerization\')
32 plt.show()

 　　错误如下：

　　网上找了好久都没找到解决方法，明明之前成功过的。于是我查看了df23数据，发现它是这样的：

 与之前成功的dataframe的唯一差别就是索引！！！重要的事情说三遍！！！索引！！！索引！！！于是乎，我去找怎么重置索引的方法，见代码：

1 df24=df23[["forks_count","has_issues","has_wiki","open_issues_count","stargazers_count","watchers_count","created_pushed_time","created_updated_time"]]
2 df24=df24.reset_index()
3 df24=df24[["forks_count","has_issues","has_wiki","open_issues_count","stargazers_count","watchers_count","created_pushed_time","created_updated_time"]]

　　然后聚类就成功了。。。心累。。。。