解决：TypeError: '(slice(None, None, None), 1)' is an invalid key

问题背景

使用matplotlib将DBSCAN分类结果散点图可视化时提示此TypeError

源代码：
from sklearn.cluster import DBSCAN import pandas as pd import
matplotlib.pyplot as plt def devicesDbscan():
path="./unique_deviceID_lng_lat.csv"
df=pd.read_csv(path,header=None,names=["DEVICE_ID","LNG","LAT"])
print(df.shape()) X_df=df.drop("DEVICE_ID",axis=1) #去掉ID
y_pred=DBSCAN(eps=0.1,min_samples=1,n_jobs=20).fit_predict(X_df) #拟合并返回预测标签
count_clusters = len(set(y_pred)) #聚类簇的数目
print("clusters的数目："+str(count_clusters))
plt.scatter(X_df[:,0],X_df[:,1],c=y_pred) #-->提示错误地方 plt.show() if
__name__=="__main__": devicesDbscan()
解决

将DataFrame对象X_df转成ndarray数组即可
from sklearn.cluster import DBSCAN import pandas as pd import
matplotlib.pyplot as plt def devicesDbscan():
path="./unique_deviceID_lng_lat.csv"
df=pd.read_csv(path,header=None,names=["DEVICE_ID","LNG","LAT"])
print(df.shape()) X_df=df.drop("DEVICE_ID",axis=1)
y_pred=DBSCAN(eps=0.1,min_samples=1,n_jobs=20).fit_predict(X_df) count_clusters
= len(set(y_pred)) print("clusters的数目："+str(count_clusters))
plt.scatter(X_df.values[:,0],X_df.values[:,1],c=y_pred) plt.show() if
__name__=="__main__": devicesDbscan()
 

 

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