请问Python因数组无特征报错怎么处理？

Question

代码来源：北京理工pythong机器学习公开课。网址https://www.bilibili.com/video/av71711733?p=5。数据集是我自己找的。

import numpy as np
from sklearn.cluster import KMeans

def loadData(filePath):
    fr = open(filePath,'r+')
    lines = fr.readlines()
    retData = []
    retCompanyName = []
    for line in lines:
        items = line.strip().split(",")
        retCompanyName.append(items[0])
        retData.append([float(items[i])
    for i in range(1,len(items))])
        return retData,retCompanyName

if __name__=='__main__':

    data,companies=loadData('travel insurance.csv')
    km=KMeans(n_clusters=3)
    label = km.fit_predict(data)
    expenses = np.sum(km.cluster_centers_,axis=1)
    CompanyCluster = [[],[],[]]
    for i in range(len(companies)):
        CompanyCluster[label[i]].append(companies[i])
    for i in range(len(CompanyCluster)):
        print("Expenses.%.2f" %expenses[i])
        print(CompanyCluster[i])

报错内容：
Traceback (most recent call last):
File "G:/Studying/Shtrathclyde/All Python/BDT/Diagram Test.py", line 20, in
label = km.fit_predict(data)
File "D:\software_for_class\Anaconda\lib\site-packages\sklearn\cluster\k_means_.py", line 995, in fit_predict
return self.fit(X, sample_weight=sample_weight).labels_
File "D:\software_for_class\Anaconda\lib\site-packages\sklearn\cluster\k_means_.py", line 969, in fit
return_n_iter=True)
File "D:\software_for_class\Anaconda\lib\site-packages\sklearn\cluster\k_means_.py", line 309, in k_means
order=order, copy=copy_x)
File "D:\software_for_class\Anaconda\lib\site-packages\sklearn\utils\validation.py", line 558, in check_array
context))
ValueError: Found array with 0 feature(s) (shape=(1, 0)) while a minimum of 1 is required.

Process finished with exit code 1

Answer 1

应该是数据集的问题，你的数据集是怎么找的，格式和数据本身是否有问题。特别注意下，你的数据有没有列头，以及列数是否和教学的一致