没有笔记本用了

from numpy.core.fromnumeric import reshapefrom skimage import iofrom sklearn import cluster from sklearn.cluster import KMeansimport numpy as np#第一步读取图像image = io.imread("ladybug.png")# io.imshow(image)# io.show()#第二步取出长和宽rows = image.shape[0].

#1.读取数据（可以下载，也可以直接读取） #下载from os import read, sepimport pandas as pd# df = pd.io.parsers.read_csv(filepath='https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data',# header=None,sep=",",) #读取df = pd.read_csv(".

根据之前的房屋出租的特征和价格来预测房屋出租价格-----基于欧式距离import pandas as pdfrom sklearn.preprocessing import StandardScalerfeatures = ['accommodates','bedrooms','bathrooms','beds','price','minimum_nights','maximum_nights','number_of_reviews']dc_listings = pd.read_csv('l