import numpy as np Copyright By PowCoder代写 加微信 powcoder import pandas as pd import matplotlib.pyplot as plt import seaborn as sb from sklearn.tree import DecisionTreeClassifier from sklearn.model_selection import train_test_split from sklearn.metrics import confusion_matrix from sklearn.tree import plot_tree from sklearn.neighbors import LocalOutlierFactor from sklearn.cluster import KMeans pd.options.display.max_columns = 100000 listings_raw = pd.read_csv(“listings.csv”) listings = listings_raw.drop([“listing_url”,”scrape_id”,”last_scraped”,”summary”,”space”,”description”,”experiences_offered”,”neighborhood_overview”,”notes”,”transit”,”thumbnail_url”,”medium_url”,”picture_url”,”xl_picture_url”,”host_location”,”host_about”,”host_acceptance_rate”,”host_thumbnail_url”,”host_picture_url”,”host_listings_count”,”host_has_profile_pic”,”host_neighbourhood”,”neighbourhood”,”city”,”state”,”market”,”smart_location”,”country_code”,”country”,”square_feet”,”calendar_last_scraped”,”requires_license”,”license”,”jurisdiction_names”,”require_guest_profile_picture”,”require_guest_phone_verification”], axis