公开数据集
数据结构 ? 0M
Data Structure ?
* 以上分析是由系统提取分析形成的结果,具体实际数据为准。
README.md
Collected from Internet 2019-12-28 for an Machine learning task and I want to share this dataset with all who is interested to use it.
For any questions about the dataset feel free to contact me on fredrick_nilsson '@' yahoo.comthe names, email addresses, institutions, and other contact information of the donors and creators of the data set.
Data Set Information:
The dataset contains of 10'000 or 100'000 rows and of 22 columns The data has been cleaned in the way that
column price and square_feet never is empty but the dataset is saved as it was created.
Can be used for different machine learning tasks such as clustering, classification and also regression for the squares feet column
Attribute Information:
Provide information
id = unique identifier of apartment
category = category of classified
title = title text of apartment
body = body text of apartment
amenities = like AC, basketball,cable, gym, internet access, pool, refrigerator etc.
bathrooms = number of bathrooms
bedrooms = number of bedrooms
currency = price in current
fee = fee
has_photo = photo of apartment
pets_allowed = what pets are allowed dogs/cats etc.
price = rental price of apartment
price_display = price converted into display for reader
price_type = price in USD
square_feet = size of the apartment
address = where the apartment is located
cityname = where the apartment is located
state = where the apartment is located
latitude = where the apartment is located
longitude = where the apartment is located
source = origin of classified
time = when classified was created
bout each attribute in your data set.
Relevant Papers:
Provide references to papers that have cited this data set in the past (if any).
Citation Request:
If you have no special citation requests, please leave this field blank.
帕依提提提温馨提示
该数据集正在整理中,为您准备了其他渠道,请您使用
- 分享你的想法
全部内容
数据使用声明:
- 1、该数据来自于互联网数据采集或服务商的提供,本平台为用户提供数据集的展示与浏览。
- 2、本平台仅作为数据集的基本信息展示、包括但不限于图像、文本、视频、音频等文件类型。
- 3、数据集基本信息来自数据原地址或数据提供方提供的信息,如数据集描述中有描述差异,请以数据原地址或服务商原地址为准。
- 1、本站中的所有数据集的版权都归属于原数据发布者或数据提供方所有。
- 1、如您需要转载本站数据,请保留原数据地址及相关版权声明。
- 1、如本站中的部分数据涉及侵权展示,请及时联系本站,我们会安排进行数据下线。