Select Language

AI社区

公开数据集

墨尔本住房市场

墨尔本住房市场

11.74M
177 浏览
0 喜欢
0 次下载
0 条讨论
Social Issues and Advocacy,Demographics,Housing Classification

数据结构 ? 11.74M

    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

    ##Update 06/08/2018 - Well it finally happened, Melbourne housing has cooled off. So here's your challenge; 1) when did it exactly happen? , 2) Could you see it slowing down? What were the variables that showed the slowing down (was it overall price, amount sold vs unsold, change in more rentals sold and less housing, changes in which CouncilArea or Region, more houses sold in distances further away from Melbourne CBD and less closer)? 3) Could you have predicted it (I'm not sure how you would do this, but I'm sure you magicians have a way that would make me think we should burn you for being a witch) 4) Should I hold off even longer in buying a two bedroom apartment in Northcote? <-- This is the real reason for me in publishing this dataset :) # Update 22/05/2018 - Will continue with a smaller subset of the data (not as many columns). The web scraping was taking some time and also may potentially cause problems. Will continue to post the data. # Update 28/11/2017 - Last few weeks clearance levels starting to decrease (I may just be seeing a pattern I want to see.. maybe I'm just evil). Anyway, can any of you magicians make any sense of it? Melbourne is currently experiencing a housing bubble (some experts say it may burst soon). Maybe someone can find a trend or give a prediction? Which suburbs are the best to buy in? Which ones are value for money? Where's the expensive side of town? And more importantly where should I buy a 2 bedroom unit? ## Content & Acknowledgements This data was scraped from publicly available results posted every week from Domain.com.au, I've cleaned it as best I can, now it's up to you to make data analysis magic. The dataset includes Address, Type of Real estate, Suburb, Method of Selling, Rooms, Price, Real Estate Agent, Date of Sale and distance from C.B.D. ....Now with extra data including including property size, land size and council area, you may need to change your code! ## Some Key Details **Suburb**: Suburb **Address**: Address **Rooms**: Number of rooms **Price**: Price in Australian dollars **Method**: S - property sold; SP - property sold prior; PI - property passed in; PN - sold prior not disclosed; SN - sold not disclosed; NB - no bid; VB - vendor bid; W - withdrawn prior to auction; SA - sold after auction; SS - sold after auction price not disclosed. N/A - price or highest bid not available. **Type**: br - bedroom(s); h - house,cottage,villa, semi,terrace; u - unit, duplex; t - townhouse; dev site - development site; o res - other residential. **SellerG**: Real Estate Agent **Date**: Date sold **Distance**: Distance from CBD in Kilometres **Regionname**: General Region (West, North West, North, North east ...etc) **Propertycount**: Number of properties that exist in the suburb. **Bedroom2** : Scraped # of Bedrooms (from different source) **Bathroom**: Number of Bathrooms **Car**: Number of carspots **Landsize**: Land Size in Metres **BuildingArea**: Building Size in Metres **YearBuilt**: Year the house was built **CouncilArea**: Governing council for the area Lattitude: Self explanitory Longtitude: Self explanitory
    ×

    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

    注:部分数据正在处理中,未能直接提供下载,还请大家理解和支持。
    暂无相关内容。
    暂无相关内容。
    • 分享你的想法
    去分享你的想法~~

    全部内容

      欢迎交流分享
      开始分享您的观点和意见,和大家一起交流分享.
    所需积分:0 去赚积分?
    • 177浏览
    • 0下载
    • 0点赞
    • 收藏
    • 分享