Code Monkey home page Code Monkey logo

house_prices_data_analysis's Introduction

House_prices

Projects File descriptions Ask a home buyer to describe their dream house, and they probably won't begin with the height of the basement ceiling or the proximity to an east-west railroad. But this dataset proves that much more influences price negotiations than the number of bedrooms or a white-picket fence.

With 79 explanatory variables describing (almost) every aspect of residential homes, this dataset can be used to predict the final price of each home.

train.csv - the training set test.csv - the test set data_description.txt - full description of each column, originally prepared by Dean De Cock but lightly edited to match the column names used here sample_submission.csv - a benchmark submission from a linear regression on year and month of sale, lot square footage, and number of bedrooms Data fields

Here's a brief version of what you'll find in the data description file.

SalePrice - the property's sale price in dollars. This is the target variable that you're trying to predict. MSSubClass: The building class MSZoning: The general zoning classification LotFrontage: Linear feet of street connected to property LotArea: Lot size in square feet Street: Type of road access Alley: Type of alley access LotShape: General shape of property LandContour: Flatness of the property Utilities: Type of utilities available LotConfig: Lot configuration LandSlope: Slope of property Neighborhood: Physical locations within Ames city limits Condition1: Proximity to main road or railroad Condition2: Proximity to main road or railroad (if a second is present) BldgType: Type of dwelling HouseStyle: Style of dwelling OverallQual: Overall material and finish quality OverallCond: Overall condition rating YearBuilt: Original construction date YearRemodAdd: Remodel date RoofStyle: Type of roof RoofMatl: Roof material Exterior1st: Exterior covering on house Exterior2nd: Exterior covering on house (if more than one material) MasVnrType: Masonry veneer type MasVnrArea: Masonry veneer area in square feet ExterQual: Exterior material quality ExterCond: Present condition of the material on the exterior Foundation: Type of foundation BsmtQual: Height of the basement BsmtCond: General condition of the basement BsmtExposure: Walkout or garden level basement walls BsmtFinType1: Quality of basement finished area BsmtFinSF1: Type 1 finished square feet BsmtFinType2: Quality of second finished area (if present) BsmtFinSF2: Type 2 finished square feet BsmtUnfSF: Unfinished square feet of basement area TotalBsmtSF: Total square feet of basement area Heating: Type of heating HeatingQC: Heating quality and condition CentralAir: Central air conditioning Electrical: Electrical system 1stFlrSF: First Floor square feet 2ndFlrSF: Second floor square feet LowQualFinSF: Low quality finished square feet (all floors) GrLivArea: Above grade (ground) living area square feet BsmtFullBath: Basement full bathrooms BsmtHalfBath: Basement half bathrooms FullBath: Full bathrooms above grade HalfBath: Half baths above grade Bedroom: Number of bedrooms above basement level Kitchen: Number of kitchens KitchenQual: Kitchen quality TotRmsAbvGrd: Total rooms above grade (does not include bathrooms) Functional: Home functionality rating Fireplaces: Number of fireplaces FireplaceQu: Fireplace quality GarageType: Garage location GarageYrBlt: Year garage was built GarageFinish: Interior finish of the garage GarageCars: Size of garage in car capacity GarageArea: Size of garage in square feet GarageQual: Garage quality GarageCond: Garage condition PavedDrive: Paved driveway WoodDeckSF: Wood deck area in square feet OpenPorchSF: Open porch area in square feet EnclosedPorch: Enclosed porch area in square feet 3SsnPorch: Three season porch area in square feet ScreenPorch: Screen porch area in square feet PoolArea: Pool area in square feet PoolQC: Pool quality Fence: Fence quality MiscFeature: Miscellaneous feature not covered in other categories MiscVal: $Value of miscellaneous feature MoSold: Month Sold YrSold: Year Sold SaleType: Type of sale SaleCondition: Condition of sale

house_prices_data_analysis's People

Contributors

jet2016 avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.