Houses#

House prices and characteristics for houses sold in King County (home of Seattle) from May, 2014 through May, 2015.

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Initialization#

library(fosdata)
data <- fosdata::houses

Accessing fields#

data <- fosdata::houses
sqft_living15 <- data$sqft_living15 # Just a random field in the dataset

Interactive R Sample#

You can use the R editor below to interactively explore the dataset and generate plots. This contains a fully self-contained R environment with fosdata, ggplot2, and dplyr loaded.

webR + fosdata Test

Console

Plot

No plot generated yet.

LLM instructions#

If using an LLM, you can copy-paste the following instructions to accompany your prompt to inform the model of the fields and their types in the dataset.

LLM Instructions

The fosdata::houses dataset containing the following fields:

fields[21]{name,type,values}:
  id,numeric,n/a
  date,character,n/a
  price,numeric,n/a
  bedrooms,integer,n/a
  bathrooms,numeric,n/a
  sqft_living,integer,n/a
  sqft_lot,integer,n/a
  floors,numeric,n/a
  waterfront,integer,n/a
  view,integer,n/a
  condition,integer,n/a
  grade,integer,n/a
  sqft_above,integer,n/a
  sqft_basement,integer,n/a
  yr_built,integer,n/a
  yr_renovated,integer,n/a
  zipcode,integer,n/a
  lat,numeric,n/a
  long,numeric,n/a
  sqft_living15,integer,n/a
  sqft_lot15,integer,n/a

Fields#

Name	Description	Type	Min	Max	Values
`id`	unique id of each home	numeric	1000102	9900000190	-
`date`	date of sale	character	-	-	-
`price`	price of sale	numeric	75000	7700000	-
`bedrooms`	number of bedrooms	integer	-	33	-
`bathrooms`	number of bathrooms	numeric	-	8	-
`sqft_living`	Square footage of living space	integer	290	13540	-
`sqft_lot`	square foot of the lot	integer	520	1651359	-
`floors`	number of floors	numeric	1	3.5	-
`waterfront`	Is the home on the waterfront?	integer	-	1	-
`view`	Rating from 0 to 4 of how good the view is	integer	-	4	-
`condition`	Rating from 1-5 on the condition of the home	integer	1	5	-
`grade`	Rating of 1-13 on the quality of materials used. 1-3 is substandard, 7 is average and 11-13 is excellent.	integer	1	13	-
`sqft_above`	square footage above ground level	integer	290	9410	-
`sqft_basement`	square footage of basement	integer	-	4820	-
`yr_built`	year built	integer	1900	2015	-
`yr_renovated`	year renovated	integer	-	2015	-
`zipcode`	zip code of house	integer	98001	98199	-
`lat`	lattitude	numeric	47.1559	47.7776	-
`long`	longitude	numeric	-122.519	-121.315	-
`sqft_living15`	square footage of the 15 nearest neighbors	integer	399	6210	-
`sqft_lot15`	lot sizes of 15 nearest neighbors	integer	651	871200	-

Source#

https://www.kaggle.com/harlfoxem/housesalesprediction