AmesHousing

This package contains the data described by De Cock (2011) where 82 fields were recored for 2,930 properties in Ames IA. Different versions of the data are available using the package.

Installation

To install the package from CRAN, use

install.packages("AmesHousing")

You can install the development version of AmesHousing from GitHub with:

# install.packages("devtools")
# devtools::install_github("topepo/AmesHousing")
install.packages("AmesHousing", repos = c('https://topepo.r-universe.dev', 'https://cloud.r-project.org'))

Details

• Using data(ames_raw), a tibble is attached with the data as it is found on the website.
• Using the command, make_ames() a tibble is returned that has a processed version of the data (see notes below).
• The command make_ordered_ames() returns a similar tibble but several of the variables are formatted as ordered factors.

The Processed Version

The exact details can be found in the code of make_ames but a summary is:

• All factors are unordered.
• PID and Order are removed.
• Spaces and special characters in column names where changed to snake case. To be consistent, SalePrice was changed to Sale_Price.
• One row was removed with an unexplained missing value.
• Many factor levels were changed to be more understandable (e.g. Split_or_Multilevel instead of 080)
• Many missing values were reset. For example, if the variable Bsmt_Qual was missing, this implies that there is no basement on the property. Instead of a missing value, the value of Bsmt_Qual was changed to No_Basement. Similarly, numeric data pertaining to basements were set to zero where appropriate such as variables Bsmt_Full_Bath and Total_Bsmt_SF.
• Garage_Yr_Blt contained many missing data and was removed.
• Approximate longitude and latitude are included for the properties. Also, note that there are 6 properties with identical geotags. These are units within the same building.

The Ordered Factor Version

make_ordinal_ames is the same as make_ames but many ordinal data were changed to class ordered.