title	output
Webscrape Boliga	html_document keep_md true

What does it do?

This package has a few helper functions to webscrape the content of home sales prices from Boliga.

This package will try to follow the Ethical Scraper guidelines.

This is how you use it

First of all, you need to install the package using devtools.

library(devtools)

if(!require(boliga)){
  install_github("krose/boliga")
}

## Loading required package: boliga

It is rather simple to use. You only need to do the following to scrape the actual sales prices for an area from Boliga's homepage:

library(boliga)
library(dplyr)
library(ggplot2)

boliger <- boliga_webscrape_sold(min_sale_date = "2017-04-01", 
                                 max_sale_date = "2017-06-30", 
                                 type = "Fritidshus", 
                                 postal_code = 4500)

glimpse(boliger)

## Observations: 103
## Variables: 10
## $ adresse     <chr> "Østre Pilevej 3, 4500 Nykøbing Sj", "A Olufsensve...
## $ pris        <int> 275000, 657000, 740000, 1995000, 570000, 1535000, ...
## $ pris_kvm    <int> 2777, 18771, 8809, 57000, 8769, 21619, 26612, 6549...
## $ vaerelser   <int> 4, 3, 5, 3, 4, 4, 3, 5, 4, 4, 2, 3, 4, 4, 3, 3, 4,...
## $ type        <chr> "Sommerhus", "Sommerhus", "Sommerhus", "Sommerhus"...
## $ kvm         <int> 99, 35, 84, 35, 65, 71, 62, 82, 52, 71, 42, 40, 73...
## $ bygget_aar  <chr> "2018", "1958", "1957", "1974", "1971", "2011", "2...
## $ udbudsrabat <dbl> -4, 10, 6, 0, NA, -4, -4, NA, NA, 1, -8, 0, NA, -4...
## $ dato        <date> 2017-06-30, 2017-06-30, 2017-06-30, 2017-06-29, 2...
## $ salgstype   <chr> "Alm. Salg", "Alm. Salg", "Alm. Salg", "Alm. Salg"...

I just bought a summer house in Nykøbing Sj. so let's see how the distribution of prices is for the 2nd quarter of 2017.

ggplot(boliger %>% filter(pris_kvm < 50000), aes(pris_kvm)) +
  geom_histogram()