boligfinn

The goal of boligfinn is to be able to extract data from Finn.no and create a database for current appartments on sale. You can then just use your imagination on how to use the data. The default areas are around OSLO but you can easily adjust the code to whatever town in Norway you are interested in.

The documentation can be found here (https://ybkamaleri.github.io/boligfinn)

Installation

You can install the released version of boligfinn from CRAN when I am ready to publish it in CRAN with:

install.packages("boligfinn")

but until that time comes, then you have to install it from GitHub.

if(!require(remotes)) install.packages("remotes")
remotes::install_github("ybkamaleri/boligfinn")

Extract data

This is a basic example which shows you how to use the main function ie. finn():

library(boligfinn)
## basic example code
finn()

## or save as an object
DF = finn()

## specify the parameter
DF = finn(area = 1, pmin = 35, pmax = 5000000)

Currently these areas can be selected:

1:Bygdøy/Frogner

2:Grünerløkka/Sofienberg

3:Sagene/Torshov

4:St.Hanshaugen/Ullevål

5:Uranienborg/Majorstuen

You could combine area during download such as area = c(1,3), but isn’t recommended. You could only get maximum 50 rows per download and I haven’t figured it out how to solve this problem and still in the TODO list. Please come with solution if you have it!

For the minimum and maximum prices, it is in million. You can write it the whole digits or exclude the zeros.

Create database

If you are interested to save the extracted data to a database.

You know that it won’t be easy to remember things that you don’t use frequently 😄. At least I have that problem. Therefore if you want to save the downloaded data as a database, this will be created automatically and you don’t have to remember what the database is call! Therefore it is not necessary to specify the database name.

read_db()

#save the output
dt = read_db()

But if you are curious and want to check the path for database file, use path_db() function.

Hope you will find this package is useful! You are welcome to make pull request to contribute.