Pinned Repositories
airbnb-price-calculator
A workflow that estimates Airbnb pricing and predict the rental properties annual revenue based on the characteristics of the Airbnb.
airbnb-price-changes-during-public-holidays
Team assignment for the Data Preparation & Workflow Management course, part of the Master degree in Marketing Analytics at Tilburg University. The scope of the assignment is to analyse whether Airbnb prices in Amsterdam, Paris and New York are influenced by 3 public holidays, among other variables.
covid19_on_length_of_stay-team1
This respository was made by Jonas Klein, Matthijs van Gils, Marijn Bransen and Dianne Burgess and was commissioned by Hannes Datta, proffesor at Tilburg University as part of the course 'Data Preparation and Workflow Management'.
Formula1-event-on-Airbnb-prices
This repository is created for the course Data Preparation and Workflow Management taught at the university of Tilburg. Our goal is to compare a city's availability on Airbnb during a Formula 1 event with a city that is comparable, but where no event is hosted. As for the scientific method, we are going to implement a quasi-experiment.
host-characteristics-on-airbnb-prices
This research is about the effect of different host characteristics on prices of Airbnb's. We will compare countries with high and low inflation in the last years to see whether there is a difference in the effect of host characteristics between these countries. We will also give a general impact of host characteristics on prices.
MovieGenre_IMDbAnalysis
This repository aims to shed a light on the effect of movie genre on its IMDb popularity score.
ratings_series_imdb
We investigate the average rating per season.
team9dPrep
team-project-team_9_group_project created by GitHub Classroom
The_impact_of_Airbnb_hosts_on_guest_reviews
Welcome to our repository dedicated to researching the impact of Airbnb hosts on guest reviews, using Inside Airbnb datasets.
what-influences-AirBnB-prices
Estimating the effect of Hawaiian AirBnB listing characteristics, the time until the booking starts (in days) and the season on the price per night.
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