This is my journaling process for a full project on Tableau.
I first started by using Airbnb data for Seattle. The Dataset was acquired here: http://insideairbnb.com/get-the-data/
Kaggle also has a copy that can be used here: https://www.kaggle.com/datasets/alexanderfreberg/airbnb-listings-2016-dataset
The first step is to create a data connection using the acquired .xslx file
I first create the joins. I make sure to match the IDs for the Calendar & Reviews Tables
I double check the number of rows so that they don’t change dramatically from when I checked the .xlsx file on Excel.
For Tableau public, it was only possible to use less than 15,000,000 rows of data. Tableau promps a filter to grab less data. Due to this limitation, for this project, only the joining of Listings + Calendar will used.
For a use case, a good scenario would be to determine the factors that would be important when chosing a good option for a airbnb. For this purpose, I decide to check the Average Price for Zipcode using a simple columns & rows comparison
The results can be visualized by area with labelling per Zipcode and Average Price per Bedroom:
For the next example, there’s a huge drop in price for no apparent reason. The data for the next value doesn’t translate into a good visualization. A way to fix this is to apply a filter:
For this sheet, it’s possible to indicate that the highest prices for renting an airbnb is by showing the data numbers, that spike in Summer and by the End of the Year
For the fourth sheet, when looking at the price related to the no. of bedrooms;