This the concern completing the portfolio project sas code
Data Analysis of New York City Airbnb Dataset
#Portfolio Milestone 1:
2. Which local neighbourhoods are the most loved by Airbnb guests?
For the analysis, a public database from the Airbnb platform was utilised. The dataset offers details on the characteristics of homes, review ratings, comments, and the availability of more than 10,000 listings in 2019. The Airbnb data was employed to execute visualisations, and SAS studio additionally carried out linear regression to identify the elements influencing higher ratings. SAS was also employed to analyse consumer reviews.
In this data set, there are a total 16 variables or columns which includes 11 numerical variables and 5 are character variables.
Data Description of Listings, Calendar, and Reviews
| Variable | Description |
| ID | Listing id of the property |
| Name | Name of the property |
| Host_Id | Id of the property host |
| host_name | Name of the host property |
| Price | Price of the property |
| availability_365 | Availability of property |
| Calculated_host_ _Listings_count | Total listings the host has |
| Neighbourhood group | Neighbourhood of the property |
| neighbourhood | Neighbourhood of the property |
| Min_nights | Minimum number of nights required to book |
| Reviews_per_month | Average Number of reviews in a month |
| room_type | Type of the room |
| number_of_reviews | Total number of reviews |
| last_review | Date of the last review |
| Latitude | Location of the Latitude |
| Longitude | Location of the Longitude |
Now, these variables 'id', 'host_name', 'last_review' are not needed to address the business problem because these drop variables are irrelevant and not significant to our investigation.
In this next part, we will use the SAS program for creating the filtered dataset.
Appendix 1: (SAS Code)
Guggilla, Chakraborty, P. Price Recommendation Engine for Airbnb. Support.sas.com. Retrieved from https://support.sas.com/resources/papers/proceedings17/1326-2017.pdf.
Kas, J., Delnoij, J., Corten, R., & Parigi, P. (2022). Trust spillovers in the sharing economy: Does international Airbnb experience foster cross‐national trust?. Journal Of Consumer Behaviour, 21(3), 509-522. https://doi.org/10.1002/cb.2014.
