At Rearc, we're passionate about telling stories with our data: exploring it to better understand the world around us and leveraging it to create innovative solutions to real-world problems.
With that in mind, we would like you to explore the dataset(s) provided and use your creativity to draw compelling insights from the data.
The goal of this quest is to showcase your data analytics skills. If you are an expert at extracting valuable insights from data, by all means do that. If you consider yourself a master designer of beautiful and informative visualizations, you may of course do that as well. If you are curious and like to ask questions / make predictions of data, then you may do that too.
This is intended to give you a platform to put your analytical expertise on display, so feel free to exercise creativity and do your thing!
- To download these files, copy/paste the link address into the address bar.
- Alternatively, pd.read_csv(url) should work just fine.
| File | Description |
|---|---|
| listings.csv.gz | Detailed Listings Data |
| calendar.csv.gz | Detailed Calendar Data |
| reviews.csv.gz | Detailed Review Data |
| listings.csv | Summary information and metrics for listings in San Francisco |
| reviews.csv | Summary Review data and Listing ID |
| neighborhoods.csv | Neighborhood list for geo filter. Sourced from city or open source GIS files. |
| neighbourhoods.geojson | GeoJSON file of neighborhoods of the city |
San Francisco is one of the most popular tourist destinations in the United States, attracting millions of visitors every year. Airbnb has become a popular choice for travelers seeking affordable and unique accommodations in the city. In this project we ask you to utilize the above tables to explore Airbnb rentals in San Francisco and attempt to answer the following questions:
- What factors are most strongly associated with the price of an Airbnb rental in San Francisco?
- What neighborhoods in San Francisco have the highest demand for Airbnb rentals?
- Can you identify any interesting trends or patterns in the demand for Airbnb rentals in San Francisco over time?
- Can you predict the occupancy rate and/or price of a given Airbnb listing in San Francisco based on its attributes and availability?
You may do some of these, you may do all of these; you may even branch off in additional directions that demonstrate your analytical reasoning and creativity.
You are free to use any data analytics tool such as Python, R, Excel, Tableau, or Power BI. Submit your analysis and outcome in a Jupyter notebook, RMarkdown, or other formats that you are comfortable with. Make sure we are able to view your results without requiring any proprietary software, complicated setup, or re-running your code.
We have many more for you to solve as a member of the Rearc team!
There is no fail. Complete whatever you can and then submit your work. Doing everything in the quest is not a guarantee that you will "pass" the quest, just like not doing something is not a guarantee you will "fail" the quest.
No. If you host your answers in version control such as Github, we ask that you please keep the repository private.