Our goal for the Yelp Data Project was to transform the Yelp data set and turn it into usable visuals for perspective business owners. Through our visualization, we hope to provide prospective business owners with more insight on how they should operate their business in terms of selecting a specific location or selecting a price range that is competitive in the region. We provided several graphs to illustrate and answer our problem set. With Yelp and digital marketing becoming more and more important, it can be important for new business owners to pay attention to what data Yelp collects. We hope to provide a tool and resource for these business owners to be more competitive.
- Learn about the average price range of restaurants
- Understand where the highest rated restaurants are in the region
- See the impact of check-ins and reviews
Since the original Yelp Data Set consists of data in the continental United States, we felt that our report would be more beneficial if we partition it to a specific city. We decided to use the vibrant city of Las Vegas, NV, which is home to a number of top restaurants and business. We focused on data on the cities of Las Vegas, North Las Vegas, and Henderson.
For this report, we utilized tools like "Dplyr", "Plotly", "GGPlot2", and "Shiny". Dplyr was used primarily for data wrangling and sectioning off the data to specific parts that we focused on. Plotly and GGPLot2 were used in creating interactive visualizations such as the map and the graphs. This tool allowed us to transform the data that we wrangled with in Dplyr to a visual. Finally, we used the Shiny tool to create customized inputs, so that the visuals were customized to the reader's needs.
Some of the challenges we faced:
- Using the data-set from Yelp that was originally a .json file
- Seeing that the Las Vegas region had three different cities, so we had to include all three cities when data wrangling
- Having trouble decide what insights to get from such a large, broad data-set.