Final-Project-Tableau

Project/Goals

The project was to demonstrate visualization techniques with Tableau and show any trends with a data source provided. The goal is to turn data comparisons into bars, charts, maps, and plots that are easy to present for the general audience to understand a business objective.

Process

1. I have chosen Option 2. (III) AIRBNB because it reminded me of my vacation in New York during the summer of 2015. I stayed at 'The Affinity', a hotel that is in the heart of Manhattan, New York, across from The Madison Square Garden and travel was accessible at Penn Station. I did not recall hearing about Airbnb at that time, so I thought that it would be interesting what I could discover with the Airbnb dataset and perhaps why was it so popular with users through social media and word of mouth.
2. The 'airbnb.xlsx' file was uploaded to the 'Data Source' in Tableau.
3. The data was analyzed between measures (e.g., zipcodes, neighborhood, property types, and room types) versus dimensions (e.g., number of beds, prices, number of reviews, and review ratings).
4. A map was created to categorize the five (5) boroughs of New York by color - Manhattan, Brooklyn, Queens, Bronx, and Staten Island.
5. A pie chart was created to show the percentage of listings between the boroughs of New York.
6. A bar graph was created to show the total different types of rooms whether private, shared, or fully occupied.
7. Another bar graph was created to show the average price between number of beds.
8. A line graph was charted to show the review ratings over the time of listings were hosted.
9. Another line graph was charted to show the number of listings over the time of listings hosted.
10. A scatterplot was created to show an array of plots between the number of reviews and review ratings.
11. A cluster was analyzed to see if there were any notable categories between numericals - number of beds, price of listings, number of reviews, and review ratings.
12. A box plot was create to detect any outliers.

Results

• Between the 5 boroughs of New York City, Manhattan and Brooklyn have substantially more Airbnb listings Queens, Bronx, and Staten Island, which dominate with over 80% of the total share.
• It is cheaper staying at Airbnb than hotels. Visitors have more choices with prices, locations, spaces, and types of properties.
• Apartments are the most abundent type of property in New York City to be listed given the urban city design and level of crowdedness. Plus, Airbnb empowers owners and tenants, depending on the demographic and standards of living, to have financial flexibility and freedom to live at different locations.
• There are a couple of outliers notably between the type of property and price. For example, there is a 2-bed listed for $10,000. Data validation may be needed to confirm the type of property and price.
• This is the most interesting result that I have encounted. In the line graph, the number of Airbnb listings sharply declined in 2014. Having sought external online resources, it is discovered that Airbnb was in a legal dispute with the state of New York because it was illegal to have short-term rentals for less than 30 days:
  • The huge influx of Airbnb listings led to the review of Airbnb's business records showing over third-quarters of bookings have broken the state's laws.
  • Taxes were avoided to be paid like hotels.
  • Often, owners are not present with the occupier(s).
  • Unregulated safety concerns with respect to fire evacuation protocol and sprinkler systems.
  • Airbnb listings were converted into "illegal" hotel rooms that takes real estate off the market for private gain.
  • It was consequential to housing shortages and housing affordability in New York City.

Challenges

• Difficult to plot variables between x-axis and y-axis to make direct quality comparisons.
• Properly apply enhancements, such as colours, tables, and filters, to convey message visually to the general audience.
• Brainstorm and follow with a story to capture the attention of the general audience.
• Tableau is different from SQL and Python. Programming languages have orders and structures. Tableau requires user interaction, such as "drag-and-drop" windows and application of visual layouts.

Future Goals

• As the dataset is up to 2015, I hope to find a dataset that can be merged with the existing Excel file to see if any trends have updated recently.
• Work on advanced Tableau skills, such as timing with animations.
• Look over dataset between Airbnb and hotels to point out distinct comparisons in my message.