Challenges and expectations of foreign assignment writing, AirBnB & Zillow data analysis
Before starting this challenge, please keep in mind our basic requirements for players:
? Creative thinking: find the most efficient way to deal with it; be sure to use automated and efficient methods to replace tedious and repetitive work.
? Data Analysis Thinking: To fully understand the data we are about to process, to find the best entry point.
? Business acumen: How to explain your project is as important as others, whether you can let others understand your project determines the success of your project.
Problem Description and Guidelines
Problem Statement
Now there is a company in New York that wants to buy properties to offer short-term rentals to clients, and the company has come to a conclusion that two-bedroom properties are the most profitable, but the company doesn't yet know which area (zip code) is the best place to invest. Now that you're a new data analyst at the company, all you need to do now is run a data analysis and find out which zip code is in the area that generates the most profit.
In the Zip_Zhvi_2bedroom.csv data file, Zillow provides us with historical data on the median property value in different zip codes around the world (from which we should be able to roughly estimate the cost of the company's purchase of property in an area).
And AirBnB is one of the most popular home rental agency websites that investors use today. From the data provided by AirBnB, we can see the rental situation in different areas of New York City. ? You can assume an occupancy rate of 75% or you can come up with
your own model to calculate occupancy; just let us know how you came to that calculation
At the same time, the company leaders told you that the company currently has the following assumptions:
1. The company will pay in full when purchasing the property (so there will be no interest, no other additional fees, etc.)
2. The value of money varies with Changes in time will not change (for example, 1 yuan 100 years ago is still 1 yuan today)
3. In the same area (zip code), the cost and benefit per square foot are the same. That is, if in Manhattan, 1,000 square feet is twice as good as 500 square feet, and 1,000 square feet costs twice as much as 500 square feet.
4. For Zillow's data, although Zillow gives us the average value of two-bedroom houses in various places every year, and does not give the area of the house, we can know the average value of two-bedroom houses in NYC through data query. The area is 1000 square feet.
5. Company Assumptions
guide
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When you get the data, the first thing you need to realize is that it's a real-world flawed data, so we think you'll need roughly three hours to complete this data analysis challenge. If you are not sure about certain issues, you can also make your own assumptions, but make sure that your assumptions make sense. At the same time, be sure to use a document to document your assumptions.
In general, we hope that you can complete this data analysis job in the following three areas:
1. Data cleaning
? Inaccurate data is worse than no data
? Clean data that you consider unimportant or bad and create a new database
2. Data analysis ?
Use your data analysis skills to find out what factors are important to the final result Tools needed for visualization : R (packages that may be used: Shiny, plyr, ggplot) http://www.daixie0.com/contents/18/1296.html