MongoDB_Weekly_Challenge_2019

This repo is created to record answers I submitted for Eliot's Weekly MongoDB World Challenge 2019

The Charts Challenge with AirBNB Data

Problem Summary:

We’re planning a trip for all the MongoDB Engineers and we want to make sure that they visit and stay in the most popular destination spots in the world. We’re very particular about the accommodations we arrange for our Engineers. So we’re hoping you’ll help us sort out all of the details we need in order to plan their trip. To do this, you’ll use the sample AirBNB dataset available right inside your MongoDB Atlas cluster.

Sample AirBNB dataset

The questions below will present a scenario which requires analysis. Create a separate chart to answer each of the questions below. To submit your solution for the challenge, you will need to embed each of the charts into a web page and provide the URL to this page as your answer. This page should be internet accessible so that our judges can review your solution.

1. Remember we want our Engineers to stay in the most popular, populated market. To that end, use MongoDB Charts to analyze the data to determine which market (address.market field) has the largest number of properties listed in the sample dataset. Create a chart showing your analysis and provide a link to this chart using the embed code feature of Charts.

2. MongoDB Engineers typically like to stay in either Tree Houses or Castles. On average, does it cost more to stay in a treehouse or a castle? To solve this, you will probably want to use the mean value of the property_type and price fields in you chart.

3. We also like to ensure that our Engineers stay where they have the most amenities. In which market (address.market field) do properties have the highest average number of amenities (amenities)?

4. Of the properties with at least one review (number_of_reviews), what month and year had the highest number of first reviews (first_review field)?

5. We have a lot of Engineers these days and we want to try to get them all in the same home. Help us out and find out what is the maximum number of bedrooms (bedrooms field) of any property in the dataset?

6. Please enter the URL to the HTML page you created with the embedded charts that answer the questions above.

My Submission:

MongoDB Charts built for problem 1 through 5: