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First Project - Data Analysis

This project is centered around exploratory data analysis techniques and presentation of results to a stakeholder.

Once you start working please follow the workflow to help you achieve the tasks successfully!

The data

  • You will use the King County Housing Data: This dataset contains information about home sales in King County (USA).

  • The dataset will be provide, please copy it in the data folder where it will not be uploaded to github.

  • The description of the column names can be found in the column_names.md file.

  • The column names may NOT be clear at times:

    In the real world we will run into similar challenges. We would then go ask our business stakeholders for more information. In this case, let us assume our business stakeholder who would give us information, left the company. Meaning we would have to identify and look up what each column names might actually mean. (google is your friend ;) )

The Tasks

  1. Create a new repo using this template.

  2. Through EDA/statistical analysis above please come up with AT LEAST 3 insights regarding the overall data. One should be geographical.

  3. In addition also come up with AT LEAST 3 recommendations for your stakeholder.

Note, you can take either the perspective of a buyer or a seller. Choose a stakeholder from the list at the end of this file.

The Deliverables

  1. New repository from template
  2. A well documented Jupyter Notebook (see here for an example) containing the code you've written for this project and comments explaining it. This work will need to be pushed to your GitHub repository in order to submit your project. Do not push all the analysis... just the analysis that is relevant! You can start with the starter notebook.
  3. An updated and organized README.md file in the GitHub repository that describes the contents of the repository. This file should be the source of information for navigating through the repository.
  4. A short Keynote/PowerPoint/Google Slides/Jupyter slides presentation giving a high-level overview of your methodology and recommendations for non-technical stakeholders. The duration of the presentation should be 10 minutes, then the discussion will continue for 5 minutes. Also put your slides (delivered as a PDF export) on Github to get a well-rounded project. Do not present using your jupyter notebook!
  5. Optional - A Python script for processing and cleaning your data, here feel free to write clean code, using functions and docstrings. Even more optional you can also do unit tests. If you do this part, you may also update your EDA notebook to make use of these functions. See (optional)[optional] folder for example.

The Stakeholders

  • Please chose a stakeholder.

Note: As these stakeholders are made up (any resemblance to present people is absolutely random), please make assumptions about answers they would give to your questions. (i.e. How do you define a rich neighborhood? take the zipcodes with most houses in upper 10% percentile..). Whatever assumptions you make, please write them explicitly in your presentation and notebook.

Name Stakeholder Characteristics
Thomas Hansen Buyer 5 kids, no money, wants nice (social) neighborhood, Timing?, Location?
Charles Christensen Seller Invest with big returns, wondering about renovation?, which Neighborhood? Timing?
Bonnie Brown Seller Has house and wants to move soon (timing?), but wants high profit in middle class NH (neighborhood)
Larry Sanders Buyer Waterfront , limited budget, nice & isolated but central neighborhood without kids (but got some of his own, just doesn't his kids to play with other kids .. because of germs)
Nicole Johnson Buyer Lively, central neighborhood, middle price range, right timing (within a year)
Jennifer Montgomery Buyer High budget, wants to show off, timing within a month, waterfront, renovated, high grades year
Bonnie Williams Seller Has several houses, some in bad neighborhoods, willing to evict people, timing?, big returns, open for renovations
William Rodriguez Buyer 2 people, country (best timing & non-renovated) & city house (fast & central location), wants two houses
Erin Robinson Buyer Invest in poor neighborhood, buying & selling, costs back + little profit, socially responsible
Jacob Phillips Buyer Unlimited Budget, 4+ bathrooms or smaller house nearby, big lot (tennis court & pool), golf, historic, no waterfront
Zachary Brooks Seller Invests in historical houses, best neighborhoods, high profits, best timing within a year, should renovate?
Timothy Stevens Seller Owns expensive houses in the center, needs to get rid, best timing within a year, open for renovation when profits rise
Amy Williams Seller Italian mafiosi, sells several central houses(top10%) over time, needs average outskirt houses over time to hide from the FBI