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DAA Internship Introduction

Purpose:

The goal is to give you (DAA students) a chance to have a “data” position on your LinkedIn & resume. That way you now have data experience - no matter your background

Who can participate?

Anyone can participate in the internship at any time! Whether you’re brand new, or been in the program for awhile, you are welcome.

Of course, you might be less useful than you’d like if you’re new, but you’re welcome to try!

How often do we do them? We are testing out every quarter right now. It feels like often enough to make it available to everyone, but not every month where we all get burnt out

Can it be my capstone project? Absolutely! That’s a great idea. Do it.

Do I work in teams or by myself? We prefer you work in teams (that’s often how real data analysis happens), but if you want to be a lone-wolf, go ahead and do that too!

What should I be doing? When should I be doing it? We’ve given you a list of some tasks to complete, but these internships are intentionally left a little vague for you to learn and grow. You and your team can decide when you meet, how often, and what tasks each individual should do.

What do we do with the data you analyze? We try to use it in our content (YouTube, LinkedIn, etc). We will try to tag you when we do :)

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Timeline

📅 Start: January 21st

⏳ Mid-Way Check In: February 4th

✅  Submit Work: February 18th

🏁 Finish Feedback: March 4th

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Download the Data

properties_main.csv

price_history.csv

All data from:

https://www.kaggle.com/datasets/isaacoresanya/uk-property-prices-with-sale-history

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Feel free to use this Google Meet link to talk: https://meet.google.com/uhg-dwvv-oqx

Analysis To Do:

Things to Explore:

  1. Price change between sales

    Show the median percent change between consecutive sales.

    Break it down by property type and postcode area, one metric per cell.

  2. Typical time between sales

    Show the median time to the next recorded sale, in years.

    Break it down by property type and postcode area.

  3. Quick resales

    Show the share of properties that have at least one resale within 2 years, and within 5 years.

    For each resale window, also show the median percent gain for those quick resale events only.

  4. Fastest growing postcode areas over the last decade

    Rank postcode areas by median sale price in 2013 vs 2023.

    Show median price in 2013, median price in 2023, percent change, and number of sales used in each year.

  5. New build premium, like for like

    For each postcode area and year, compare the median sale price for new build vs not new build.

  6. Price ladder by property type in one area

    Pick one postcode area and one year.

    Show median sale price for Flat, Terraced, Semi detached, Detached.

  7. Leasehold vs freehold

    For each postcode area, compare median sale price across Leasehold and Freehold.

  8. Biggest winners and losers, first to last recorded sale

    Find properties with at least 2 recorded sales.

    Pick the 10 largest percent gains and 10 largest percent drops from first recorded sale to last recorded sale.

    Add a short note for each including years held (recorded), number of recorded sales, property type, and postcode area.

    Flag any properties affected by questionable prices or extreme outliers.

  9. Price paths in shock years

    Focus on 2008 and 2020.

    Pick a few postcode areas with high sales volume.

    For each area, show the median sale price in the year before, the shock year, and the year after.

    Then show percent change from year before to year after.

Deliverables

We want insights we can use in a YouTube video or a newsletter.