These Kaggle datasets provide downloaded real-estate listings from the UK real estate market, capturing data from a leading platform in the UK (Zoopla), reminiscent of the approach taken for the US dataset from Redfin and French dataset from Seloger. It encompasses detailed property listings, pricing, and market trends across UK, stored in weekly CSV snapshots. The cleaned and merged version of all the snapshots is named as UK_clean_unique.csv.

The cleaning process mirrored that of the US and French datasets, involving removing irrelevant features, normalizing variable names for dataset consistency with the USA and France, and adjusting variable value ranges to get rid of extreme outliers. To augment the dataset's depth, external factors like inflation rates, stock market volatility, and macroeconomic indicators have been integrated, offering a multifaceted perspective on the UK's real estate market drivers.

For exact column descriptions, see columns for UK_clean_unique.csv and my thesis.

Table 2.6 and Section 2.2.2, which I refer to in the column descriptions, can be found in my thesis; see University Library. Click on Online Access->Hlavni prace.

If you want to continue generating datasets yourself, see my [Github Repository] (https://github.com/ArturDragunov/Master_Thesis/tree/main) for code inspiration.

Let me know if you want to see how I got from raw data to France_clean_unique.csv. There are multiple steps, including cleaning Tableau Prep and R, downloading and merging external variables to the dataset, removing duplicates, and renaming some columns.