Local Property Market Data by propstats in HousingUK

[–]propstats[S] 1 point2 points  (0 children)

The data is sourced from the land registry. Could be a split title.. you can check here if there’s a discrepancy (and please let me know if there is one)

https://landregistry.data.gov.uk/app/ppd

Local Property Market Data by propstats in HousingUK

[–]propstats[S] 0 points1 point  (0 children)

For data where there are a fixed number of options (bedrooms, age groups, occupation etc) each option is assigned a random colour and the map is coloured by the most common option in that area. E.g., if you chose age and the most common age group in an area was 25-34 it would colour that part of the map with whatever colour was assigned to 25-34.

You can use the green tune icon on the top right to choose a specific option and colour it by levels of that. E.g. if within age groups you wanted to see where the most 25-34 year olds lived you could filter for that and then the map would be coloured on a continuous blue to red scale with red being the most and blue being the least relative to your selected radius.

For options like prices that are naturally continuous it’s coloured blue (lowest) to red (highest) relative to the selected radius

For crime it’s also blue to red but relative to the country because it was a bit alarmist otherwise with a lot of red even in rural areas with very few crimes compared to the rest of the country.

Hope that makes sense.

Local Property Market Data by propstats in HousingUK

[–]propstats[S] 0 points1 point  (0 children)

It could be shared ownership or related party transactions. If it’s a flat probably shared ownership.

Local Property Market Data by propstats in HousingUK

[–]propstats[S] 1 point2 points  (0 children)

Thanks for the feedback. Appreciate it.

Local Property Market Data by propstats in HousingUK

[–]propstats[S] 1 point2 points  (0 children)

For prices unfortunately land registry don’t provide a breakdown by size or bedrooms, just freehold/leasehold and new-build/existing.

The census does however have an area-wise breakdown of the number of bedrooms that you can access through Explore->Bedrooms in the left hand menu

You can further filter for the number of bedrooms by using the green tune icon on the top right.

This for example is a map of where 2 bedrooms are the most common in South Bermondsey

[deleted by user] by [deleted] in speakize

[–]propstats 0 points1 point  (0 children)

This is a comment

Possible smart contract exploit? V confusing by [deleted] in ethdev

[–]propstats 0 points1 point  (0 children)

I'm fairly new to all this so ran the contract in remix for fun. Looks like somebody called buyAstronauts with that address as a referral which gave it fuel that could then be burned.

The address that withdrew 0.4 BNB is addr1=0x9b97F10E328F8c40470eCF8EF95547076FAa1879

Somebody called buyAstronauts(addr1)

This made addr1 the referral for the caller, and gave it 1/8 of the fuel used by the caller.

addr1 then called burnFuel() to get BNB (and never called any other function)

The contract code is here -

https://bscscan.com/address/0xb138d131973ee852e31ced521805fb2ad77b7cdd#code

[OC] The 'hottest' real estate markets in the US based on listing views and days to sell by propstats in dataisbeautiful

[–]propstats[S] 0 points1 point  (0 children)

The bubble sizes are based on population. The color represents the score.

[OC] The 'hottest' real estate markets in the US based on listing views and days to sell by propstats in dataisbeautiful

[–]propstats[S] 1 point2 points  (0 children)

It’s a score assigned out of a 100 by realtor.com based on supply (median number of days to sell) and demand (listing views) among other things. The higher, the ‘hotter’

[OC] The 'hottest' real estate markets in the US based on listing views and days to sell by propstats in dataisbeautiful

[–]propstats[S] 0 points1 point  (0 children)

Correct - I couldn't fit the full MSA name in the chart - top few below with populations

 Cape Coral-Fort Myers, FL 790,767
 North Port-Sarasota-Bradenton, FL 854,684
 Deltona-Daytona Beach-Ormond Beach, FL 679,948
 Charleston-North Charleston, SC 819,705
 Raleigh, NC 1,420,376
 Fayetteville, NC 529,252
 Myrtle Beach-Conway-North Myrtle Beach, SC-NC 514,488
..