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refreshing_username t1_ivvac4d wrote

I'm struggling to get anything from this. Looks like median days on market moved up or down largely independent of location? Or is there another point I'm missing?

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boganvegan t1_ivvxeul wrote

If the median days on market increased by 24 days during a 30 day month that implies that sales have fallen off a cliff.

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michigician OP t1_ivw67b4 wrote

That would be a percent increase.

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40for60 t1_ivyhb57 wrote

Percent of what? If it was 1 hour and it went up 24% now its 1 hour 15 min?

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michigician OP t1_ivykw9j wrote

Days. Each home listed for sale has been on the market for a certain number of days. The data for all listings in a county has been used to calculate a median number of days on market for each county. This statistic is reported each month by realtor.com. This map shows the change in that statistic from September to October.

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michigician OP t1_ivvfhqb wrote

Each county is calculated seperately.

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refreshing_username t1_ivvisf5 wrote

I get that. I just cant see any pattern. It just lookes like static.

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michigician OP t1_ivw5rvl wrote

Some of it is noise. You have to look for patterns, out west, in the north, in rural areas. But you are right, a lot of it is random.

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shark_snak t1_ivvq6y6 wrote

A single color gradient would be better

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N3TMelc t1_ivvtn0f wrote

What is this scale? It looks like it's made so that each color has the same proportions of counties, but why would anyone decide to present it like this? You lose all nuance in the negative changes and it makes the visualization useless. The only thing I can gather from this is some counties went up, some went down.

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michigician OP t1_ivv7ck6 wrote

Blue means houses are selling more quickly than last month, red means houses are sitting around not being sold longer than last month.

It could be caused by seasonal changes, but in many cases, it is due to the higher cost of financing a home purchase, and prices which are too high for buyers.

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Liesthroughisteeth t1_ivvdlup wrote

It's seasonal in part for sure coming up on the winter months, generally it slows down some with people much less inclined to be disturbed by showings and the prospect of moving a household in the middle of winter.

However the economy isn't getting any better. Major corporations are laying people off, consumer confidence is taking a hit and corporations are sidelining any capital expenditures and expansion as the cost of borrowing goes up. This is what happens (as it is intended to) when interest rates go up to combat inflation.

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boganvegan t1_ivvwxts wrote

West Central Florida's red zone coincides with the area damaged by Hurricane Ian.

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[deleted] t1_ivvqod9 wrote

Seem like a lot of noise and not much signal.

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wnaj_ t1_ivxkwcd wrote

What is this map supposed to tell me?

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michigician OP t1_ivxuypm wrote

Regions which have a lot of red counties are in a slowdown of demand, regions with blue counties saw an increase in demand, regions with a mix of colors are not seeing much change. The differences between individual counties are not that significant because local housing markets are varied and unique.

One thing you could take away is that there is no national housing crash, as some have predicted. There are some regions where demand has dropped from last month.

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wnaj_ t1_ivxvc1g wrote

Great, so the conclusion is that this map tells me nothing, so why did you make it?

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michigician OP t1_ivxw5h8 wrote

Some people are able to see valuable information in it.

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wnaj_ t1_ivxxe6i wrote

How? Unless you know every single county thats on this map there is no use for it as it shows no pattern

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CommunicationShot946 t1_ivxs1nj wrote

i think this is quite cool actually — begs the question why? Why are neighboring counties seeing such a big difference. I think what others are pointing out is that could be caused by a ton of different variables (my guess is average home price would be a big cause) so adding another layer somehow might be cool.

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data-curious-2k t1_iw79x8e wrote

Nice and informative, but i do have one quibble. In your scale, green straddles negative and positive values. You should break it into 2 ranges, namely the negative one up to but not including zero, and zero to the positive value. I presume what you show is due to some natural breaks in the data. But it should also be about what the data mean.

Also a time lapse movie going back as many months as you can gather would be nice. :-P

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johnscura t1_iwcennx wrote

In this case a black and white scale would give more information than using colors. Or just any single color using shade/intensity.

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