The objective was the highlight markets where mom and pop operators, i.e. small AirBnB’s, small rental portfolios, etc. were contributing a large share of all new single family homes coming onto the for sale, resale listing market.
Housing dynamics are complex. There are tiers of actors ranging from the large institutions like Blackstone, to owner occupied units. The motivations differ for each set of these actors. Understanding how they contribute to sales, and resale activity is important however visualizing it in a succinct way is an active area of research.
IMO, housing analytics needs substantial love. Would welcome feedback on the visual and ideas for providing more transparency into housing analytics in general.
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Tools used: Python & D3
Data: Parcl Labs
The objective was the highlight markets where mom and pop operators, i.e. small AirBnB’s, small rental portfolios, etc. were contributing a large share of all new single family homes coming onto the for sale, resale listing market.
Housing dynamics are complex. There are tiers of actors ranging from the large institutions like Blackstone, to owner occupied units. The motivations differ for each set of these actors. Understanding how they contribute to sales, and resale activity is important however visualizing it in a succinct way is an active area of research.
IMO, housing analytics needs substantial love. Would welcome feedback on the visual and ideas for providing more transparency into housing analytics in general.