TASK NO. 03: US HOUSING MARKET DYNAMICS
A home is usually the expensive purchase a person makes in one’s lifetime. Ensuring users have sufficient information about their interested market is paramount. Housing market refers to the type, cost, supply/demand of homes in a specific region. Housing markets usually experience substantial short-term price change momentum, supply/demand volatility due to various factors. Market dynamics can be analyzed using metrics & trends observed over time. Providing insights from market dynamics data aids buyers/sellers to make better & informed decisions.
Problem Statement:
● Analyze metrics at state & county level provide your insights in an hierarchical fashion.
● Analyze & infer trends, seasonality, cyclic nature of metrics provided.
Objectives:
● Extract provided data and if needed, transfer into any database of your choice.
● Provide insightful inferences which would be of interest for buyers/sellers.
● Build an interactive dashboard to visualize your findings/provided metrics using any language or tool, preferably as a web page. Eg: https://www.covid19india.org/
● Host your dashboard on any platform of your choice. Eg: Github pages
How to download the dataset?
Data: Observation of 91 metrics as either a rolling 1, 4 or 12-week window from Jan 2017 to Mar 2022 of all counties & metro regions in the US is provided.
Link: https://tinyurl.com/8hcw3s7b
How to run the file?
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Download the US_Housing_Market_Dynamics.ipynb file.
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Upload the tsv file and uncomment the second cell.
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Now run the whole file and download the final House_market_Dynamics.csv file.
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Next, download and run Dashboard.py file after uploading the above House_market_Dynamics.csv file.
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Finally, Click and follow the http link.