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Analyzed FEMA and Zillow data using Python to get insights on how natural disasters affect home prices.

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FEMA_Analytics

This project was created by 4 team members to analyse and co-relate data from Federal Emergency Management Agency(FEMA) and Median House Prices from Zillow.

Team 5 Project Plan:

  1. Data Set: a. FEMA - https://www.fema.gov/openfema-dataset-openfema-data-sets-v1 b. Zillow API: http://www.zillow.com/webservice/GetRegionChildren

  2. Exploratory Analysis:

    FEMA Disaster regions

    FEMA Cost per disaster

    FEMA Budget per disaster

    FEMA After-effects of disaster

    Zillow House Prices By County

  3. Analysis Results: For Analysis purpose, FEMA and Zillow data was compared between the state of Texas. As per the comparision, it was found that few counties did show direct corelation between the number of disasters and house prices. However, the pattern was not consistent which indicates there were other factors affecting the house prices.

Texas Disaster by County

Texas Median House by County

MAP

Comparing Payouts by Disaster

Boxplot of Average Payout by State

Other Charts of Disasters

Folders:

  1. Final_Data - contains the data files to be used for analysis
  2. Archive - contains redundant files
  3. Final Presentation - contains .ppt presentation of the project
  4. Output_Visual - contains out put of all visuals created.

Git Commands to Push Changes:

  1. git add -A
  2. git commit -m "COMMENT WHAT CHANGES INCLUDED"
  3. git push

Additional GIT Commands:

  1. git pull origin master #pulls changed files from master
  2. git checkout -t origin/branch-name #switch to a new branch
  3. git push origin branch-name #push changes to the branch

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Analyzed FEMA and Zillow data using Python to get insights on how natural disasters affect home prices.

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