Yesterday, I created a visualization that looked at areas that could possibly be exposed to hurricane force winds. I took it down because I was concerned some typos were causing issues with understanding it. Here is an updated visual with incorporation of some of the feedback I got.
To create this data visualization, I gathered shape file data to see what areas had any probability of seeing hurricane force winds from the [National Hurricane Center](https://www.nhc.noaa.gov/). I then overlayed that data with the census tract boundries from the U.S. Census Bureau and joined the [Community Resilience Estimates](https://www.census.gov/programs-surveys/community-resilience-estimates.html) to see which areas are social vulnerable to disasters. I used python (geopandas and pandas) to do the data work and Tableau to visualize the map.
The Components of Social Vulnerability the Community Resilience Estimates look at are:
1. Income-to-Poverty Ratio (IPR) < 130 percent (Household)
2. Single or zero caregiver household – only one or no individuals living in the household who are 18-64 years old (Household)
3. Unit-level crowding with > 0.75 persons per room (Household)
4. Communication Barrier (Household) defined as either:
1. No one in the household speaks English “very well” or
2. No one in the household has a high school diploma
5. No one in the household is employed full-time, year-round – excludes households where all individuals are aged 65 years or older (Household)
6. Disability, at least one serious constraint to significant life activity (Individual)
7. No health insurance coverage (Individual)
8. Aged 65 years or older (Individual)
9. No vehicle access (Household)
10. Households without broadband internet access (Household)
The percentage of the population with three of more of these components are what is considered high risk.
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Yesterday, I created a visualization that looked at areas that could possibly be exposed to hurricane force winds. I took it down because I was concerned some typos were causing issues with understanding it. Here is an updated visual with incorporation of some of the feedback I got.
To create this data visualization, I gathered shape file data to see what areas had any probability of seeing hurricane force winds from the [National Hurricane Center](https://www.nhc.noaa.gov/). I then overlayed that data with the census tract boundries from the U.S. Census Bureau and joined the [Community Resilience Estimates](https://www.census.gov/programs-surveys/community-resilience-estimates.html) to see which areas are social vulnerable to disasters. I used python (geopandas and pandas) to do the data work and Tableau to visualize the map.
The Components of Social Vulnerability the Community Resilience Estimates look at are:
1. Income-to-Poverty Ratio (IPR) < 130 percent (Household)
2. Single or zero caregiver household – only one or no individuals living in the household who are 18-64 years old (Household)
3. Unit-level crowding with > 0.75 persons per room (Household)
4. Communication Barrier (Household) defined as either:
1. No one in the household speaks English “very well” or
2. No one in the household has a high school diploma
5. No one in the household is employed full-time, year-round – excludes households where all individuals are aged 65 years or older (Household)
6. Disability, at least one serious constraint to significant life activity (Individual)
7. No health insurance coverage (Individual)
8. Aged 65 years or older (Individual)
9. No vehicle access (Household)
10. Households without broadband internet access (Household)
The percentage of the population with three of more of these components are what is considered high risk.