Embedded Files
Preface
Preface
The subset of visualizations that are going to be discussed come from a larger set of visualizations about the city of Pittsburgh and the state of Pennsylvania. The data and visualizations include information about diversity, COVID-19, the economy, civics, education, housing and living, and health.
Link to the Visualization:
Introduction to the Visualizations
Introduction to the Visualizations
The purpose of the COVID-19 visualization is to show:
Daily new cases
Overall confirmed cases
Confirmed cases per capita
Total Deaths
Deaths per capita
Total tests
Total hospitalization
All of these visualizations are by date on the x-axis. The above parameters are on the y-axis. After selecting a parameter, the visualization compares Pennsylvania data with states that have similar numbers as well as the United States as a whole.
The purpose of the Health Care Coverage visualization is to show the percentage of the Pittsburgh population that is covered by some form of health care between the years 2013 to 2019. The line graph format allows the viewer to see the trend of health care coverage over time. The different types of health care coverages, or lack thereof, are:
Employer
Medicaid
Medicare
Military or VA
Non-Group
Uninsured
The purpose of the Health Risks visualization is to show some of the more prevalent health risks and how much they affect particular counties in Pennsylvania from 2014 to 2021. The health risks that are included are:
Diabetes
Adult Obesity
HIV Diagnosis
STIs
Adult Smoking
Alcohol-Impaired Driving Deaths
Motor Vehicle Crash Deaths
Homicides
Violent Crime
Who were these visualizations made for?
The website from which I obtained the above visualizations does not explicitly say who they were made for. However, one could make the assumption that it was created for anyone with an interest in Pittsburgh and Pennsylvania and how their statistics stack up against the rest of the country. More specifically, it seems to be meant for anyone with an interest in the Diversity, COVID-19, Economy, Civics, Education, Housing and Living, and Health statistics in Pittsburgh and Pennsylvania.
Data Information
Data Information
The COVID-19 visualization was created by a dataset that includes the following columns:
Geography
Date
Confirmed growth
Daily deaths
Daily hospitalizations
Daily tests
Confirmed
Deaths
PositivePct
ConfirmedPc
DailyDeathsPC
DeathsPC
DailyTestsPC
TestsPC
DailyHospitalizedPC
HospitalizedPC
ConfirmedGrowthPC
ConfirmedSmooth
ConfirmedPCSmooth
DailyDeathsSmooth
DailyDeathsPCSmooth
DeathsSmooth
DeathsPCSmooth
DailyTestsSmooth
DailyTestsPCSmooth
TestsSmooth
TestsPCSmooth
DailyHospitalizedSmooth
DailyHospitalizedPCSmooth
HospitalizedPCSmooth
HospitalizedSmooth
ConfirmedGrowthSmooth
ConfirmedGrowthPCSmooth
Timestamp
This data was obtained from the COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (https://github.com/CSSEGISandData/COVID-19/tree/master/csse_covid_19_data/csse_covid_19_time_series) and CCSE Covid 19 Time Series (https://github.com/CSSEGISandData/COVID-19).
Note: The dataset is too large to capture all of the rows and columns. Click this link and select "View Data" to see the entire table: https://datausa.io/profile/geo/pittsburgh-pa#covid-cases.
The Health Care Coverage visualization was created by a dataset that includes the following columns:
Year
Geography
Kaiser Coverage
Health Insurance Policies
Share
The data was obtained from the American Community Survey (ACS) (https://www.census.gov/programs-surveys/acs/).
Note: The dataset is too large to capture all of the rows. Click this link, scroll down to "Health Care Coverage", and select "View Data" to see the entire table: https://datausa.io/profile/geo/pittsburgh-pa#health.
The Health Risk visualization is being created by different datasets depending on the health risk that is chosen. The columns that they all have in common are Year and Geography. The third column in each dataset depends on which health risk the viewer wants to see (ex if the viewer wants to see Diabetes, there is a Diabetes column). The data was obtained from the County Health Ranking & Roadmaps (http://www.countyhealthrankings.org/).
Note: There are multiple datasets that make up this visualization. Click this link, scroll down to "Health Risks", and select "View Data" to view all of the tables: https://datausa.io/profile/geo/pittsburgh-pa#health.
Questions & Answers
Questions & Answers
How many confirmed cases per capita of COVID-19 are in the state of Pennsylvania?
The user needs to use the dropdown bar titled Y-AXIS and select Confirmed Cases per Capita. From there, they can hover over the orange line and look at the specific numbers for a particular date as well as the trend of the data throughout the months.
How many confirmed COVID-19 deaths are in the state of Pennsylvania?
The user needs to use the dropdown bar titled Y-AXIS and select Deaths. From there, they can hover over the orange line and look at the specific numbers for a particular date as well as the trend of the data throughout the months.
How many confirmed COVID-19 deaths per capita are in the state of Pennsylvania?
The user needs to use the dropdown bar titled Y-AXIS and select Deaths per Capita. From there, they can hover over the orange line and look at the specific numbers for a particular date as well as the trend of the data throughout the months.
How many COVID-19 tests have been administered in the state of Pennsylvania?
The user needs to use the dropdown bar titled Y-AXIS and select Tests. From there, they can hover over the orange line and look at the specific numbers for a particular date as well as the trend of the data throughout the months.
How many COVID-19 hospitalizations have occurred in the state of Pennsylvania?
The user needs to use the dropdown bar titled Y-AXIS and select Hospitalizations. From there, they can hover over the orange line and look at the specific numbers for a particular date as well as the trend of the data throughout the months.
How do each of the above metrics compare with states with similar numbers as well as the United States as a whole?
The user can hover over the orange line to get the data for Pennsylvania on a particular day. Then, they can hover over any other line that either has different states or the United States data on that same day and compare the numbers. The visualization also offers an easy way to compare trends and overall numbers because all the lines are on the same graph with the same scale.
What percentage of people in Pittsburgh are covered by their employer in year X?
The user can hover over the line that gives information for Employer Coverage and slide their cursor over the year of interest.
What percentage of people in Pittsburgh are covered by Medicaid in year X?
The user can hover over the line that gives information for Medicaid and slide their cursor over the year of interest.
What percentage of people in Pittsburgh are covered by Medicare in year X?
The user can hover over the line that gives information for Medicare and slide their cursor over the year of interest.
What percentage of people in Pittsburgh are non-group covered in year X?
The user can hover over the line that gives information for Non-Group and slide their cursor over the year of interest.
What percentage of people in Pittsburgh are covered by the Military or VA in year X?
The user can hover over the line that gives information for Military or VA coverage and slide their cursor over the year of interest.
What percentage of people in Pittsburgh are uninsured in year X?
The user can hover over the line that gives information for people who are uninsured and slide their cursor over the year of interest.
What percentage of Pennsylvanians in county X are afflicted with disease Y during year Z?
The user needs to use the dropdown bar and select the disease of their choosing (options listed in the Purpose tab). On the bottom of the map, below the legend, the user can select the year of interest. Then, they can hover over the county of interest.
How many people in Pennsylvania have been affected by crime X during year Y?
The user needs to use the dropdown bar and select the crime of their choosing (options listed in the Purpose tab). On the bottom of the map, below the legend, the user can select the year of interest. Then, they can hover over the county of interest.
Feedback
Feedback
What needs improvement?
1. When taking an in-depth look into the COVID-19 line graph, I noticed that the Tests by Date graph is not plotted correctly. However, if the user hovers over the line, the numbers are there. Looks like they need to fix the scaling on the y-axis.
2. The COVID-19 visualization compares the Pennsylvania numbers with the other states that have similar numbers. What might be more helpful is to show the states with the highest and lowest numbers as a way to see where Pennsylvania fits in.
3. Some visualizations might be tackling too much. For instance, the Health Care Coverage visualization. The most helpful thing the user can gain from looking at it, is a sense of what percentage of the population is covered -- or not, for the uninsured -- by what entity.
The graph is doing that, but it is also trying to provide one additional piece of information -- trends over time, hence the line graph format.
I would argue that providing that piece of information is not too helpful, especially since the fluctuations are small. A better way to visualize this would be through a pie chart. This is because it is percentage based to 100. This way, the user gets a clear picture of the percentage of the population that were covered by their company, Medicare, etc.
What works?
1. The Health Risks visualization was executed really well. Initially, the map is placed directly on Pennsylvania with each of the counties clearly carved out. If the user hovers over any of the counties, they will learn the name of the county, the year that is being represented, and the value of the health risk. There is a legend that gets darker the higher the numbers go, so it is easy to see at first glance which counties have the highest risk. There is an option to zoom in on the map, zoom out on the map, and get back to the center. Lastly, there is an easy dropdown bar to select which health risk to examine.
2. In the COVID-19 and Health Care Coverage visualizations, if the user is only interested in seeing one line instead of multiple, they can click on the box on the legend that they want to see and have the other lines disappear. This can come in handy if the user only wants to see the numbers for a certain thing and does not need the comparison feature.
3. Overall, from each visualization that I examined, they successfully conveyed what they intended to, which is the main point.
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