Tag: map

This is a test of taking HTML code from Amcharts LIVE and embedding it into a post. If this works it might make making some types of maps and charts quicker. Although I like the flexibility of building charts and maps from scratch. I am just exploring all of the ways I can do data visualization so I can choose the best tool for the task at hand.

I made the map in amcharts Live and then I download the HTML code. I uploaded the code into my WordPress media file. Then I referenced the media file in a frame on this post.

I have not yet figured out how to make a map with a timeline, so here is a map showing the outbreak-associated cases in schools as reported by the Maryland Department of Health on September 1, 2021. Please refer to my first outbreak map for notes on the data. As with the other map the goal is for me to learn about the mapping software and data visualization using current data. The data and locations have not been checked.

In line with my interest in masking policies in public schools, I decided to map outbreak-associated cases in schools as reported by the Maryland Department of Health to check out the geolocation mapping feature of Datawrapper. As far as using the geolocation, it was super easy. I googled the address and pasted it into the correct box. I assume that the locations are generally accurate. It seems less precise than ArcView, but it seems to work well for when you are just trying to get a sense of the data. It did not that too long to enter the data for this number of locations. It would take a while if there were more locations. It would be much quicker if I had a spreadsheet with all the addresses of schools in the State pre-made and ready to go. I believe that there might be an official list of the public schools available. If I were to do this in the future I would explore using that existing spreadsheet.

I wish that I could add a choropleth map behind the location map to add another level of data details. I know it can be done with Arcview. But what you gain in usability you lose in features.

If you are wondering like I was about the outbreak at Quince Orchard when the school is not even open yet. The answer was found in this news article. Apparently, there was an outbreak in the football team which I assume has started practicing for the fall season.

Notes About the Data

These notes are copied from the Maryland Department of Health website.

Note: This dataset reflects public and non-public K-12 schools in Maryland that have COVID-19 outbreaks. Data are based on local health department reports to MDH, which may be revised if additional information becomes available. This list does not include child care facilities or institutes of higher education. Schools listed meet 1 or more of the following criteria:

Classroom/cohort outbreak definition:    1) At least two confirmed COVID-19 cases among students/teachers/staff within a 14-day period and who are epidemiologically linked, but not household contacts; or

School-wide outbreak definition:    

2) Three or more classrooms or cohorts with cases from separate households that meet the classroom/cohort outbreak definition that occurs within 14 days; or
 3) Five percent or more unrelated students/teachers/staff have confirmed COVID-19 within a 14 day period (minimum of 10 unrelated students/teachers/staff).

Cases reported reflect the current total number of cases. Schools are removed from the list when health officials determine 14 days have passed with no new cases and no tests pending. Archival data is available through the COVID-19 open data catalogue. These data are updated weekly on Wednesdays during the 10 a.m. hour. MDH is continuously evaluating its data and reporting systems and will make updates as more data becomes available.

I pulled data at noon on August 25, 2021, to make the above map. As I discuss locations are approximate. I provided the information on whether a school is public or private. All errors are my own. This map is not official, it is primarily for the purpose of me exploring the visualization features and keeping track of what I learned.

Sometimes I get to use my new skills to build something that is actually useful for real people. I made this map for the Maryland General Assembly to help keep track of the State’s public schools masking requirements. As a nonpartisan analyst my job is to provide clear nonpartisan information. I love how easy this map was to make on the technical side. I also like that I could add tooltips easily.

Update: Here is proof that someone important found the map useful.

Remiation Rates of Recent Maryland Public High School Graduates Enrolled at Maryland Public Institutions

Today I take a look at the remediation rates of recent Maryland public high school graduates enrolled at Maryland public institutions as published by the Maryland Higher Education Commission in their 2021 Data Book. According to data published by the Maryland State Department of Education, 57,622 students graduated from Maryland public high schools during the 2017-2018 academic year. According to MHEC’s remediation data set, 25,575 students enrolled at a Maryland public institution in fall 2018. Thus, less than half, 44%, of the public school graduates are reflected in the map below. So, the data may tell us less about the quality of public schools than first thought. I will have to see if I can drill down further to this data. My first step will be to look at the number of high school graduates from each county; however, since the percentage of students who are low-income is different in each county, the college-going behavior is likely not consistent.

I was a little surprised to see that 25,575 students enrolled in a public institution immediately after high school because according to the college pipeline data published by the Maryland Longitudinal Data System Center, 17,410 students enrolled in a public institution immediately after high school. I wonder if MLDS is better able to separate students enrolled in multiple institutions. Further, the MLDS dataset only is capturing “degree-seeking” students.

Notes About the Data

  • Students may be enrolled at more than one institution. They are included in enrollment figures for each insituiton at which they are enrolled.
  • Data include all degree- and non-degree seeking students enrolled in credit courses.
  • Maryland residents are identified using their place of residence at the time of application to the insituion.
  • Maryland public instiutitions include community colleges and four-year public colleges and universities.
  • Recent Maryland public high school graduates are defined as those graduating from a Maryland public high school, identitifed using the College Board School Code, who graduated in the 2017-2018 academic year and first enrolled in higher education in Maryland in fall 2018. Analysis relies on high school graduation date and reporting of remedial assesment data; missing data for these variable may result in underreporting.
  • Maryland residents whose county of residence is unknown are included in insitutuional-level remedial data, but excluded from reporting by county of residence.
  • Salisbury University and St. Mary's College of Maryland do not offer remedial coursework.

More Than 80% of the Student BODY At Most COmmunity COlleges are Maryland Residents

According to the Maryland Higher Education Commission, 91.6% of Maryland community college students are Maryland residents. This is not surprising at all as community college students tend to attend their local community college. From looking at a data table I was able to see that more than 80% of the student body at most community colleges are Maryland residents. However, only 55.4% of students at Allegany College of Maryland are Maryland residents. With that information and a bit of curiosity about using Datawrapper for mapping, I decided to build a map showing the location of the main campus of each community college and the percent of students that are Maryland residents.

Building the map was relatively simple. I used google to look up the address for the main campus address for each of the 16 community colleges in the State. I then pasted that information into the program and added typed in the Maryland resident information for each college. From my basic sense of the locations of the colleges, the placements look accurate, but I have not checked them.

I struggled with how to best visualize the data since most of the colleges have more than 80% of the student body being Maryland residents. Reducing the number of color categories to three really helped with this issue. It highlights that Allegany College of Maryland is an outliner and Hagerstown Community College is almost an outliner. I probably should have either rounded the numbers to make Hagerstown Community College 80% and reduced the categories to two colors, but I think it is a little fun to see that Hagerstown Community College does not quite meet the 80% requirement. I could also say something such as all but one community college has 79% or more of its student body as Maryland residents. If I was highlighting Allegany College for some reason I would probably do one of those options. But since I am just playing around with the data to see what jumps out at me, I have not done that this time.

After I mapped the data I saw that Allegany College is very close, less than 3 miles, from the West Virginia border. It is also close to the Pennsylvania border. There are other community colleges that are not far from the State borders, but these colleges seem to draw a smaller percentage of non-Maryland residents. Perhaps if I put the color break at a higher percentage and treated Allegany College less like an outliner that story would become clearer, but I have not yet tried that.

WHat I learned from this Mapping Experience

  • Adding location markers in Datawrapper is easy, but can be time consumming
  • Datawrapper is significantly easier to use than other mapping software such as ArcView, but the data crunching functionality is less
  • I have not yet figured out how to show just one of Maryland's counties in a map
  • When most of the data is in the same range, but there are outliners, the data can be hard to visualize
  • I haven't decided how to handle colleges with mulitple campuses when mapping. Representing the "main" campus seems to be the best way for now.
  • Color breaks can change the data story

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