AMCHARTS Waterfall Chart

Since I am having continued difficultly with getting the diverging bar chart and the waffle chart to render properly I decided to try the waterfall chart even though I was not sure what type of data I would put in it. Usually, I am driven by my need to see data visualized. But today I am driven by understanding the underpinnings of Amcharts better so I can figure out why I can not get my charts to render. At first, the waterfall chart would not display properly, but trying again fresh I got it to work. I am uncertain what I did differently.

The only data I could think to try to add to the waterfall chart was college costs with scholarship aid to result in a total estimated annual cost. The numbers I chose are loosely based on the University of Maryland, College Park campus net cost calculator, but the numbers are only roughly what is in the estimator. I am more interested in getting the chart to operate properly and posting it so I can see how it behaves when displayed on a phone. Unlike a traditional waterfall chart, the costs are “bad” at least from the student’s perspective and the scholarships are good so I was not sure what colors to use.

There are still a few variables I do not understand that are used to build this chart. I will have to read more into the documentation. Trying different charts and reading the documentation helps me better understand the workings of the program.

In the future, I think I could refine this chart with better data to illustrate the cost of college for different groups of students. It would be good to show that even with free tuition there are significant costs to attend college, in particular room and board.

Note: These numbers are made up for display purposes.

Short answer. Yes, free-and-reduced price status likely impacts college segment of initial enrollment. See the pretty Sankey diagram below that shows the college segment of initial enrollment for high school graduates by free- and reduced-priced meal (FARMS) eligibility status. However, read my data notes below before making any conclusions.

Most notably 47% FARMS eligible high school graduates failed to enroll in any college segment compared to 24% of non-FARMS eligible high school graduates. Also, 10% of FARMS eligible high school graduates initially enrolled in an out-of-state college compared to 24% of non-FARMS eligible high school graduates.

Click here if you can not see the diagram.

Long answer. As an analyst, I can think of a long list of reasons why this data does not answer this question. The first being is that the data source does not list actual numbers, just percentages. So I had to back into the numbers I used in the diagram. However, due to rounding, the numbers do not add up to the proper totals. If this was for real analysis I would try to get the actual numbers. I need to use numbers, even if they are not quite correct to get the diagram to render properly.

But for this project, I am just attempting to see if I can code this type of diagram and getting a general sense of what the diagram would show. On that end, it is a success. I can do the coding, I am sincerely hoping that you can see the diagram above right now. I also think I really like the visual effect. I think it works well when you have a few categories for each node.

Notes about the Data

  • The number of students are estimates from the percentages published by the Maryland Longitdinal Data System Center. I have not fully checked my calculations, this is primarily for me to learn how to create the diagrams using the software. I am also attempting to learn which types of data visulizations I find useful and worth pursuing. I also am trying to better understand the data.
  • Due to rounding in the data source the numbers do not add up to the correct totals. This is just for a general idea of the data, not for specifics.
  • Some notes adapted from those provided by the Maryland Longitudinal Data System Center, all errors are my own.
  • The number number of years following high school graduation impacts the initial postsecondary enrollment numbers. Graduates who enrolled in Private Career Schools or Continuing Education and Training Certificate sequences are not included.
  • This dashboard uses “initial enrollment,” which counts only the first enrollment of a student after graduation. For example, a student graduates high school, enrolls in a summer community college course, and then enrolls in an out-of-state college in the fall. The initial enrollment count for that student is one in-state enrollment. Other methods of counting enrollment may count that student as one in-state and one out-of-state enrollment. Accordingly, when reviewing, and especially when comparing post-secondary enrollment reports, it is important to understand how the enrollments are being counted.
  • The number of high school graduates reported on this dashboard includes: (a) only the counts of 12th grade graduates; and (b) eliminates any duplicate graduation recordsSome numbers are rounded or estimated due to data suppresssion. For general illistrative purposes only.

College of Initial Enrollment

During the 2013-2014 academic year approximately 58,300 students graduated from a Maryland public high school. Of those graduates, approximately 39,900 students had enrolled in college by the following year. The data set captures the higher education segment (community college, public four-year, State-aid independent institution, or out-of-state institution) that a graduate initially enrolls.

As shown in the Sankey diagram, high school graduates enrolled initially as follows: 30% at community college; 17% at a public four-year institution; 3% at a State-aided independent institution; and 19% at an out-of-state institution. An additional 32% of high school graduates did not (yet) enroll in a postsecondary education captured in this dataset.

This data set only captures the college of initial enrollment. For example, if a student enrolls in a community college for a summer class and then enrolls in a public four-year institution in the fall, the student will be recorded as enrolling in community college.

I wonder how the college of initial enrollment for public high school graduates compares to the total enrollment of the various sectors.

Click here if you can not see the diagram.

Source: Maryland Longitudinal Data System Center, Maryland Public High School Graduates with Initial Postsecondary Enrollments, 2013-2014 data

Notes about the Data

  • Some notes adapted from those provided by the Maryland Longitudinal Data System Center, all errors are my own.
  • Due to rounding the numbers do not add up correctly, so this is just for proof of concept if I had the actual numbers.
  • The number number of years following high school graduation impacts the initial postsecondary enrollment numbers.
  • Graduates who enrolled in Private Career Schools or Continuing Education and Training Certificate sequences are not included.
  • This dashboard uses “initial enrollment,” which counts only the first enrollment of a student after graduation. For example, a student graduates high school, enrolls in a summer community college course, and then enrolls in an out-of-state college in the fall. The initial enrollment count for that student is one in-state enrollment. Other methods of counting enrollment may count that student as one in-state and one out-of-state enrollment. Accordingly, when reviewing, and especially when comparing post-secondary enrollment reports, it is important to understand how the enrollments are being counted.
  • The number of high school graduates reported on this dashboard includes: (a) only the counts of 12th grade graduates; and (b) eliminates any duplicate graduation records
  • Some numbers are rounded or estimated due to data suppresssion. For general illistrative purposes only.

AMCHARTS Venn Diagrams

Earlier I wrote about trying to make a Venn diagram to show that high school graduates that meet University System of Maryland (USM) requirements and Career Technology Education (CTE) requirements were a subset of all high school graduates. I could not get the Venn diagram to render correctly. Today I figured out the correct syntax. I had to define areas in the Venn diagram that I did not actually want to show. That is, I had to define “USM HS Grads” and “CTE HS Grads” and “Both Requirements Grads” even though I do not want them to render separately in the chart. I know that is not the best explanation, but I want to just quickly make this diagram live to see if how it works on a live webpage. I will revisit this Venn diagram again soon with further refinements.

Click here if you can not see the diagram.

Source: Maryland Department of Education, High School Completion Data, 2019

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.

Refining the Pipeline

I spent yesterday trying to figure out how to create a divergent stacked bar chart in amcharts that would display properly on my website, which is based in WordPress. I was unsuccessful. I will need to continue reading through the documentation which is written for people who actually know how to code. Since I got frustrated with my original project, I decided to return to the immediate college enrollees pipeline again to refine it as I learn more about how amcharts operate.

This version of the Sankey diagram is a bit more readable. I was able to wrap the label text and add more space on the right-hand side. I also added code that will allow the data or the image to be downloaded, which I think is a cool feature. I am still having a bit of an issue getting the amcharts diagrams to display as part of the blog, but they work when looking at an individual post. I also added int the percentage numbers, each of which had to be separately added. I have read in the documentation that it is possible to load data into an amcharts from an external source, such as a spreadsheet, but I have not yet figured it out.

As with other versions of this diagram, the biggest weakness is that it does not capture transfer students.

Immediate College Enrollees Pipeline

Overall 65% of students that enrolled in college directly after high school graduation graduated college, from the same sector, by age 25. An additional 3% of students were still enrolled in college (in the same sector). Looked at another way only 31% of high school graduates graduated from college from the same sector that they enrolled in.

Click here if you can not see the diagram.

Source: Maryland Longitudinal Data System, Maryland Public School Pathways 2011

Notes about the Data

  • These notes are adapted from the notes provided by the Maryland Longitudinal Data System. Any errors are my own.
  • To be counted as a community college graduate, the student must have enrolled in any community college and graduated from any community college. Students who start at a community college but graduate from a college in another sector are not counted as graduates. Students who start in another sector but graduate from a community college are also excluded. To be counted as persisting (still in college), the student must have NOT graduated from any community college and be enrolled in any community college in Fall 2019. Some students who enrolled in community college transferred from the college and are enrolled in another four-year public, state-aided independent, or out-of-state institutions. Those students are not reported here.
  • To be counted as a public-four year college graduate, the student must have enrolled in any four-year public and graduated from any four-year public. Students who start at a four-year public but graduate from a college in another sector are not counted as graduates. Students who start in another sector but graduate from a four-year public are also excluded. To be counted as persisting (still in college), the student must have NOT graduated from any four-year public and be enrolled in any four-year public in Fall 2019. Some students who enrolled in a four-year public transferred from the college and are enrolled in another community college, state-aided independent institutions, or out-of-state institutions. Those students are not reported here.
  • To be counted as a State-aided indepented college graduate, the student must have enrolled in any state-aided independent institutions and graduated from any state-aided independent institution. Students who start at a state-aided institution but graduate from a college in another sector are not counted as graduates. Students who start in another sector but graduate from a state-aided independent institution are also excluded. To be counted as persisting (still in college), the student must have NOT graduated from any state-aided independent institutions and be enrolled in any state-aided independent institutions in Fall 2019. Some students when enrolled in a state-aided independent institutions transferred from the college and are enrolled in another community college, public, or out-of-state institutions. Those students are not reported here.
  • The out-of-state table above evaluates within sector college graduation independent of college of enrollment. To be counted as a college graduate, the student must have enrolled in out-of-state institutions of any type and graduated from an out-of-state institution of any type. Students who start at an out-of-state institution but graduate from a college in Maryland are not counted as graduates. Students who start at a college in Maryland but graduate from an out-of-state institution are also excluded. Out-of-state institutions may be community colleges, public four-year, or other types of private institutions.

Public High School Graduates that Earn a College degree by Age 25

I am back at making Sankey diagrams to illustrate the pathway to college degrees. Today I have manipulated data published by the Maryland Longitudinal Data System Center. Look at the College and Workforce Outcomes for Maryland High School Graduates data dashboards and the college pipeline report. MLDS produces dashboards on three populations, immediate college enrollees, non-traditional college enrollees, and “complete” college enrollees. I used that information and a little fudging to make a Sankey diagram showing the pathway to a college degree, which for this data is defined as a postsecondary certificate, or an Associate’s, Bachelor’s, or Master’s degree or higher. Unfortunately, this data set does not track the type of degree earned or the pathway the students took to earn the degree, although I hope to play around with the data in the future making some educated guesses to illustrate those pathways. For this diagram, I used the class of 2011.

Approximately 78% of public high school graduates enrolled in college either full-time or part-time as degree-seeking or non-degree seeking at any point after high school graduation. Overall approximately 50% of students who enrolled in college at any time earned a college degree by age 25. Those who are reported as not earning a college degree by age 25 may be actively pursuing a college degree at age 25 or earn a college degree after age 25.

Click here if you can not see the diagram.

Sources: Maryland Longitudinal Data System Center, College and Workforce Outcomes for Maryland High School Graduates; Maryland Longitudinal Data System Center, College Pipeline Report

Notes on the Data

  • College enrollment and graduation from Maryland’s community colleges, four-year public institutions and state-aided independent institutions is evaluated using data from the Maryland Higher Education Commission. College enrollment and graduation from out-of-state colleges and in-state private colleges is evaluated using data from National Student Clearinghouse. National Student Clearinghouse reports college graduation for the five year period after high school graduation, which is approximately age 23. It is possible additional students graduate from out-of-state colleges or in-state private career colleges after five years. Those records are not available to include in this analysis.
  • Non-Traditional College Enrollment includes high school graduates that either delayed degree-seeking enrollment in college until age 20, or enrolled for the first time as part-time degree-seeking. Non-Traditional College Enrollment is not reported until two years have lapsed since high school graduation.
  • A high school graduate is considered enrolled in college if the graduate meets the definition of Immediate College Enrollment. Immediate college enrollment is defined as a high school graduate who enrolls in college as a full-time, degree-seeking student in the fall immediately following high school graduation.
  • Students reported as “No College Degree by Age 25” may be actively pursuing a college degree at age 25 or earn a college degree after age 25.
  • The data in the diagram has not yet been fully checked. This post is the product of an active learning process. I plan to revisit the data and diagram in the future.

Venn Diagram in AMCHARTS

This post is mainly to show that I learned how to code a Venn diagram in Amcharts. However, I still have a ton to learn about how to code the data and what the data means. The Venn diagram is not one of the preset charts available in the Amcharts WordPress plugin. That said, with a little trial and error I was able to copy one of their examples and make it work. The main challenge was figuring out the correct resources to load.

I got data from the Maryland State Department of Education about high school completion for the class of 2019. It shows the number and percentage of students that left high school with a variety of qualifications. Three of the categories are University System of Maryland (USM) requirements, career technology education (CTE) requirements, and the requirements for both. Generally, the USM requirements are completing the credits required for admittance to a USM institution.

To be a CTE completer, a student must complete an approved CTE course of study. CTE programs are typically about 4 credits.

Since MSDE publishes the number of students in the State that complete both the USM and CTE requirements I can build a Venn diagram. The data below is for the entire State of Maryland. It is the first Venn diagram I have built using Amcharts. I need to explore more of the options. However, since it is easy for me to break the functionality of the charts using Amcharts, I will explore the functionality slowly and iteratively.

Blog | Caroline Boice

As I figure out the program you need to click on the actual post or this link to see the chart. I am working on this issue.

Future Venn Diagrams

It is sad that I probably will not be able to create a completely accurate Venn diagram for all of the high school completer options because I do not know how the categories overlap, but I will probably play with trying to set up a "representation" with a bunch of stated assumptions.

Update: Technical Issues

As I learn about these computer programs I am bound to run into technical issues because I am coming at this data from a public policy and scientific background. My last formal coding training was in 1992 or so when I was in middle school. As I was making these charts I ran into the (documented) issue of needing to use a specified placeholder value for the charts so that they show up properly. I failed to do that for a few charts because I was copying pieces of code from other places. I think I figured out that issue after a bit of trial and error. Now I've run into the problem of a few of the Amcharts not properly rendering when as part of the blog stream, but will render as part of an individual post. I have made a workaround of explaining the issue and posting a link to the post, but I am going to continue to explore a more elegant solution. The issue is probably I am missing a piece of code.

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

Ploting the Data

Yesterday I looked at SAT scores in Maryland by county and income and for the incoming freshman classes of the public four-year institutions. Today I take a brief look at SAT scores by county and race/ethnicity from the same dataset published by the Maryland State Department of Education. I made a dot plot using Datawrapper with all the race/ethnicity categories available in the data set as well as “all students”. To be honest, the chart looks very busy and is rather hard to read. I changed the color scheme to reds and oranges to aid with distinguishing the categories, but it only helped a little. I could choose custom colors for each group, and would if I was intending to show this data to a wider audience, but since this is primarily for my own exploration of the data I decided I did not have the energy to make those choices today. I did decide to highlight the “all student” category to help with readability a bit.

An alternative visualization, and the one I have seen used at State Board of Education meetings, is a grouped bar chart. While I think that would work for smaller numbers of counties or race/ethnicities, I think that it is worst than the dot plot for a large amount of data. However, I may explore this visualization in the future.

SAT SCores by county and Race/Ethnicity

It is hard to draw any conclusions from this data. For one thing, I am unsure if this data represents public school students or all students who took the test from that county. For another thing, not all students take the SAT and different local school systems have different policies about pushing students to take the SAT.

Howard County stands out as having very high scores, for students of all races. From the data, I do not know if Howard County encouraged only high-performing students to take the SAT. I would be surprised if that was the case, but it is a possibility. Since there is information about the number of students that took the test, I might be able to infer the policy from that data or I might look at their website to see if they have a SAT policy.

Note: I likely will not be posting for a while as I will be on vacation.