Get started (or continue) with dynamic web content creation. This assignment will introduce (or reintroduce) you to JavaScript and how it can be used to manipulate HTML and SVG content.
There are three parts for this assignment. You may complete the assignment in a single HTML file or use multiple files (e.g. one for CSS, one for HTML, and one for JavaScript). You may not use D3 or any other external libraries for any of this assignment except for loading data. The Mozilla Developer Network documentation serves as a great reference for the technologies involved in this assignment. In addition, Scott Murray’s Interactive Data Visualization for the Web is a useful reference (see Chapter 3).
The assignment is due at 11:59pm on Friday, September 27.
You should submit any files required for this assignment on Blackboard. For Observable, do
not publish your notebook; instead, (1) share it with me
(@dakoop
) and (2) use the “Export -> Download Code”
option and turn in that file renamed to a2.tar.gz
(or
a2.tgz
) file to Blackboard. Please do both of these steps
as (1) is easier for me to grade, but (2) makes it possible to persist
the state of the submission. If you complete the assignment outside of
Observable, you may complete the assignment in a single HTML file or use
multiple files (e.g. one for HTML and one for CSS). Note that the files
should be linked to the main HTML document accordingly in a
relative manner (style.css
not
C:\My Documents\Jane\NIU\CSCI627\assignment2\styles.css
).
If you submit multiple files, you may need to zip them in order for
Blackboard to accept the submission. The filename of the main HTML
document should be a2.html
.
This assignment deals with data about the computer science graduates according to data collected by the National Center for Education Statistics (NCES). NCES runs the Integrated Postsecondary Education Data System (IPEDS) survey and makes that data available. We wish to examine the trends in computer science graduates from 2000 through 2023. Note that while IPEDS now captures information about students whose gender does not align with the “Men” or “Women” categories, schools are required to allocate all students to those categories (see their FAQ). I have downloaded it and reformatted this subset of the data here. The attributes of this data include:
YEAR
: the yearCTOTALT
: the total number of graduates (NA
if this information was not provided)CTOTALM
: the total number of graduates who were
allocated as menCTOTALW
: the total number of graduates who were
allocated as womenAWLEVEL
: the type of degree awarded (5 for Bachelor’s,
7 for Master’s, and 9 for Ph.D.)You will create three visualizations from this data: a table, a horizontal bar chart, and a vertical bar chart. Note that only CSCI 627 students need to complete Part 3b, but CS 490 students may complete it for extra credit.
Like Assignment 1, start by creating an HTML web page with the title “Assignment 2”. It should contain the following text:
You should load the data via a d3.csv
call using the
full url: https://gist.githubusercontent.com/dakoop/dd74308ae4c368c99c05c85381e4c7e2/raw/de7570bdb7b4da7151c930dd61c7d86bfa32b3a6/cs-grads.csv.
Outside of Observable, this requires including the d3-fetch
library. In Observable, File
Attachments could also be used, but make sure you do not
edit the contents of the file before uploading it; if you edit
the file instead of using JavaScript to process it, points will be
deducted. Once you load the file, you should see an array of objects,
one for each year. In Observable, you can view the output of your code,
but if you’re in another environment, consider using the
console.log
function to print your updated data to the
Console (a tab in Developer Tools panel of your browser). The data for
Bachelor’s degrees in 2003 looks like:
YEAR: "2003", AWLEVEL: "5", CTOTALM: "43229", CTOTALW: "16063", CTOTALT: "NA"} {
We will be processing this data to first exclude graduates who received degrees other than a Bachelor’s, convert the strings to numbers, compute and fill in missing totals, and then render a table of these three values.
In this section, do not use loops. Use Array
functions map
, filter
, reduce
,
and/or forEach
. Also, do not change the
order of the data items (i.e. do not sort the array). First, we only
wish to examine Bachelor’s degrees so create a new array that only
includes the entries for that type of degree. Second, some of the older
data did not include values for the total count (CTOTALT
);
missing entries are indicated with the value “NA”. Create a new array
where the entries that are missing have been filled in with the sum of
CTOTALM
and CTOTALW
. For the others, transform
them from the string to an integer. (See this note
about IPEDS’s requirement that the sum of these two categories matches
the total.) In this new array, the data for 2003 should look like
YEAR: 2003, CTOTALT: 59292, CTOTALM: 43229, CTOTALW: 16063} {
(Note the absence of quotes indicating that these are numbers instead of strings now.) The full output is available here.
parseInt
method that will convert a
string into an integer.{key1: var1, key2: var2}
)Once you have verified that your function works correctly, display
the results in text on your web page. If you were not
able to get part a to work correctly, you may store the output here in a JavaScript variable. To create the
table, you will need to dynamically create HTML elements in your web
page. You may either create a <div>
element for the
table and add the necessary elements to it using JavaScript, or use
templating to dynamically create the rows. I recommend using Observable
, but you may also use innerHTML
and template
literals. Your table should have four columns: one for the year, one
for the number of graduates allocated to “Men”, one for the number of
graduates allocated to “Women”, and one for the total number of
graduates. Add headers to the top of the table to
indicate what is shown in each column. Your table should be sorted, but
do this by creating a copy of the array using toSorted
(leave the original array unsorted).
document.getElementById
or document.querySelector
function to get a reference to the parent div
element.Now, let’s create a more visual representation of this data using a bar chart that shows the total degrees by year using the same data as in Part 1a. Important: Do not sort the data from Part 1a! The bar chart should be horizontal, meaning that bars grow from the left to the right side of the canvas. Add axes labels to indicate the starting and ending year as well as range of values. For this assignment, the labels do not need to be precise.
Create an svg
element with width 300px and height 400px.
Then, add svg elements using JavaScript to create the bars and labels.
The visualization must accurately represent the data, but you should
experiment with the design of the chart (thickness of lines, number of
labels, spacing, axes scales, colors) to find a visualization that
communicates the data well. Here, templating should again work well, but
you may also use the addEltToSvg
helper method we saw in
class:
function addEltToSvg(name, attrs, appendTo)
{var element = document.createElementNS("http://www.w3.org/2000/svg", name);
if (attrs === undefined) attrs = {};
for (var key in attrs) {
.setAttributeNS(null, key, attrs[key]);
element
}if (appendTo) {
.appendChild(element);
appendTo
}return element;
}
Now, redo Part 2 but as a vertical bar chart, meaning that bars grow from the bottom to the top of the canvas. Again, add axes labels to indicate the starting and ending years as well as range of values. Again, use JavaScript or templates to add the SVG elements. Here, the SVG is 400x300 pixels.
Now, update your code for the vertical bar chart so that a user can
highlight a group of bars by half-decades. Specifically, given a
half-decade (e.g. 2005), change the appearance of all
of those half-decade’s bars (e.g. 2005 through 2009) to stand out from
the others. This should be static; you should not
update the highlighted bar based on where the mouse is. In either case,
use the class
attribute to specify the style of the
highlighted bars and write the corresponding CSS to specify the change
to the style. If using Observable, you can use an input to set a
variable that you can use reactively in your template.
= html`<input type="range" id="half-decade" min="2000" max="2020" value="2000" step="5"></input>`; viewof halfDecade
Now, other cells can reference the variable decade
and
any time the slider moves, those cells will reactively execute.
The other approach is to add the following HTML after your vertical barchart:
<div id="controls">
<label for="decade">Half-Decade:</label>
2000<input type="range" id="decade" min="2000" max="2020" value="2000" step="5"></input>
2020</div>
and JavaScript code:
document.getElementById('half-decade').onchange=(function() { highlightHalfDecade(this.value); });
and finally, define a function highlightHalfDecade
that
will highlight the specified decades. (You could also put this directly
in the onchange
function if you wish.) In addition, if you
wish to use a different input to trigger the highlighting (e.g. a text
field), this is also ok. However, you may not simply
have the user define the variable (halfDecade = 2005
); it
must use an <input>
element as we are trying to
improve user interaction.
setAttribute
calls.