Assignment 3

To be completed before 27-3-2021(Thurs) 1200hrs

This repo link will be of the format https://<username>.github.io/IDV-assignment3
In the forked repo create a basic index.html file, and make it visible on GitHub repo pages (it's under the settings tab, under GitHub pages).
You can put your CSS style tags, HTML and JS script code into one file, or organize them into files/directories.

We'll be looking at tabular datasets from data.gov.sg.
For example, housing, education or budget data.
You probably have to do some data manipulation. Whether it is in the CSV or via code or via API query, it's up to you.

The dataset can be huge, so frame one simple hypothesis that you are interested in.
E.g. What are HDB transactions in only Ang Mo Kio like in the last 6 months?
E.g. I'm interested in which universities in 2023 have the best employment prospects.
E.g. What is the projected revenue going to be like for our government this year?

Up to you. Do you want to do a complicated one scatterplot chart? Or maybe line and pie charts.
Feel free to come up with derived columns, and/or filter away data that is not relevant to your hypothesis.
If you are doing summary statistics, D3 has functions like D3.group to make your life easier. Or use an external library like tidyr.
Have a very, very simple writeup (a few lines) to explain your hypothesis and choice.
I'll get all of you to present your hypothesis and charts once the assignment is in.

I'm expecting at least one chart, but you are free to do more.
You may prefer not to use D3 and you can use any library that you want. However, please try not to just use Excel and then screenshot an image.
Up to you how much interactivity you want to put into the piece. Good interactivity takes a ton of work.
We'll be doing small code assignments for this course, so I'm not expecting anything complicated. Save it for the project.

Frame your hypothesis carefully so that you don't have to kill yourself doing this assignment.
You might want to use a tool like Pivot Tables to get an exploratory sense of the data.
The point of this assignment is to think about how to approach a bigger dataset (data), frame your hypothesis (task abstraction), then execute it (idiom).

Questions?

Chi-Loong | V/R