31:T602,## Submission Instructions: 1. You are free to either **fork this notebook** or **create your own notebook** for this mini-project. Ensure that: - The notebook is made _public_ in the settings. - That you include the following details inside of your submission at or near the top of the notebook: 1) _NetID_, 2) _Name_, and 3) _Notebook URL_. **You will get a ZERO if you do not include these details!** 2. Complete each question to the best of your ability, clearly marking which visualization and/or written answer corresponds to which question asked. - Your coded solutions **must use D3**. Other visualization libraries (.e.g Vega-Lite) are not allowed. - You are allowed to use functions and modules created by other creators. For example, you can use [Mike Bostock's Color Legend](https://observablehq.com/@d3/color-legend) notebook to create your legends. 3. Export a `.tgz` of your completed notebook and upload it to the correct Assignment on Brightspace. This mini-project is due November 20 @ 11:59pm.

[NOTE]: Please make sure to Read ALL instructions carefully for each part of this assignment; the code should try to match exactly the requirements specified!

[NOTE]: Please make sure that your NOTEBOOK URL link correctly links to your noteook, alongside your Name and NetID, before submitting!

32:T4dd,### Aid Data, Revisited Here we load a simplified and reduced version of the AidData dataset. You are free to change this code as you wish. If you don't want to preprocess your data on Observable, then you can do the preprocessing using whatever languages or tools you'd like and then [upload](/@observablehq/file-attachments) your preprocessed data to Observable. If you take this approach, then you should delete the aiddata cell below so that you're not loading unnecessary data. The dataset contains the following columns: - yearDate: year of the commitment as a Date object - yearInt: year of the commitment as an integer - donor: country providing the financial resource - recipient: country receiving the financial resource - amount: the total amount of financial resources provided - purpose: the purpose of the transaction33:Tb55,## Questions Your goal is to create 3 independent visualizations of the same data set, each one with the intent of answering the questions stated below. For each numbered question, you should be able to 1) create a data visualization that answers **all** of the questions specified, 2) provide a written analysis that extrapolates from your visualization and answers **all** of the questions specified, and 3) provide a written description of your thought process and why you think your solution is *appropriate* and *effective*. These are the 3 visualizations you should create: - **Visualization 1:** a) How does the amount donated vs. amount received change over time for each country?; b) Are there countries that mostly send or mostly receive and countries that have a similar amount of donations they receive and send?; c) Are there countries that change their role over time? That is, they used to mostly send donations and turn into mostly receiving donations and vice-versa?; d) Are there countries in which you can find a sudden increase ("peak") or a sudden decrease ("valley")? - **Visualization 2:** Focus on the top 10 "Coalesced Purposes" of donations (in terms of amount of disbursement across all countries and all time). What are the top 10 purposes of disbursements (in terms of total amount of disbursement) and how does their relative amount compare over time? E.g., are there purposes that tend to be prominent for a period of time and others that become more prominent during other periods? - **[Hint]**: looking at the graph one should be able to observe: “Ah! During these years donations were mostly about X but then there were way more donations about Y”. - **[Note]**: if the purpose is “UNSPECIFIED” it should be removed. - **Visualization 3:** Focusing exclusively on countries that receive donations, how do donations shift geographically over time? Do donations tend to be always in the same regions of the world over the years or they have been shifting over time? Can you build a visualization that shows the "history of donations" so that one can get a sense of which regions of the world have had more need for donations over the years? - **[Note 1]**: for this visualization you can, if you wish, use interaction (but you don’t have to). - **[Note 2]**: For this exercise you may want to review the lecture on geographical visualization in which we explain how you can visualize geographical data over time. - **[Note 3]**: if you want, you can aggregate data over a few years (say, group together data at 5 year intervals).

[Note]: It is okay to submit more than one solution for a given visualization problem if you think there are some competing solutions that work well. When you do that, make sure to compare the solutions by commenting on their advantages and disadvantages.

34:[{"id":"55260abbc777c0a3b8fed19f3929dd822fef9d5118b53b76b2176d20782910e599eac919999ea8ee85a60b783fd37082574f6591fd46c0d70ddf9b00df71ce27","href":"https://static.observableusercontent.com/files/55260abbc777c0a3b8fed19f3929dd822fef9d5118b53b76b2176d20782910e599eac919999ea8ee85a60b783fd37082574f6591fd46c0d70ddf9b00df71ce27","name":"countries-50m.json","type":"application/json","lastModified":1762448451011.011,"size":4177662}] 2f:{"title":"Mini-Project 2: Temporal Data Visualization","cells":[{"id":155,"value":"# Mini-Project 2: Temporal Data Visualization","pinned":false,"hidden":false,"mode":"md"},{"id":162,"value":"import {css} from \"@rk2546/2025-infovis-cse_notebook-gallery\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":165,"value":"css","pinned":false,"hidden":false,"mode":"ojs"},{"id":168,"value":"$31","pinned":false,"hidden":false,"mode":"md"},{"id":170,"value":"---\n\n#### [TO-DO]\n\nFill out the following submission details:\n\n* **Name:** <FULL NAME>\n* **NetID:** <NET ID>\n* **NOTEBOOK URL:** <NOTEBOOK URL>\n\n---","pinned":false,"hidden":false,"mode":"md"},{"id":179,"value":"## About the Datasets","pinned":false,"hidden":false,"mode":"md"},{"id":175,"value":"$32","pinned":false,"hidden":false,"mode":"md"},{"id":96,"value":"Inputs.table(aiddata)","pinned":true,"hidden":false,"mode":"ojs"},{"id":5,"value":"googleSheetCsvUrl = 'https://docs.google.com/spreadsheets/d/1YiuHdfZv_JZ-igOemKJMRaU8dkucfmHxOP6Od3FraW8/gviz/tq?tqx=out:csv'","pinned":false,"hidden":false,"mode":"ojs"},{"id":7,"value":"aiddata = {\n const data = await d3.csv(googleSheetCsvUrl, row => ({\n yearDate: d3.timeParse('%Y')(row.year),\n yearInt: +row.year,\n donor: row.donor,\n recipient: row.recipient,\n amount: +row.commitment_amount_usd_constant,\n purpose: row.coalesced_purpose_name,\n }));\n \n data.columns = Object.keys(data[0]);\n \n return data;\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":32,"value":"### Country GeoData\n\nNext we load GeoJSON data for countries. This file is derived from data from Natural Earth.","pinned":false,"hidden":false,"mode":"md"},{"id":37,"value":"geoJSON = FileAttachment(\"countries-50m.json\").json()","pinned":true,"hidden":false,"mode":"ojs"},{"id":119,"value":"$33","pinned":false,"hidden":false,"mode":"md"},{"id":57,"value":"### Remember\n\nThe questions above are a very useful tool for you to verify whether you are producing a good solution or not. As you go about solving this exercise you can use the questions above as an evaluation tool in two main ways:\n\n1. Verify that you can indeed answer the questions with your visualization. If you can’t fully answer the questions, it means your solution has some problems.\n2. Compare multiple solutions to the same problem and ask yourself: “which one makes it easier for me to answer these questions?”, where easier may mean, more accurately, with less effort or faster.\n\nFurthermore, you should feel free to process and transform the data any way you deem relevant and use any tool you prefer for data processing. Data transformation does not necessarily have to be in JavaScript nor within Observable. It’s ok to pre-process the data and then load it in Observable if you prefer.","pinned":false,"hidden":false,"mode":"md"},{"id":143,"value":"### Grading Criteria\n\nYour answers to each question are graded on the following qualities, with each question totaling up to **25 points**:\n\n- **[10pts]**: Does the visualization answer the questions posed in the exercise?\n- **[10pts]**: Does the written answer & discussion the questions posed in the exercise?\n- **[5pts]**: Is the visual representation clear? Does it have good aesthetics? If needed, you can review this [notebook on clarity](/@nyuvis/contextual-elements-aesthetics-and-clarity) for reference.","pinned":false,"hidden":false,"mode":"md"}],"files":"$W34","stdlib":"1","titling":"auto"}