#10 Translation Device

Description

General Description:

white: date
pink: conversion rate of 1 USD to CNY on the shown date
cyan: confirmed cases in the US on specific date
lavender: confirmed cases in China on specific date

Q: Which feminist data principle did you choose to follow and why?
A: Principle 6: The Numbers Don’t Speak for Themselves
Numbers/data are always considered being unbiased, and reflect objective facts. However, there're many data do "lie", because 1. the interference of existing power; 2. the limited parameters being calculated. So, I'd like to find datasets of topics that are new to me--datasets that seem reflecting facts but actually have something hidden behind, and do some research to find out the real truth about the issue. This project is more for my own study purpose.

I used loadJSON()to load the two datasets into p5js, and use callback function to draw them out. dates from 2020-01-30 to 2020-12-14 are listed line by line with the conversion rate on that date. Confirmed cases are listed every 30 days, because if they're listed on daily bases, the whole canvas will look too crowded and messy. The point is to show confirmed cases are constanly increasing in the US, so it shows the fact even if not everyday is listed.

The reason why US dollar value increased during the worst time in the US was because when the market was full of uncertainty and risk, investors tended to hold cashes instead of investment assets(e.g. stocks, fund, etc.). US dollar is still the leading currency in the world, so investors see it as an asset to lower risks. Also, another reason why US dollar was doing unusually well during this period was because other countries were doing worse at this time. That also increased the appeal of US dollar.

However, as cases in the US continued to increase, and the unprecedent actions taken by US government, the value of US dollar started to decrease. Comparing to China, which has got the pandemic under control, US dollar was less appealing as time approaches to the end of the year, and China Yuan became more attractive because capitals are attracted by China's relatively safe environment during the pandemic and the growing economy.

References:
Miller, Chris. “The Dominance of the U.S. Dollar During the COVID-19 Pandemic.” Foreign Policy Research Institute, 13 May 2020, www.fpri.org/article/2020/05/the-dominance-of-the-u-s-dollar-during-the-covid-19-pandemic/.

Landsman, Stephanie. “Economist Stephen Roach Issues New Dollar Crash Warning, Sees Double-Dip Recession Odds above 50%.” CNBC, CNBC, 24 Sept. 2020, www.cnbc.com/2020/09/23/us-faces-dollar-crash-high-double-dip-recession-odds-stephen-roach.html.

Design Process

Q: Describe your design process.
A: 1.Select datasets:
API:
1)Dataset of Covid-19 confirmed cases in China and the US
2)Dataset of conversion rate 1 USD to the amount of CNY(China Yuan) from 2020-1-30 to 2020-12-14
2.Comparing the two sets and see how currency rate of US dollar change comparing to CNY during the pandemic, and analyze how the pandemic has affected the rates.

p5js code

Confirmed Cases & USD/CNY Conversion Rate
Confirmed Cases & USD/CNY Conversion Rate(Simpler Version)

Reflection

1. Remember to add "https://" when put the url in loadJSON() function.

2. Use for loop to separate long array into several parts, in order to split them and show them line by line.

3. Security issue is important for p5js. If a website is not secure, the p5js is not able to load the JSON file directly from that website.