The rate of COVID-19 deaths and cases in the US is crazy high after the 2020 winter holidays and maybe still be going up. This visualization shows the number of COVID cases that occur in one hour or the COVID deaths that occur in one day based on the average of the last five days. This is another attempt to show the true scale of how many cases and deaths the US is dealing with, since it is often hard to understand large numbers. I have also attempted to show the scale of US deaths/cases here and here. Unfortunately, there are so many people getting sick and dying, it’s hard to fathom just how many people this actually is.
The 5-day averaging was done to smooth out any peaks and troughs in data reporting due to weekends/holidays, since I noticed that some states were literally reporting zero COVID cases some days while reporting many hundreds or thousands of cases other days.
The dots shown on the animation are located in the state that the cases or deaths occur but are randomly spread out within the state. This is done for visual clarity since if they were shown in their actual location, most of the dots would be overlapping in urban, high density areas. This approach lets you see which states have high COVID instances but still locate them by state.
You can share this animation by putting ?cat=deaths or ?cat=cases behind the url or copying and sharing one of these links:
Sources and Tools:
The coronavirus data comes from the covidtracking.com API. The data is parsed daily using a custom python script and visualizations are made using the open-source Leaflet javascript mapping library and the interface and animation are made using HTML/CSS/javascript.
This visualization looks at the variation in the amount of sunlight different latitudes receive over the different days of the year. The amount of sunlight can be classified in 3 different categories:
The default view is to see the number of hours of sunlight received by latitude on the current date, shown by the yellow bars. The sunlight hours range from 0 to 24 hours per day while most latitudes range from 9 to 15 hours.
If you hover over the yellow bars (or click on mobile), you will see the exact number of hours for that latitude band for that date.
Pressing the ‘Start Animation’ button, will change the angle of the sun relative to the Earth (as the earth rotates around the sun) and change the distribution of sunlight across the globe. You can view this animation with the earth fixed and the sun angle changing (the default view) or with the sun location fixed and the earth’s tilt changing.
This visualization helps to show how the seasons come about. When the Northern Hemisphere is tilted towards the sun, the amount of sunlight it receives increases (hours of daylight, average sun intensity and total amount of sunlight received). As the hemisphere tilts away from the sun, the amount of sunlight it receives decreases. The amount of sunlight a region receives causes the seasons that we experience.
Interestingly, when you are at the equator, the amount of sunlight per day does not really vary too significantly over the course of the year, whereas if you are near the poles, the difference between summer and winter is very dramatic. When looking at total sunlight received, the poles generally have lower sunlight because even in their summer, there is much lower land area relative to the middle latitudes (close to the equator)
The second visualization shown here shows how the tilt of the Earth’s axis is changed over the course of the Earth’s revolution around the sun. The Earth’s axis is tilted at 23.5 degrees relative to the plane of the Earth’s orbit around the sun. Like the last visualization, you can look at Earth the way we normally do (without the tilted axis) or from the perspective of the sun (with a tilted axis). This makes it a bit clearer why the tilt of the Earth’s axis can change from the north pole angled away to angled towards the sun.
Sources and Tools:
The equations for average daily solar insolation come from online lecture notes from University of Albany. The equations for number of hours of daylight comes from Wikipedia. The visualizations are made using the javascript d3 data visualization library and the interface and animation are made using javascript.
This visualization shows the phases of the moon. It’s a fairly simple visualization that shows a photo of the moon and covers it with a shadow to show only the lit up portion of the moon. Half of the moon is always lit up (half of the sphere) but we can usually only see part of the lit up portion.
Controls
You can use the slider to control the opacity of the shadow. There is a button that lets you start and stop the animation and you can also step through the animation with the ‘Back’ and ‘Forward’ buttons or the left and right arrow keys.
These are combined to get eight different distinct phases:
The moon goes through these phases once every 29.5 days. Because it’s not exactly a whole number of days, the size of each crescent isn’t exactly the same each lunar cycle. The rate of change in the size of the lit up portion of the moon is fastest when the moon is close to a quarter moon and slowest when the moon is closest to a new moon or full moon. This has to do with the way the light is projected onto a 3D sphere but viewed as a 2D disc.
Data Sources and Tools:
The moon image was downloaded from unsplash.com and taken by Mike Petrucci representing Delaware. The code to determine the size and draw the shadow was written in javascript and d3 open source data visualization library.
I was watching my kids try to pick who got go first by doing the kids rhyme,
“Eeny, meeny, miny, moe, catch a tiger by the toe, if he hollers let him go, eeny, meeny, miny moe.”
Since there were only two of them, it got me thinking, if you knew which one it would fall on at the end, you could decide who to start counting with to ensure that you select who you want. For each set with different numbers of options, you will get a different individual from that set chosen so I thought I’d visualize who gets selected.
Click “Start” to see which option gets selected when there are different numbers of options. Hover over the graph to see which option is chosen.
There are multiple variants of the rhyme, but the primary one mentioned above has 16 counting elements. The math is such that you take the modulo (which is equivalent to a remainder in long division). For example, if you have 15 choices for the 16 element phrase, you’ll count through all 15 and then go back to the first option and end on it (i.e. item number 1 is chosen). 16 divided by 15 has a remainder of 1. In the case that the remainder is zero, you choose the last item. I.e. if there are 16 items/people to choose among, the last option is chosen and the remainder will be 0.
Longer variants will have more words, which are also shown on the dropdown menu. If you know of other variations, let me know in the comments and I can add them.
Primary: “Eeny, meeny, miny, moe, catch a tiger by the toe, if he hollers let him go, eeny, meeny, miny moe.” – 16 counting elements (“catch a” is one element, “by the” is another, etc)
Variation#1: “Eeny, meeny, miny, moe, catch a tiger by the toe, if he hollers let him go, eeny, meeny, miny moe My mother told me to pick the very best one and that is Y O U” – 31 counting elements
Variation#2: “Eeny, meeny, miny, moe, catch a tiger by the toe, if he hollers let him go, eeny, meeny, miny moe My mother told me to pick the very best one and you are it” – 29 counting elements
Source and Tools:
The rhymes come from my childhood and my kids helped me remember some of the variants. Calculations are done in javascript and visualization is done with the open source Plotly javascript graphing library.
This animation shows the number of electoral votes each state had during each of the 59 presidential elections in US history between 1788 and 2020. It’s interesting to see the number of US states and their relative population sizes (in terms of electoral votes) over many different presidential elections. The population is counted every 10 years in the census so if a presidential election occurs between a census, it likely will not see any difference in numbers of electoral votes, unless something else happens (such as addition of a new state to the country).
Instructions
You can use the slider to control the election year to focus on a specific election and toggle the animation by hitting the Start/Stop button. Hovering over each state will tell you the number of electoral votes and the percentage of the total number of electoral votes in that election.
In the elections during and immediately after the US Civil War, we also see some states whose electoral votes for president are not counted (shown in purple). Wyoming, the state with the lowest population in the US, has the highest number of electoral votes per person in the state, while the three most populous states, California, Florida and Texas have the least number of electoral votes per person. Wyoming has four times the number of electors per capita than these 3 states have (i.e. accounting for their population sizes). That will be the subject of another map dataviz.
Sources and Tools:
Data on number of electoral votes by state for each election is from Wikipedia. And the visualization was created using javascript and the open source leaflet javascript mapping library.
Since the shelter-in-place orders across the United States due to the coronavirus in early to mid-March, many things have changed about our daily lives. One of the main ones is that schooling and work is being done remotely through video conferencing apps on our computers, tablets and smartphones. Our kids have zoom meetings with their teachers, parents have zoom meetings with our work colleagues and we all have facetime and google hangouts chats with our friends and family.
I remembered just a few year ago Skype was a very popular app to use for video chats, so I wanted to see how Zoom came to be the most popular app. The animated graph above shows the relative search volumes for 5 popular video conferencing apps from January 1 to May 15th (before and during the coronavirus restrictions on travel and gatherings).
This article implies that the reason Zoom had taken over so much is because it is free and easy to use for consumers. Even my tech-challenged mother is doing zoom calls for friends and classes.
Data and Tools:
Data is from google trends analysis of videoconferencing apps. Data is processed in javascript and graphed using the plotly open source graphing library.
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