Posts for Tag: animation

Zoom has become the primary video conferencing app over the last few months as schools and workplaces increasingly turned to remote learning and meetings.

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.

Earlier, I had made a visualization showing that Mercury is the closest planet to Earth (on average) and not Venus or Mars. To make that, I downloaded a bunch of NASA ephemeris (orbital) data. I realized I could use the same data to make some cool orbital art inspired by a spirograph – a planetary spirograph.

Basically, you get to choose a planet and the visualization will draw a line connecting that planet and Earth every few days. These lines will then build up into a cool pattern over 40 earth years of orbital cycles. Each planet (Mercury, Venus and Mars) has a different orbital period around the sun than Earth does and as a result, interesting patterns emerges.

Orbital periods of the four inner rocky planets:

• Mercury: 88 days
• Venus: 225 days
• Earth:365 days
• Mars: 687 days

Also evident is that the orbits of some of the planets are not quite circular so the pattern isn’t quite centered on the sun. Venus has the most regular pattern, creating a distinctive 5-lobed design. The other planets also have visually stunning patterns, though they do not repeat perfectly over time.

You can change the planets using the drop down menu as well as change the speed of the spirograph, and hide the planets and the sun.

Data and Tools:
I had thought about simulating the planets but there are plenty of tools out there that generate this orbital data so instead just downloaded 40 years of ephemeris data (data related to positions of astronomical bodies) from NASA website.. I processed the data using javascript and drew the picture using HTML canvas tools.

Earth is known as the blue planet, because it’s covered with quite a bit of water. But do you know where all that water on Earth is located? This interactive visualization will show the various amounts of water in its many forms on Earth: Oceans, Lakes, Rivers, Ice, Groundwater, etc….

If you hover over a part of the circular, sunburst graph, it will show you the amount of water that is in each of the various forms shown. If the label for that form is bolded, you can click on it and see further subdivisions beyond that broad category. For example, if you click on Oceans, it will show you how the water in the oceans is distributed among the five main oceans on Earth. As you move towards more focused views on the graph, you can click on the center of the circle to move back out to larger categories and see the big picture again.

As you can see, most of the water on Earth is found in a salty form, and most of that is in the oceans. It can be hard to click through to see freshwater lakes and rivers, as you have to be very precise to expand the “Surface Water” wedge, when you are looking at all “Freshwater”.

Even smaller, on that same visualization, is the “Living things” wedge is basically invisible. You can further explore the details of the living things category by clicking on the button that appears on the freshwater graph.

Checking the Group Rivers and Lakes checkbox will group rivers by continent and lakes by major groups.

It is interesting to see how much water there is on Earth (about 1.4 billion cubic kilometers of water), but how little of it is non-salty, liquid freshwater at the surface (about 100,000 cubic kilometers, though that is still quite a lot) but it only makes up about 0.008% of all water on Earth. That means for every 10,000 gallons of water on Earth, only one of those gallons is freshwater in a lake or river that we can easily access.

It is also believed that there is more water deep in the Earth’s interior (i.e. the mantle) than on the surface or near-subsurface, but estimates of that are highly uncertain and are not included in this graph.

If you click out past Earth’s water to look at water in the solar system, the estimates shown in this visualization are only including liquid water and do not include estimates of ice (which I haven’t been able to find estimates of). The amount of water in living things is estimated assuming that the ratio of organic carbon to liquid water is more or less the same across all different types of living things (i.e. viruses, bacteria, fungi, plants, animals, etc.). This isn’t a great assumption but the estimates, which come from estimates of the dry carbon weight of these organisms, vary across many orders of magnitude so being off in liquid water weight/volume by a factor of two or so isn’t a huge problem.

Tools and Data Sources
The sunburst chart is made using the open source, javascript Plot.ly graphing library. Data on water distributions is primarily from Wikipedia – Distribution of Water – List of Rivers by Discharge – List of Lakes – Weight of Living Biomass – Extra-terrestrial water estimates

Watch the United States assemble state by state based on statistics of interest

Based on earlier popularity of the country-by-country animation, this map lets you watch as the world is built-up one state at a time. This can be done along a large range of statistical dimensions:

These statistics can be sorted from small to large or vice versa to get a view of the US and its constituent states plus DC in a unique and interesting way. It’s a bit hypnotic to watch as the states appear and add to the country one by one.

You can use this map to display all the states that have higher life expectancy than the Texas:
select “Life expectancy”, sort from “high to low” and use the scroll bar to move to the Texax and you’ll get a picture like this:

or this map to display all the states that have higher population density than California:
select “Population density, sort from “high to low” and use the scroll bar to move to the United States and you’ll get a picture like this:

I hope you enjoy exploring the United States through a number of different demographic, economic and physical characteristics through this data viz tool. And if you have ideas for other statistics to add, I will try to do so.

Data and tools: Data was downloaded from a variety of sources:

• Population https://en.wikipedia.org/wiki/List_of_states_and_territories_of_the_United_States_by_population
• Admission to union https://simple.wikipedia.org/wiki/List_of_U.S._states_by_date_of_admission_to_the_Union
• Educational attainment https://nces.ed.gov/programs/digest/d18/tables/dt18_104.88.asp
• Highest points https://geology.com/state-high-points.shtml
• Life expectancy https://en.wikipedia.org/wiki/List_of_U.S._states_and_territories_by_life_expectancy
• Median Age http://www.statemaster.com/graph/peo_med_age-people-median-age
• Land area https://statesymbolsusa.org/symbol-official-item/national-us/uncategorized/states-size
• Mean elevation https://www.census.gov/library/publications/2011/compendia/statab/131ed/geography-environment.html
• Electricity price https://www.chooseenergy.com/electricity-rates-by-state/
• Gasoline price https://gasprices.aaa.com/state-gas-price-averages/
• GDP https://www.bea.gov/data/gdp/gdp-state
• Sunlight North America Land Data Assimilation System (NLDAS) Daily Sunlight (insolation) for years 1979-2011 on CDC WONDER Online Database, released 2013. Accessed at http://wonder.cdc.gov/NASA-INSOLAR.html on Jun 14, 2019 1:37:15 PM
• Births United States Department of Health and Human Services (US DHHS), Centers for Disease Control and Prevention (CDC), National Center for Health Statistics (NCHS), Division of Vital Statistics, Natality public-use data 2007-2017, on CDC WONDER Online Database, October 2018. Accessed at http://wonder.cdc.gov/natality-current.html on Jun 14, 2019 1:53:58 PM
• Precipitation North America Land Data Assimilation System (NLDAS) Daily Precipitation for years 1979-2011 on CDC WONDER Online Database, released 2013. Accessed at http://wonder.cdc.gov/NASA-Precipitation.html on Jun 26, 2019 3:30:40 PM
• Temperature http://www.usa.com/rank/us–average-temperature–state-rank.htm

The map was created with the help of the open source leaflet javascript mapping library

The current CO2 concentration in the atmosphere is over 400 parts per million (ppm). This has grown about 46% since pre-industrial levels (~280 ppm) in the early 1800s. The growing concentration of CO2 is a big concern because it is the most prevalent greenhouse gas, which is increasing the temperature of the planet and leading to substantial changes in the Earth’s climate patterns.

This graph visualizes the growth in CO2 concentration in the atmosphere (mainly from CO2 emissions due to human activities, such as burning fossil fuels for energy production, deforestation and other industrial processes). The graph starts at 1980 when CO2 concentration in the atmosphere was around 340ppm. It has grown significantly since then.

One of the interesting aspects of CO2 concentration is that it is not identical all around the globe, as it takes awhile for the atmosphere to mix. The graph shows geographic differences in CO2 concentration as well as seasonal ups and downs, that underly an overall growing trend in annual average (mean) concentration.

Seasonal trends in CO2 concentration occur due to differences in the amount of plant growth across different months. Spring and summer plant growth in the northern hemisphere causes a significant amount of photosynthesis, and CO2 absorption, relative to the fall and winter. This plant growth causes a very large amount of CO2 to be absorbed by plants and a noticeable reduction in the amount of CO2 in the atmosphere. The southern hemisphere spring and summer (northern hemisphere fall and winter) aren’t as obvious because there is much less land in the southern hemisphere and the land that is there is close to the tropics and green all year round.

CO2 concentration can change by about 4-5 ppm due to the “breathing” of plants, which is pretty significant. The total weight of CO2 in the atmosphere is about 3 trillion tonnes of CO2, so 4-5 ppm is about 1% of this or 30 billion tons of CO2 removed by plant life each spring/summer.

Data and Tools:
Data comes from the US National Oceanic and Atmospheric Administration (NOAA). Data was downloaded using an automated python script and the graphs were made using javascript and the open-sourced Plot.ly javascript engine.

Electoral Vote maps give more visual power to states with large areas but few electoral votes

This map shows the electoral outcome of the 2016 and 2020 US Presidential Election and is color coded red if the state was won by Donald Trump (R) and blue if the state was won by Hilary Clinton or Joe Biden. When looking at the map, red states tend to be larger in area than blue states, but also generally have lower populations. This gives a misleading impression that the electoral share is “redder” than it actually is. For 2016, we can see that Trump won 306 electoral votes or (57% of the total electoral votes), but the map is shaded such that 73% of the area of the US is colored red. Similarly, Clinton won 232 electoral votes, but the map is shaded such that only 27% of the map is colored blue. For 2020, we can see that Biden won 306 electoral votes or (57% of the total electoral votes), but the map is shaded such that 38% of the area of the US is colored blue. Trump won 232 electoral votes, but the map is shaded such that 62% of the map is colored red.

The map shrinks the states with low electoral votes relative to its area and increases the size of states with large numbers of electoral votes relative to its area. On average blue states grow as they are under-represented visually, while red states tend to shrink quite a bit because they are over-represented visually. Alaska is the state that shrinks the most and DC and New Jersey are the areas that grow the most in the new map.

Here’s another map I made that looks at the 2016 and 2020 Presidential Election by County and shows the size of each county by land area or population.

I think this gives a more accurate picture of how the states voted because it also gives a sense of the relative weight of those states votes.

Data and Tools:
Data on electoral votes is from Wikipedia. The map was made using the leaflet open source mapping library. Data was compiled and calculations on resizing states were made using javascript.