# Posts for Tag: graphics

### Compound Interest and Stock Returns Calculator

Posted In: Economics | Money

# Calculate returns on regular, periodic investments

This calculator lets you visualize the value of investing regularly. It lets you calculate the compounding from a simple interest rate or looking at specific returns from the stock market indexes or a few different individual stocks.

Instructions

• Enter the amount of money to be invested monthly
• Choose to use an interest rate (and enter a specific rate) or
• Choose a stock market index or individual stock
• Use the slider to change the initial starting date of your periodic investments – You can go as far back as 1970 or the IPO date of the stock if it is later than that.
• Use the “Generate URL to Share” button to create a special URL with the specific parameters of your choice to share with others – the URL will appear in your browser’s address bar.

You can hover over the graph to see the split between the money you invested and the gains from the investment. In most cases (unless returns are very high), initially the investments are the large majority of the total balance, but over time the gains compound and eventually, it is those gains rather than the initial investments that become the majority of the total.

Some of the tech stocks included in the dropdown list have very high annualized returns and thus the gains quickly overtake the additions as the dominant component of the balance and you can make a great deal of money fairly quickly.

It becomes clearer as you move the slider around, that longer investing time periods are the key to increasing your balance, so building financial prosperity through investing is generally more of a marathon and not really a sprint. However, if you invest in individual stocks and pick a good one, you can speed up that process, though it’s not necessarily the most advisable way to proceed. Lots of people underperform the market (i.e. index funds) or even lose money by trying to pick big winners.

Understanding the Calculations
Calculating compound returns is relatively easy and is just a matter of consecutively multiplying the return. If the return is 7% for 5 years, that is equal to multiplying 1.07 five times, i.e. 1.075 = 1.402 (or a 40.2% gain).

In this case, we are adding additional investments each month but the idea is the same. Take the amount of money (or value of shares) and multiply by the return (>1 if positive or <1 for negative returns) after each period of the analysis.

Sources and Tools:

The graph is created using the open-source Plotly javascript visualization library, as well as HTML, CSS and Javascript code to create interactivity and UI.

### How much wealth do the world’s richest billionaires have?

Posted In: Money

This dataviz compares how rich the world’s top billionaires are, showing their wealth as a treemap. The treemap is used to show the relative size of their wealth as boxes and is organized in order from largest to smallest.

User controls let you change the number of billionaires shown on the graph as well as group each person by their country or industry. If you group by country or industry, you can also click on a specific grouping to isolate that group and zoom in to see the contents more clearly. Hovering over each of the boxes (especially the smaller ones) will give you a popup that lets you see their name, ranking and net worth more clearly.

The popup shows how much total wealth the top billionaires control and for context compare it to the wealth of a certain number of households in the US. The comparison isn’t ideal as many of the billionaires are not from the US, but I think it still provides a useful point of comparison.

This visualization uses the same data that I needed in order to create my “How Rich is Elon Musk?” visualization. Since I had all this data, I figured I could crank out another related graph.

Sources and Tools:
Data from Bloomberg’s Billionaire’s index is downloaded regularly using a python script. Data on US household net worth is from DQYDJ’s net worth percentile calculator.

The treemap is created using the open-source Plotly javascript visualization library, as well as HTML, CSS and Javascript code to create interactivity and UI.

### How Rich is Elon Musk? – Visualization of Extreme Wealth

Posted In: Money

See related visualization: How much wealth do the world’s richest billionaires have?

This visualization attempts to represent how much money Elon Musk, the richest person in the world, has. It gives context on this extreme amount of wealth by showing other very large sums of money that are somehow less than his net worth.

Each pixel on the screen represents a very modest amount of money (from $500 to$4000). As you scroll to the right, you will start to understand how incredibly large one billion dollars is, let alone hundreds of billions. You can change the amount of scrolling needed to get to the end of the visualization by selecting the amount represented by one pixel in the drop down menu.

This visualization was inspired heavily by a similar visualization made by Matt Korostoff for Jeff Bezos (when he was the richest person in the world) called “Wealth shown to scale”.

If you have any ideas about other items that could be added to the money chart, please leave them in the comments, and I will see if I can add it.

Mega-billionaires such as Musk or Jeff Bezos are not just extremely rich, the wealth they possess is unimaginably large. There are some extremely rich folks shown in the visualization who can buy pretty much whatever they could ever possibly need and yet their wealth is closer to that of the average person than they are to that of Elon Musk.

Sources and Tools:

The full list of data sources for the various money amounts are listed below. The visualization was made using HTML, CSS and Javascript code to create interactivity and UI. Data from Bloomberg’s Billionaire’s index , which is the source of Musk’s (and others) estimated wealth, is updated regularly.

Full List of Data Sources:

### Using up our carbon budget

Posted In: Environment

# How much more CO2 can we emit if we want to keep the global temperature rise below 1.5°C or 2°C?

Every bit of CO2 we release is one step closer to using up our carbon budget.

Click on the animate button (or use the slider) to see how we have used up our carbon budget to limit global warming to 1.5°C or 2°C.

Climate change is the result of greenhouse gases such as CO2 and methane from human activities. The amount of CO2 and other greenhouse gases in the atmosphere determines how much of the incoming solar radiation is trapped as heat. Since CO2 is the most common greenhouse gas and very long lived in the atmosphere, there’s a good correlation between the total amount of human CO2 emissions and the amount of warming that the earth will experience. This leads to the concept of a carbon budget.

# What is the carbon budget?

For every ton of CO2 that is emitted into the atmosphere about half a ton becomes part of the atmosphere for the long term, assuming there’s no massive new program to remove CO2 from the atmosphere. And there’s a direct correlation between the atmospheric concentration of CO2 and the earth’s temperature. Scientists tend to look at milestones of 2°C or 1.5°C when thinking about potential future warming. There is some uncertainty, but the total amount of human CO2 emissions that will lead to a 1.5°C warming from pre-industrial levels is around 2200 billion metric tonnes of CO2 plus or minus a few hundred billion tons (or 460 billion metric tonnes from 2020). This unit is also written as GtCO2 or gigatonnes of CO2. The values for the budget for 2°C warming are 1310 GtCO2 from 2020 or 2993 GtCO2 from pre-industrial levels.

Shown below is a graph from the Carbon Brief that shows the uncertainty in estimates for the remaining carbon budget (from 2018) before having a 50% chance of exceeding 1.5°C warming. As you can see there’s a fairly large range.

Update: The article’s author Zeke Hausfather pointed me to an updated article with newer IPCC estimates for the carbon budget of these two warming milestones. I have updated the code to account for these two new values.

# What may happen at 1.5 degrees of warming?

1.5°C (2.7°F) doesn’t sound like alot, but there are some pretty serious potential consequences that we’ll be dealing with. These include increasing the amount or frequency of the following:

• extreme heatwaves
• droughts
• extreme storms and precipitation events
• loss of wildlife and biodiversity
• sea level rise
• and impacts of human health

This NASA article has much more info on the specific issues related to this temperature rise. Ideally we’d keep warming to under 1.5°C but it looks likely that we may exceed 2°C unless we take fairly dramatic action to reduce or CO2 emissions from fossil fuel combustion and use cleaner/lower-carbon sources of energy, like renewables and nuclear power.

From 1750 to 2020, humans have emitted approximately 1683 GtCO2. The IPCC estimates that 460 GtCO2 would put us at 1.5°C warming and 1310 GtCO2 would put us at 2°C warming. These values give us an estimated total carbon budget of 2143 GtCO2 for 1.5°C and 2993 GtCO2 for 2°C warming.

You can really see how we are getting close to using up all of our 1.5°C carbon budget and the speed at which we are using it up, especially in the last few decades.

Sources and Tools:

Annual emissions data is from the Global Carbon Project. The visualization was made using the plotly.js open source graphing library and HTML/CSS/Javascript code for the interactivity and UI.

### National Park 3D Elevation Models

Posted In: Geography | Maps

#### Play with an interactive 3D model of some popular National Parks in the US

I wanted to try my hand at creating 3D elevation models and thought trying to model some of the popular (and some of my favorite) national parks would be a good starting point.

#### Instructions

Once a 3D elevation model is selected and shown you can manipulated it in multiple ways:

• Zoom – You can zoom in and out, though the method depends on the device you are using. Try scrolling or pinch to zoom. You can also select the magnifying glass in the toolbar and drag to zoom.
• Rotate – You can rotate and change the angle of the model using by clicking and dragging on the model. This is the default selection in the toolbar (circular arrow around z axis)
• Pan – You can move the model around with if you select the panning tool from the toolbar (arrows going in all directions)
• Show contours – if you hover or click on part of the map, it can show all the areas of the model with the same elevation and the tooltip will show the geographic coordinates and elevation (you can toggle showing the tool tip if you select the tooltip bar)
• Save image – click on the camera icon in the toolbar to save as png
• Colors – you can change the color scale used to show elevation. You can also reverse the color scale.
• Change vertical exaggeration – you can select whether the vertical height is exaggerated using the ‘Height Scale’ slider.  You can change between 1 (no exaggeration) to 11 (vertical scale is exaggerated by factor of 11).
• Change min elevation – you can select whether the minimum elevation is sea level or the lowest elevation in the park.

You can select a number of different parks from the drop down menu. If you have suggestions for additional parks, I may be able to add them to the list.

Note: the elevation files are data intensive since the visualization is downloading the elevation across in some cases, many hundreds or thousands of square miles. To keep the data needs down, I’ve reduced the resolution of the elevation data. Though the original data is 90 meter resolution (elevation is specified across every 90 x 90 m square in each park, I’ve averaged these squares together so that each park model only has about tens of thousands of these squares, regardless of the actual area of the park. This improves data loading and rendering times and makes the improves the responsiveness of the model.

Sources and Tools:
This visualization is written in HTML/CSS/Javascript. Digital elevation data is obtained from Open Topography and uses Shuttle Radar Topography Mission GL3 (90 meter resolution). The elevation data is downloaded using the opentopography API and parsed in a python script which downsamples the data to limit the number of elevation cells. The script also determines if a point is inside or outside of the park boundaries in order to create the elevation model. The 3D model is rendered using the Plotly open-source javascript graphing library.

### Iceberger Remixed and Improved – Iceberg Simulator

Posted In: Fun | Water

The code has been updated to allow for multiple chunks of icebergs now, which can occur via melting if you draw an iceberg a certain way.

#### Draw (or choose) an iceberg and visualize how it will float and melt

I was so impressed with the interactive Iceberger tool that Josh Tauberer (@JoshData) made that I had to modify it and add some additional features. Click here to see the original. My additions allow you to conjure up pre-made “icebergs” to see how they float and also allow some interaction. Try “poking” the icebergs you make.

Josh and I were both inspired by a tweet by Megan Thompson-Munson (@GlacialMeg).

Instructions
You can choose between 3 different iceberg creation options:

• Draw Iceberg – the original Iceberger option. Choose this option and draw any shape you want and see how it floats.
• Select State – Choose this option and select from one of the states of the United States to see how it will float.
• Select Shape = Choose this option and select from one of the premade shapes to see how it will float.

Once the iceberg has been created, you can also affect it in a couple of different ways:

• Click on the Iceberg – This lets you push on the left side of the iceberg to induce some rotation and see if there are multiple stable orientations. Click it several times in a row if you want to flip the iceberg over. If you push on the right size it will rotate the iceberg clockwise and if you push on the left size, it will rotate counter clockwise. if you push in the middle third of the iceberg, it will push it straight down.
• Melting – You can select between different options – No melting, slow medium and fast. This took awhile to code correctly. Previously, I’d just scale parts of the iceberg but this new code actually takes material away from the surface of the iceberg in a uniform way. It works more like you would expect melting ice to behave.
• Changing the Sky – You can change the colors of the sky between sunrise, midday and sunset colors.
• Showing forces – You can toggle whether to show the center of buoyancy (B) and center of gravity (B) of the iceberg.

Some Physics – no equations
The force of gravity (G) affects the entire body regardless of where it is or how it is oriented. If you show the forces, the red dot labeled G shows where the center of mass of the iceberg is. The blue dot labeled B shows where the center of buoyancy is. This is the center of mass of the part of the iceberg that is submerged. The force acting on the submerged part is equal to the volume of water displaced. If the center of buoyancy is below the center of gravity, then the forces will be equal and object will be in stable equilibrium. If the center of buoyancy is somewhere other than under the center of gravity, then the buoyant force will be pushing up on a different place than the gravity force and this will induce a rotation until they are directly over one another.

The code has been updated so that multiple icebergs are now allowed. Melting can separate a single piece of iceberg into multiple pieces, just as in real life. The melting process was a bit difficult to program because of the complexity of shapes that could be produced.

If you have additional suggestions for shapes or countries to add to the list or other improvements to make, let me know in the comments. Also if you are using this as a teaching tool, I’d love to hear how you are incorporating it into your curriculum.

Sources and Tools:
This visualization uses HTML/CSS/Javascript code from the Iceberger app to simulate the buoyancy of icebergs. Melting was accomplished with the help of code from the turf.js, polygon-offset and simplify.js javascript libraries. Additional elements of the UI and other features are also made using HTML, CSS and javascript.