Posts for Tag: data

Navigate the globe to the specified cities eating as many apples as you can

I coded a unique twist on the classic snake game, Snake on a Globe, where your mission is to eat as many apples as you can when given their location and find the best ways to navigate the globe.

The game includes the largest cities in the world and tests your geographical knowledge about country and city locations. Your challenge is to move to the next apple and city in the most efficient manner, moving only along lines of longitude or latitude. But remember you are on a sphere so you can move around the globe in any of four directions: over the poles and east and west.

Instructions

Sources and Tools:
The list of cities and their population is from Simplemaps. The game is coded with Three Globe and Three.js, 3D javascript libraries in javascript and HTML and CSS.

Which majors are most competitive across the University of California system?

The University of California consists of nine campuses with undergraduate programs and they are all ranked among the best universities in the US (according to US News). All nine rank within the top 45 public schools including #1 and #2 and top 85 national universities in the US.

This data visualization focuses on the acceptance rates for students based on their indicated preferred majors in their application to the various University of California campuses in the Fall of 2023 admissions cycle. When you apply to a given university campus, you need to specify a major and this choice can affect the student’s chances of getting accepted, especially if the major is very sought after. Subjects like computer science are very popular and as a result, the data shows that most campuses have a lower acceptance rate for computer science as compared to the university as a whole.

Data visualization

The graph shown in the data visualization is a marimekko graph which shows a percentage based bar graph showing the acceptance rate (in blue) for a given major at a given university. The height of each horizontal bar is proportional to the number of applicants to that major, so taller bars have more applicants vs bars that are shorter. If you hover over (or click on mobile) a bar, it provides more information about the acceptance rate, enrollment rate (i.e. yield rate) and the GPA of accepted students. You can choose to sort the graph by subject name, admit rate or number of applicants.

The data visualization can help you explore different campuses and major categories. If you are viewing “School View“, you can see how the various disciplines compare for a single university at one time. Whereas if you view “Subject View” you can see the comparison of a single discipline across the University campuses that offer those majors.

The University of California has over 240,000 undergraduate students and extends about 140,000 acceptances to fill out 42,000 slots for first year students. There is a significant amount of overlap as most students applying for admission apply to several campuses, and many students get accepted to multiple campuses.

The broad disciplines used in the visualization are composed of a number of individual majors and these are detailed in the table below.

GPA calculation

The University of California only considers grades from 10th grade and 11th grade for admissions decisions, and uses a weighted system where honors and AP classes are given an extra point in GPA calculations above the normal A=4, B=3, C=2, etc. . GPA calculation. So for an honors math class, for example, an A would be worth 5 points.

Sources and Tools:
Data comes directly from the University of California website for the fall of 2023, which has quite a bit of interesting data about students and admissions. I downloaded the data and processed it with python to organize it. The webtool is made using javascript, HTML and CSS and graphed using the open-source plotly graphing library.

Table of Disciplines to majors

This table lists the specific areas and majors that make up the broad disciplines shown in the data visualization.

What are the main sources of California’s electricity?

I added the option to view the graph for any day or monthly average from April 2018 to the present using the calendar picker and a daily generation summary

In the United States, electric power plant emissions account for about 25% of greenhouse gas emissions. However, California has been a leader in the transition to clean and renewable energy, driven by ambitious climate policies and a commitment to reducing greenhouse gas emissions. The state has set an electricity target for the state of 60% renewables by 2030 and 100% zero-carbon, clean electricity by 2045. To meet these targets, the state has been investing heavily into solar and wind energy sources. Solar is the largest proportion of California’s electricity grid and California now generates more solar energy than any other state.

The California Independent System Operator manages the grid for around 32 million Californians or about 80% of the total demand in the state. Here is a map showing the service area and the other electricity districts in the state, the main exceptions include the city of LA and the Sacramento area.

How to read the graph of California’s electricity

The graphs shown here allow us to visualize how electricity generation in the California Independent System Operator (CAISO) region varies over the course of the day. We can see how solar ramps up to be a huge contributor in the middle of the day. And overall, the vast majority of the generation in the state is one form of renewable electricity or another (e.g. solar, wind, hydro, geothermal, biomass and biogas). Add in a small contribution from zero-carbon nuclear energy and we can see that a large majority of power generation comes from zero-carbon sources. It also shows the total electricity demand, which should always be less than the total electricity supply in the state.

Because of the intermittent nature of some renewables, like wind and solar, there are times where the demand for electricity is not able to be met by these sources, and other options are needed to maintain supply demand balance on the state’s grid. To address this issue, the state relies on importing power from outside of the state as well as energy storage (primarily batteries) to meet electricity demand when renewable energy supply is low. If demand is much less than supply, then likely there will be power exported or some charging of batteries. And if demand is less than total generation in the state, power will be imported and/or batteries will be discharged to make up for the power shortfall.

On the graph, positive values from batteries and imports is when those sources are supplying power to the California grid. Negative values for batteries and exports are when there is excess power in the state and batteries are being charged up or power is being exported to neighboring states.

You can view the graph in two forms:

• Detailed – shows all of the power plant fuel types that is provided in the CAISO data: Solar, Wind, Nuclear, Coal, Other, Natural Gas, Large Hydropower, Small Hydropower, Geothermal, Biomass and Biogas. In addition, it shows aggregated net imports into the state from other regions as well as battery discharging or charging.
• Simplified – I aggregated the categories from CAISO into Solar, Wind, Nuclear, Fossil Fuel (including Coal, Other and Natural Gas), Hydro (Large and Small Hydropower), and Other Renewable (Geothermal, Biomass and Biogas). In addition, it shows aggregated net imports into the state from other regions as well as battery discharging or charging.

Also, I added the ability to see yesterday’s data as well. In the future, I will add the ability to see other dates as well.

Data Sources and Tools
Data for electricity sources for California grid comes from the California Independent System Operator (CAISO). This data from this site is downloaded and processed using a python script and updated every 5 minutes. The graph is made using the open source Plotly javascript graphing library.

Where in the world are babies being born and how fast?

This interactive, animated map shows the where births are happening across the globe. It doesn’t actually show births in real-time, because data isn’t actually available to do that. However, the map does show the frequency of births that are occurring in different locations across the world. And you can see it in two ways, by country and also geo-referenced to specific locations (along a 1degree grid across the globe). There are many different ways to view this global birth map and these options are laid out in the controls at the top of the map. The scrolling list across the bottom also shows the country of each of the dots on the map.

Instructions

• Speed – change the slider to change the rate at which births show up on the map from real-speed to 25x faster
• Map projection – change the map projection
• Highlight country – an outline around the country when a birth occurs
• Choropleth – Build – as each birth occurs, the background color of the country will slowly change to reflect the number of births in the country
• Choropleth – Show – this option colors all the countries to show the number of births per day that occur in the country
• Dots – Show – this is the main feature that shows where each birth is occurring at the frequency that it does occur.
• Dots – Persist – this feature shows where previous births have occurred and the dots get darker as more births happen in that location.

If you hover (or click on mobile) on a country during the animation, it will display how many births have occurred since the animation stared.

Population distribution data combined with country birthrates

I used data that divided and aggregated the world’s population into 1 degree grid spacing across the globe and I assigned the center of each of these grid locations to a country. Then the country’s annual births (i.e. the country’s population times its birthrate) were distributed across all of the populated locations in each country, weighted by the population distribution (i.e. more populated areas got a greater fraction of the births).

Data Sources and Tools
Population and birthrate data for 2023 was obtained from Wikipedia (Population and birth rates). Population distribution across the globe was obtained from Socioeconomic Data and Applications Center (sedac) at Columbia University.

I used python to process country, population distribution data and parse the data into the probability of a birth at each 1 degree x 1 degree location. Then I used javascript to make random draws and predict the number of births for each map location. D3.js was used to create the map elements and html, css and javascript were used to create the user interface.

When does Tioga Pass in Yosemite typically open?

The graph shows the closing and opening dates of Tioga pass in Yosemite National Park for each winter season from 1933 to the present. Tioga pass is a mountain pass on State Highway 120 in California’s Sierra Nevada mountain range and one of the entrances to Yosemite NP. The pass itself peaks at 9945 ft above sea level. Each winter it gets a ton of snow, but also with a great deal of variability, which really affects when it can be plowed and the road reopened.

Our family likes to go to Yosemite in June after the kids school lets out and sometimes Hwy 120 and Tioga Pass can often be closed at this time, which limits which areas of the park you can visit. So I often look at data on when the road has opened before and thought it would be a good thing to visualize.

You can toggle the labels on the graph that show the dates of opening and closing as well as the number of days that the pass was closed each winter. Hovering (or clicking) on the circles on the graph will give you a pop up which gives you the exact date.

Data and Tools
The data comes from the US National Park Service for most recent data as well as Mono Basin Clearinghouse for earlier data going back to 1933. Data was organized and compiled in MS Excel. Visualization was done in javascript and specifically the plotly visualization library.

Update: Added a histogram below main graph to view the difficulty of today’s puzzle in context of historical data (compared to a number of previous puzzles)

What is today’s Wordle difficulty?

Wordle is a game of highs and lows. Sometimes your guesses are lucky (I mean, highly skilled) and you can solve the puzzle easily and sometimes you barely get it in 6 guesses. When the latter happens, sometimes you want validation that that day’s puzzle was hard. This dataviz lets you see how difficult today’s wordle puzzle was for other NY Times Wordle players did.

The graph shows the distribution of guesses needed to solve today’s Wordle puzzle, rounded to the nearest whole percent. It also colors the most common number of guesses to solve the puzzle in green and calculates the average number of guesses. “NS” stands for Not Solved. The lower histogram provides some context for how difficult the day’s puzzle is compared to many other puzzles in the past based on average number of guesses needed to solve the puzzle. It doesn’t include the entire history of wordle, but a subset of days that I was able to gather data on.

Even over 1 year later, I still enjoy playing Wordle. I even made a few Wordle games myself – Wordguessr – Tridle – Scrabwordle. I’ve been enjoying the Wordlebot which does a daily analysis of your game. I especially enjoy how it indicates how “lucky” your guesses were and how they eliminated possible answers until you arrive at the puzzle solution. One thing it also provides is data on the frequency of guesses that are made which provides information on the number of guesses it took to solve each puzzle.

Instructions

Data and Tools
The data comes from playing NY Times Wordle game and using their Wordlebot. Python is used to extract the data and wrangle the data into a clean format. Visualization was done in javascript and specifically the plotly visualization library.