A simple visualization illustrtion the 100-year Global Warming Potential for carbon dioxide (CO2), methane (CH4), and nitrous oxide (N20).
A simple visualization of inpulse response functions for carbon dioxide and methane emissions. These functions help scientists quantify Global Warming Potentials.
A framework for creating Dot Maps in d3.js using d3.geom.quadtree and Mitchell’s Best-Candidate (MBC) algorithm as its backbone. Here, I show the percentage of California residents who rent on a county basis.
The rendering speed is very slow due to the recursive MBC calls and small circle areas. However, it is worth the wait if all you are trying to do is download a map for a report.
A simple simple way to represent percentages on a map. Data: Percentage of residents who rent.
| exporting_country,United States,China,Germany,France,United Kingdom,Japan,Italy,Canada,Korea,Spain,Netherlands,India,Mexico,Belgium,Russian Federation,Australia,Switzerland,Chinese Taipei,Brazil,Singapore,Poland,Ireland,Sweden,Saudi Arabia,Austria,Malaysia,Turkey,Thailand,Denmark,Indonesia,Czech Republic,Norway,Greece,Finland,Hungary,"Hong Kong, China",Portugal,Viet Nam,South Africa,Luxembourg,Israel,Slovak Republic,Romania,Philippines,Argentina,Chile,New Zealand,Bulgaria,Slovenia,Lithuania,Latvia,Estonia,Cyprus,Cambodia,Malta,Iceland,Brunei Darussalam | |
| United States,1,111955.9,74435,51782.3,77745.3,89562.1,24319.9,213176.9,44279.2,21442.1,33111.1,28761.5,126533.1,15768.9,13912.6,28923.3,12717.2,24182.8,33361.2,25467.1,6441.3,44732.8,11847.8,18816.2,6383.9,19952.4,9994.3,12478.9,9168.9,11288.5,3893.6,8359.9,6815.9,5666.1,4141.2,9852.9,2673.7,4453.2,7556.4,5353.9,11168.5,1673.4,1887.7,8626.4,8175.5,9872.5,4132.5,1114.5,1297.4,778,656.4,676,734.7,843.3,635,687.3,592.7 | |
| China,289963.9,1,68753.2,42191.1,39545.3,111 |
Simple example of displaying a route in Leaflet using d3.js.
Particles flowing along a gradient.
A simple example of 0/1 Knapsack Problem Dynamic Programming in d3.js.
Items are first ranked according to weight. Next, at each stage (e.g., item:capacity combination) in the algorithm, the model assesses whether adding a new item (row) improves the solution at that paritcular weight capacity (column). If so, it adds the new item and updates the best solution; otherwise, it obtains the previous best solution. Click the tiles to examine each step.
Once the final solution is found, the model back calculates the optimum item set. Rows with highlighted tiles (blue) correspond to items in this set.
Note: This model purposefully shows only one solution. Can you determine when multiple solutions exist?
A simple interface for visualizing the marginal effects on fuel combustion given a change in vehicle attributes.
Economic Input-Output Life Cycle Assessment (EIO-LCA) is a method to quantify the material, energy, and environmental impacts resulting from activities in our economy. The Economic Input-Output (EIO) method was first formalized by Nobel Prize winning economist, Wassily Leontief, in the 1970s. It took two decades before the computation performance of modern computers was sufficient enough to utilize this model at scale. Since the mid-1990s, EIO-LCA has been used to estimate economy-wide environmental impacts of many products and services, such as automobiles, refrigerators, computers, paper, retail trade, food systems, etc.
In this illustrative example, I model a simple economy consisting of three industrial sectors: steel, electric