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This choropleth encodes unemployment rates from 2008 with a quantize scale ranging from 0 to 15%. A threshold scale is a useful alternative for coloring arbitrary ranges.

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This simple force-directed graph shows character co-occurence in Les Misérables. A physical simulation of charged particles and springs places related characters in closer proximity, while unrelated characters are farther apart. Layout algorithm inspired by Tim Dwyer and Thomas Jakobsen. Data based on character coappearence in Victor Hugo's Les Misérables, compiled by Donald Knuth.

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This simple line chart is constructed from a TSV file storing the closing value of AAPL stock over the last few years. The chart employs conventional margins and a number of D3 features:

• d3.tsv - load and parse data
• d3.time.format - parse dates
• d3.time.scale - x-position encoding
• d3.scale.linear - y-position encoding
• d3.extent - compute domains
• d3.svg.axis - display axes
• d3.svg.line - display line shape

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This simple line chart is constructed from a TSV file storing the closing value of AAPL stock over the last few years. The chart employs conventional margins and a number of D3 features:

• d3.tsv - load and parse data
• d3.time.format - parse dates
• d3.time.scale - x-position encoding
• d3.scale.linear - y-position encoding
• d3.extent - compute domains
• d3.svg.axis - display axes
• d3.svg.line - display line shape

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This simple line chart is constructed from a TSV file storing the closing value of AAPL stock over the last few years. The chart employs conventional margins and a number of D3 features:

• d3.tsv - load and parse data
• d3.time.format - parse dates
• d3.time.scale - x-position encoding
• d3.scale.linear - y-position encoding
• d3.extent - compute domains
• d3.svg.axis - display axes
• d3.svg.line - display line shape

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An example of d3.behavior.zoom and d3.geo.path. By modifying the transform, the browser can rapidly redraw geographic features while panning and zooming, without the overhead of reprojection. This technique can be extended by combining with d3.geo.tile.

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An example of multiple pie (donut) charts created with D3. The data is represented as a tabular array of objects; each row in the table is mapped to an arc, and rows are grouped into pie charts using d3.nest.

http://stackoverflow.com/questions/18668271/apply-d3-nest-rollup-to-nested-pie-chart-to-vary-the-size-of-the-pies

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Created for http://stackoverflow.com/questions/18809020/accessing-properties-of-objects-in-d3-histogram-bins

This chart shows a histogram of an Irwin–Hall distribution. The data is randomly generated. The values are then binned at regular intervals using D3’s histogram layout. The x-axis uses a linear scale, such that the tick values appear between bars; this provides better indication that each bar represents the count of values between its surrounding tick values.

See also this histogram of a log-normal distribution of time durations.

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By adding transitions, we can more easily follow the elements as they are entered, updated and exited. Separate transitions are defined for each of the three states.

Note that no transition is applied to the merged enter + update selection; this is because it would supersede the transition already scheduled on entering and updating elements. It's possible to schedule concurrent elements by using transition.transition or by setting transition.id, but it's simpler here to only transition the x-position on update; for entering elements, the x-position is assigned statically.

Want to read more? Try these tutorials:

• Thinking with Joins
• Nested Selections
• Object Constancy

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Fire event during a transition

https://github.com/mbostock/d3/wiki/Transitions#wiki-attrTween

https://github.com/mbostock/d3/wiki/Transitions#interpolation