Skip to main content
SimilarExport ZIP
100%

London Marathon Finish Times 2016

✓ Published0🌍 Public
CColinEberhardt
Last edited May 28, 2019
Created on Jan 25, 2017

A histogram shows the distribution of finish times for 7,190 London Marathon 2016 finishers, with finish times in one-minute bins on the x-axis and frequency on the y-axis. The data comes from Strava athlete records. The visualization uses `d3.nest` to group finish times, `fc.seriesSvgBar` with `fc.autoBandwidth` for the bars, `fc.annotationSvgGridline` for gridlines, and `fc.chartCartesian` to assemble the chart, with `d3.timeFormat` for labeling the time axis.

AI-generated description

The distribution of finish times for 7,190 London Marathon 2016 finishers as obtainer from strava athletes data. This is a relatively straightforward demonstration of a few d3fc components:

  1. The d3.nest component is used to bucket the finish times by the minute.
  2. The d3fc bar series is configured to render this data.
  3. The bar series is rendered, along with the d3fc gridlines within a cartesian chart.
mit Licensed

Similar vizzes

Loading thumbnail…

London Marathon Athlete Splits 2016

The chart visualizes the pacing of 7,190 London Marathon 2016 finishers as a series of thin line plots, showing speed in mph across the 26-mile course, with red annotation lines marking target finish times. Below the main chart, an elevation profile displays the route's gradient changes using colored bars. The implementation uses d3 and d3fc components, including `fc.seriesSvgMulti`, `fc.seriesSvgLine`, and `fc.areaSvgBar`, with data parsed from a CSV file and elevation values supplied inline.

CColinEberhardt
84% match
Loading thumbnail…

London Marathon 2016 Pacing vs. Finish Time

This chart visualizes pacing strategies for 7,190 finishers of the 2016 London Marathon, using Strava athlete data. It shows the average speed (in mph) across each mile, with seven colored bands representing different finish-time ranges, from fastest to slowest. The visualization uses D3 and d3fc components, including `d3.nest` and `d3.pairs` to aggregate and pair the split data, and d3fc line annotations for the finish-time labels on the right. The `d3-scale-chromatic` spectral color scale distinguishes the bands.

CColinEberhardt
84% match
Loading thumbnail…

Training miles vs finish time

A scatterplot shows the relationship between average weekly training miles and finish time for 1,000 London Marathon 2016 finishers, using data from Strava athletes. Points cluster with higher mileage generally associating with faster finish times. A line connects median miles within each half-hour finish-time bin. The chart uses d3.csv for loading, d3.histogram for binning, and d3fc’s chartCartesian, seriesSvgPoint, and seriesSvgLine components for rendering.

CColinEberhardt
79% match
Loading thumbnail…

London Marathon Negative Splits

This visualization shows the distribution of split ratios for 7,190 London Marathon 2016 finishers, comparing each runner’s second-half time minus their first-half time. It groups runners by total finish time in one-hour buckets, rendering horizontal histograms with green bars for negative splits and orange for positive ones. Each panel displays the proportion of negative splits and the mode split. The chart uses d3 and d3fc components, including `d3.histogram`, `fc.seriesSvgBar`, and `d3.nest`, with data sourced from Strava athlete data in a CSV file.

CColinEberhardt
78% match
Loading thumbnail…

Weekly training days

This chart shows the average number of training days per week for approximately 1,000 London Marathon 2016 finishers, with data sourced from Strava athletes. Four lines, each representing a different weekly training-hour range, plot values across an 18-week schedule. The visualization uses d3 and d3fc components, including `fc.seriesSvgRepeat`, `fc.seriesSvgMulti`, and `fc.chartCartesian`, to render SVG points and lines. A d3 color scale with a legend distinguishes the categories, while gridlines and axis labels are added via d3fc annotations.

CColinEberhardt
77% match
Loading thumbnail…

Marathons with Most Finishers in 2018(As of 9/11)

This horizontal bar chart ranks the top ten marathons by finisher count in 2018, with the Boston Marathon leading at 25,746 finishers and the Vancouver Marathon last at 3,758. The visualization uses D3 v5’s `scaleLinear`, `scaleBand`, `axisLeft`, and `axisBottom` to map finisher values to bar widths and race names to vertical bands. Data is loaded from a local CSV file via `csv()` and rendered as SVG rectangles in purple. The chart’s left margin is widened to accommodate long race names, and the source is attributed to findmymarathon.com.

NNikkor
72% match
Loading thumbnail…

Weekly marathon training mileage

The chart compares weekly training mileage for the 2016 London Marathon, broken down by four weekly training-hour brackets, from 1 to 17 weeks before the race. Four multi-series lines, one per bracket, rise and fall in a similar pattern, with a sharp taper in the final two weeks. Built with d3fc components, it uses `seriesSvgMulti`, `seriesSvgLine`, and `seriesSvgPoint` over an SVG Cartesian chart, with a d3-legend color legend mapping the categorical color scale. Data comes from the included CSV of Strava athlete mileage.

CColinEberhardt
70% match
Loading thumbnail…

Weekly mileage vs. Marathon training plans

This visualization compares weekly training mileage for London Marathon 2016 finishers (from Strava athlete data) against four Runners World training plans targeting sub-3:00 to sub-4:30 marathons. Each panel shows a shaded area between the plan’s upper and lower mileage bounds, overlaid with the actual average finisher mileage per week. The code parses CSV data with `d3.csvParseRows`, then builds small multiples using `fc.chartCartesian`, `fc.seriesSvgArea`, `fc.seriesSvgLine`, and `fc.annotationSvgGridline` from d3fc, with scales from `d3.scaleLinear`.

CColinEberhardt
69% match