OrhanYaz

@OrhanYaz·14 public vizzes

Trend Chart (Area + Line)

This trend chart illustrates loading times across releases of a hypothetical web application, combining a line chart and area chart to display the daily median loading time as a black line and percentile ranges as surrounding shaded areas. The "lollipop" markers indicate application releases, with animated transitions. Built with D3.js v3, the visualization uses `d3.svg.area` and `d3.svg.line` to construct the paths, rendering to SVG with clipping and a legend.

Apr 5, 2017

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Mass Shootings

This interactive map visualizes over 1,000 US mass shooting events from January 2013 to early December 2015, grouped by week. Scaled circles represent dead or injured counts, with red indicating fatalities and orange injuries; clicking reveals event metadata and media links. A draggable, resizable brush on the weekly bar chart filters the map, while an animation control cycles through weeks. Built with D3.js, Crossfilter.js, and Mapbox GL, it loads GeoJSON data from ShootingTracker.com and renders SVG with animated transitions.

Apr 5, 2017

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Interactive line chart

This interactive line chart displays monthly values from January to December 2016, with each data point represented as a labeled circle along a single black line. Hovering over a circle highlights it in red, enlarges its corresponding value label, and reveals a dashed vertical guide line. Built with D3 v3, the visualization uses an ordinal x-scale, a linear y-scale, and SVG elements including paths, circles, and text. Data loads from a local JSON file via `d3.json`, with dates parsed using `d3.time.format` and values formatted with `d3.format`.

Mar 28, 2017

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fresh block

This visualization shows a time series of stock prices for multiple entities (Angers, Monaco) over a year, with each actual price point accompanied by a cascade of up to 38 forecasted values (pred1 through pred38) drawn as separate steel-blue lines. The D3.js v3 code defines multiple `d3.svg.line` objects, one per prediction horizon, all sharing a time-scaled x-axis and linear y-axis. The SVG paths are animated, and the data is loaded from a CSV file, with axes formatted using `d3.svg.axis` and dates parsed via `d3.time.format`. The chart emphasizes how forecasts progressively converge or diverge from the observed price series over time.

Jan 9, 2017

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fresh block 2

The visualization displays the league table positions of four French football teams—Angers, Monaco, Saint-Etienne, and Guingamp—across 38 matchdays of the 2015-2016 season. Each team is represented by a colored line that traces its weekly rank, with a lower y-axis position indicating a higher league standing. The chart uses D3 v3 to render SVG paths, applying a basis interpolation to smooth the lines. Data is loaded from a semicolon-delimited CSV file using `d3.dsv`, and scales are defined with `d3.scale.linear`. The y-axis is generated via `d3.svg.axis`, while each line is created with `d3.svg.line`.

Jan 2, 2017

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Grippe 2003-2015

This animated choropleth map shows influenza case counts across French regions from 2003 to 2015, with a slider letting viewers step through weekly data. The visualization uses D3 v3 with `d3.geo.conicConformal` projection and `d3.geo.path` to draw regions, while a quantile color scale encodes case values. Hovering highlights a region and displays its name and weekly count via a tooltip. Data comes from a CSV file loaded with `d3.queue` and merged into a GeoJSON object.

Dec 7, 2016

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Grippe 2014

A choropleth map of France displays regional influenza case counts for November 2014, using a green color scale to indicate relative intensity. The map uses D3's geo projection and path rendering to draw the regions, with data from a CSV file merged with a GeoJSON of French regional boundaries. Hovering over a region triggers a tooltip showing its name and total case count, while the region's opacity dims on interaction.

Dec 1, 2016

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Grippe 2014

A choropleth map of France shows the total influenza cases reported in each administrative region during November 2014, using a green color scale. The map renders French regional boundaries from a GeoJSON file and merges them with weekly case counts from a CSV dataset, summing the five November weeks per region. The visualization uses D3 v3's `d3.geo.conicConformal` projection and `d3.geo.path` for map drawing, with `d3.scale.quantize` mapping summed values to colors. Hovering over a region triggers a tooltip displaying the region name and its total case count.

Nov 24, 2016

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Gist 64174c24e41df28d6d2ea7a35a185651

A choropleth map of metropolitan France depicts the total weekly influenza cases for each region during November 2014, aggregated from the CSV data. Regions are colored on a green scale using a d3.scale.quantize, with darker shades indicating higher case counts. The map uses d3.geo.conicConformal projection and d3.geo.path to render GeoJSON features, and hover interactions display region names via a tooltip while dimming the selected path.

Nov 24, 2016

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Interactive line chart

A static line chart plots monthly values from a JSON dataset, with month labels along the x-axis and a black line connecting points. Hovering over a circular point highlights it in red, enlarges its value label, and reveals a dashed vertical guide line. Built with D3 v3, the visualization uses ordinal and linear scales, SVG paths for the line, and interactive mouseover and mouseout events to toggle element visibility and opacity.

Nov 24, 2016

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Gist 7318a250abd12cc0d3e1181da3f1ecb0

This example shows a choropleth map of France, coloring each administrative region according to the cumulative number of flu cases reported during November 2014. The data is loaded from a CSV file and joined to GeoJSON features by region name. The map uses `d3.geo.conicConformal` projection and `d3.geo.path` to render the regions, with a `d3.scale.quantize` color scale mapping summed weekly values to a green color ramp. Hovering over a region displays its name in a tooltip.

Nov 24, 2016

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Gist b15a0719d472a2a011176c8a2677efb8

A choropleth map of metropolitan France shows cumulative influenza cases per region for November 2014, using a five-step green color scale applied to regional polygons. The visualization loads CSV data with weekly case counts per region and a GeoJSON file of French regions, merging them by regional name to calculate the November total. Built with D3 v3, it uses `d3.csv`, `d3.json`, `d3.geo.path` with a conic conformal projection, and `d3.scale.quantize` for color mapping, with hover tooltips displaying region names.

Nov 24, 2016

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Gist 54ef66cc8b6ee717b9f33d505ce60940

A choropleth map of France shows the total number of influenza cases reported in 2014 for each administrative region. The map uses a green color scale, with darker shades representing higher case totals, and grey for regions without data. The visualization is built with D3 v3, using `d3.geo.conicConformal` for the map projection and `d3.geo.path` to render the GeoJSON boundaries. CSV data is joined to the geographic features, with a quantize scale mapping summed annual case counts to the color range.

Nov 24, 2016

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Kernel K-means.

This example demonstrates kernel k-means clustering, which extends standard k-means to nonlinear decision boundaries by computing distances in a kernel-induced feature space. The code, written by Mathieu Blondel, implements a custom `KernelKMeans` estimator using scikit-learn’s `BaseEstimator` and `ClusterMixin`, with distance calculations based on pairwise kernels from `sklearn.metrics.pairwise`. It generates synthetic blob data via `make_blobs` from `sklearn.datasets` and fits the model with a linear kernel by default, printing predicted labels for the first ten samples. The implementation iteratively reassigns clusters while monitoring convergence via a tolerance threshold.

Nov 14, 2013