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Smulgumman

@Smulgumman·22 public vizzes

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Infovis

This visualization displays Swedish municipal data as a scatterplot, plotting municipal tax rate on the x-axis against average income on the y-axis. Circle size encodes average age across the population. The code uses d3.csv to load the data, d3.scaleLinear for all three axes, and d3.axisBottom and d3.axisLeft for the chart’s gridlines and labels. A dropdown menu, built with a custom dropdownMenu function, is also included in the interface. The visualization renders as SVG circles with a steelblue fill and white stroke.

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This scatterplot displays Swedish municipal statistics, plotting municipal tax rate against average income, with circle size encoding mean age and color representing municipalities. Users can interact with a dropdown menu to switch between different data attributes. The visualization uses D3 v5 with SVG rendering, employing d3.scaleLinear for axes and circle sizing, d3.axisBottom and d3.axisLeft for gridlines, and d3.csv to load the dataset. Circle opacity and styling are set via CSS.

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This scatterplot uses Swedish municipal data to reveal relationships between local tax rates, average income, and mean age. Each circle represents a municipality, positioned by tax rate and income, with its radius encoding average age. The visualization uses D3 v5's `scaleLinear`, `axisBottom`, and `axisLeft` to construct the chart from the CSV data, rendered as SVG. A dropdown menu component is also included, though its options are not yet connected to interactive filtering.

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A scatterplot of Swedish municipalities shows the relationship between municipal tax rate and average income, with circle size encoding mean age. Each point represents a municipality, colored in semi-transparent steel blue over a white stroke. The visualization uses d3.scaleLinear for x, y, and radius scales, d3.axisBottom and d3.axisLeft for gridlines, and SVG circles rendered from data parsed from a local CSV file. A dropdown menu, powered by a custom dropdownMenu function, is present but currently offers only placeholder options.

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This visualization shows the relationship between municipal tax rates and average income across Swedish municipalities, with circle size encoding the median age of each municipality’s population. The scatterplot uses `d3.scaleLinear` for the x and y axes, `d3.axisBottom` and `d3.axisLeft` for grid lines, and `d3.svg` for rendering circles. Data is loaded from a CSV file containing demographic and economic metrics for each region.

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This example shows a bar chart of municipal income tax rates for Swedish regions, with each region listed on the y-axis and its tax rate represented by the bar length on the x-axis. It uses d3.csv to load the data, d3.scaleLinear and d3.scaleBand for the scales, and d3.axisLeft to render the region labels. The SVG rendering approach draws steelblue rectangles for each bar.

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A horizontal bar chart shows municipal income tax rates across Swedish regions, sorted by region name. The chart uses D3 v5 with a scaleLinear for the x-axis and scaleBand for the y-axis, rendering SVG rectangles whose widths encode each region's tax percentage. Data is loaded from a CSV file containing regional statistics, with axes generated via axisBottom and axisLeft.

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A horizontal bar chart shows municipal income tax rates across Swedish regions, sorted by region name. The chart uses D3 v5 with a scaleLinear for the x-axis and scaleBand for the y-axis, rendering SVG rectangles whose widths encode each region's tax percentage. Data is loaded from a CSV file containing regional statistics, with axes generated via axisBottom and axisLeft.

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This bar chart visualizes municipal tax rates across Swedish regions (kommuner), using horizontal bars to compare the Kommunal skattesats for each region, sorted by region name. Built with D3 v5, the visualization uses `scaleBand` for the categorical y-axis, `scaleLinear` for the continuous x-axis, and SVG rectangles to represent each region’s tax percentage. Data is loaded from a local CSV file and rendered in a static, scrollable SVG canvas.

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A bar chart displays the municipal tax rate for each Swedish region, sorted alphabetically by region name. The chart uses a linear scale for the tax rate values and a band scale for the region categories. Built with D3 v5, the visualization loads data from a CSV file using `d3.csv` and renders SVG rectangles, with the data parsed and converted to numeric values before being passed to the render function.

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This visualization shows the municipal tax rate for each Swedish region as a bar chart, with bars representing the tax percentage on a linear scale. The region names are mapped to the x-axis using `scaleBand`, while the tax rates are scaled with `scaleLinear`. The SVG rectangles are generated using D3 v5’s `select` and `csv` methods, with data loaded from a local CSV file containing demographic and economic statistics. The chart is rendered directly into the page’s SVG element.

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A bar chart displays municipal tax rates across Swedish regions, with each bar representing a region’s local tax percentage. The visualization uses D3 v5’s `scaleBand` for the x-axis and `scaleLinear` for the y-axis, rendering SVG rectangles. Data is loaded from a CSV file and parsed with D3’s `csv` method. The chart highlights variation in tax rates, though axis labels and scales are not explicitly drawn.

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A bar chart visualizes municipal tax rates across Swedish regions, using a dataset of demographic and economic indicators. Each bar is sized statically at 300 by 300 pixels along both axes. The visualization relies on d3.csv for data loading, d3.scaleBand for categorical x-axis scaling, and D3 selections to append SVG rectangles. The current implementation appears incomplete, as scales and axes are not fully configured or rendered.

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This example visualizes municipal data from a CSV file, mapping regions to rectangular blocks without encoding any numeric values into visual properties; it merely displays the data. The code uses D3 v5 to load and parse the data, then applies a band scale to potentially position the rectangles. However, it only appends fixed-size rectangles using SVG, relying on the `csv` and `scaleBand` APIs. The visualization does not yet implement meaningful geometry, color, or axes.

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Let's make a face with D3.js!

This example visualizes Swedish municipal statistics using D3.js v5, mapping socio-economic data such as average income, population, and tax rates. It loads external CSV data with d3.csv and logs the parsed values to the console. The visualization renders to an SVG canvas, with the title hinting at a playful, face-like composition of data points. While the code currently only parses and logs the dataset, it sets up the infrastructure for a custom scatterplot or shape-based chart using D3's data-joining capabilities.

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Let's make a face with D3.js!

A playful scatterplot maps Swedish municipal statistics onto facial features in an SVG, using D3.js v5 to load and parse CSV data. Each municipality becomes a point with attributes like income and population determining facial expressions and positions. The code demonstrates data binding and event handling through D3 selections, though the visible implementation focuses on parsing and logging the dataset.

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Let's make a face with D3.js!

This example uses D3.js version 5 to visualize Swedish municipal statistics loaded from a CSV file. The code parses numeric columns such as average income, tax rate, and population, then logs the resulting array to the console. While the page includes an SVG element and imports the `arc` function, the visualization itself is incomplete—no shapes or face are actually drawn in the provided code. The example relies on `d3.csv` for data loading and `select` for DOM manipulation.

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This example displays municipal income-tax rates for Swedish regions as a bar chart, with each bar’s height mapped to the tax percentage. The code uses D3 v5’s `scaleBand` and `scaleLinear` to set the x- and y-axis ranges, and appends SVG rectangles bound to the CSV data. While the script logs the parsed numeric values for all eight dataset columns, only the tax-rate column is visualized. The bars are positioned without explicit x-coordinates, relying on D3’s band scale to place them sequentially across the width.

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This example shows a bar chart of the municipal tax rate for each Swedish region, with each bar’s height mapped to the tax rate. The code loads data from a CSV file and uses D3’s `scaleBand` for the x-axis, `scaleLinear` for the y-axis, and `csv` for parsing. The SVG canvas is 960 by 500 pixels, with bars rendered as `rect` elements whose positions and heights are set via D3 selection methods.

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This visualization displays statistics for Swedish municipalities, showing each region’s communal tax rate as a bar chart. The bars are sized with `d3.scaleBand` for the x-axis and `d3.scaleLinear` for the y-axis. Data is loaded from a CSV file and parsed with d3.csv. The SVG is populated with rectangles for each region, rendered using d3 v5.

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This visualization displays demographic and economic statistics for Swedish municipalities, showing each region’s average income, tax rate, student population, median age, housing stock, migration patterns, and total population. The code loads data from a CSV file using D3’s `csv` method, parses numerical fields, and prepares a band scale (`scaleBand`) for positioning regions along the x-axis. The visualization currently sets up the SVG canvas and data-loading pipeline but does not yet render any marks, leaving the display incomplete. The implementation relies on D3 v5 and outputs to an SVG element.

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This visualization uses D3 v5 to display Swedish municipal data from a CSV file. It plots each region as a circle on an SVG canvas, with position and size likely derived from attributes like population, income, or other socio-economic variables. The code loads the data with D3's `csv` function, converts string values to numbers, and logs the parsed dataset to the console. The rendering relies on SVG elements, styled with Bootstrap and custom CSS.