Hilario Calderon

@hicala·11 public vizzes

loreal parsing

This interactive bar chart visualizes survey responses about RuPaul’s Drag Race viewing habits, makeup use, and demographics. Users can toggle between four views—gender, age group, generation, and province—to see the percentage distribution of respondents for each category. The visualization uses D3 v5 to load CSV data, nest and aggregate counts, and render horizontal bars with SVG. Buttons trigger updates to redraw the chart with different aggregated datasets.

Oct 11, 2019

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loreal charts_data separations

This example shows a horizontal bar chart that visualizes the percentage of survey respondents by Canadian region, with each bar labeled at its end with the corresponding percentage value and a percentage-formatted x-axis. The chart uses D3 v5’s `csv` loader to parse the dataset, `scaleLinear` and `scaleBand` for positioning, and `axisLeft` and `axisBottom` to render the axes while hiding tick lines via CSS. Data is aggregated using `d3.nest` with a `rollup` function that calculates the proportion of entries per region.

Oct 11, 2019

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loreal charts_axes customization

This example shows a horizontal bar chart of age-group percentages derived from survey data about RuPaul’s Drag Race viewership and makeup habits. The chart customizes the axes by hiding tick lines, formatting x-axis labels with a percentage sign, and positioning value labels at the end of each bar. Using d3.csv, d3.nest, d3.scaleBand, d3.scaleLinear, d3.axisLeft, and d3.axisBottom, the code processes the data and renders the visualization with SVG rect and text elements.

Oct 11, 2019

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loreal dataviz updates

This interactive bar chart displays survey respondent demographics, with buttons to toggle between gender, age group, generation, and province categories. The horizontal bars show the percentage of respondents in each category, with labels indicating the exact values. Using d3.v5, the visualization loads CSV data, computes grouped percentages via `d3.nest()`, and renders SVG rectangles with animated transitions. Axes and labels are generated with `axisLeft`, `axisBottom`, and `scaleBand`, while button clicks trigger the `update` function to swap datasets.

Oct 9, 2019

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loreal_data transitioning

This example demonstrates how demographic survey data can be interactively explored by switching between different categorical groupings. The bar chart displays the percentage distribution of respondents across gender, generation, province, or age group, with the selected category updating the visualization. Built with D3 v5, the code loads data from a CSV file and uses `d3.nest()` with `rollup` functions to aggregate counts into percentages. The SVG rendering employs `scaleLinear` and `scaleBand` for the axes, with buttons triggering the data swap and horizontal bars displaying percentage labels.

Oct 3, 2019

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loreal charts

This bar chart displays the count of survey respondents grouped by gender, with the data sourced from a CSV file containing responses about RuPaul’s Drag Race viewing habits and makeup usage. The visualization uses d3.nest() to aggregate records and d3.scaleBand for the categorical y-axis, d3.scaleLinear for the quantitative x-axis, and d3.axisLeft and d3.axisBottom to render axes. The SVG rendering shows horizontal bars with steelblue fills, highlighting the distribution of male versus female participants in the dataset.

Sep 27, 2019

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Making a Bar Chart

A horizontal bar chart ranks ten countries by population using data from a CSV file, with population values converted from thousands to absolute numbers. The visualization uses D3 v5 scales (`scaleLinear` and `scaleBand`) to map data to SVG rectangles, with `axisLeft` and `axisBottom` generating the country labels and population axis. The chart displays population values as bar lengths, styled with steelblue fills, within an SVG canvas of 960 by 500 pixels.

Sep 27, 2019

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Making a Bar Chart

Sep 27, 2019

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Tutorial

This chart shows a horizontal bar graph comparing population values for individual names, with each bar’s length proportional to the amount from the dataset. The code loads data from a CSV file, multiplies each amount by 1,000, and renders it using D3 v5 with SVG. It uses `d3.scaleLinear` for the x-axis and `d3.scaleBand` for the y-axis, while `d3.axisLeft` and `d3.axisBottom` generate the labeled axes. The bars are drawn as `rect` elements with a steelblue fill.

Sep 27, 2019

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Making a bar chart: my grades

A bar chart displays university grades, with each subject on the y-axis and its corresponding score (from 18 to 30) on the x-axis. The chart uses green bars and a readable font size. The implementation relies on D3 v5's `scaleLinear`, `scaleBand`, `axisLeft`, and `axisBottom` APIs to position and scale the marks. Data is loaded from a CSV file via `d3.csv`, and the SVG rendering is created through `svg.append('g')` and `selectAll('rect')` calls.

Sep 27, 2019

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Hello VizHub

This example shows a simple text rendering that greets viewers with “Lesson 1” on a dark blue background. It uses D3 v5’s `select` API to target a `div` with the id `message` and set its text content. The text is styled via CSS, importing the Ubuntu font from Google Fonts and setting a large font size. The code demonstrates ES6 module imports, with the message string stored in a separate `myMessage.js` file, and includes a local `bundle.js` script for execution.

Sep 24, 2019