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@amccartney·6 public vizzes
This visualization ranks every table in a PostgreSQL database by its live row count, displaying the table names and schemas in descending order. The horizontal bar chart makes it immediately clear which tables dominate the database in size and how quickly the counts taper off. The data comes from the `pg_stat_user_tables` system view, which tracks `n_live_tup` (an estimate of live rows). The query runs directly against PostgreSQL, returning `schemaname`, `relname`, and `n_live_tup` for each table, and the chart renders those values as proportional bars.
This example demonstrates how to build a search index for contract records using Elasticsearch, Django, and Haystack. It shows the configuration of a Haystack connection to an AWS Elasticsearch instance with request signing via `requests_aws4auth.AWS4Auth`, and defines a `ContractIndex` class that indexes fields like fiscal year, dollars obligated, and transaction status. The code uses Haystack’s `indexes.CharField` and `indexes.DecimalField` to map model attributes, with a template-based `text` field for full-text search. It also includes Django REST Framework and `drf-haystack` for API integration, though the visualization behavior itself is not depicted.
This example walks through the process of building a static website with Jekyll and deploying it to Amazon Web Services’ S3 hosting. It shows a step-by-step tutorial covering environment setup, theme installation, local testing, and customization. The visualization illustrates the workflow with a series of screenshots and code snippets, making the deployment process clear and accessible.
The example resolves multiple related JSON objects into a single school detail view, aggregating expense records by school ID. It uses D3.js to group and sum expense amounts, then displays the school name, ID, total expenses, and ranked expense categories in a styled HTML dashboard. The data comes from a static sample array of Django objects, and the front-end renders the summary via D3 selections and text nodes. No interactive simulation or canvas rendering is used; the visualization relies solely on D3’s data-binding and DOM manipulation.
This example visualizes 15 years of U.S. federal contract data for a specified company, scraped from USASpending.gov. The code uses bash scripting with `curl` to download XML files by fiscal year, then converts them to JSON using `xml2json`, and cleans the output with `sed` to remove namespace prefixes. The resulting JSON files are stored per year, ready for further analysis or visualization.
A single cyan circle and a horizontal aquamarine bar are drawn on an aliceblue SVG canvas. The circle is positioned at coordinates (50, 50) with a large radius of 500, while the bar spans the full width of the 960-by-300 viewport with a dashed aqua stroke. The visualization uses D3.js version 3.5.5 to set up the SVG container, with circle and rectangle elements styled directly via SVG attributes. No data or interactive behavior is present; the example simply demonstrates basic geometric shapes and SVG styling properties.