ICE5

ICE5

This example presents a data-driven summary of stolen property statistics for each state. The visualization page displays a concise metadata readout of the underlying dataset, showing its file size in kilobytes, the total number of rows, and the number of columns. The code fetches the CSV data from a GitHub Gist using the D3.js `d3.csv` method, then calculates and formats the metadata with `d3.csvFormat`. The resulting text message is injected into an HTML `<pre>` element. The page uses D3 v7 and CSS for its minimal presentation.

92% match

Fork of ICE5

This example displays the metadata of a CSV dataset about property stolen and recovered in each state. It loads the data using d3.csv and presents the row and column counts in a pre-formatted text container on the page. The visualization relies on D3 v7 for data fetching and basic DOM manipulation, while the layout is styled with CSS and structured with plain HTML.

86% match

ICE5

This example displays metadata about a dataset of property stolen and recovered in each state. It loads a CSV file from a GitHub gist using `d3.csv`, then counts the number of rows and columns in the data. The resulting message, which states the dataset contains a certain number of rows and columns, is written into a `<pre>` element via `document.getElementById`. The page is styled with CSS and uses D3 v7 for data fetching and parsing.

86% match

Fork of Fork of ICE5

This example displays the count of rows in a dataset about property stolen and recovered in each state. The visualization is a minimal HTML page that loads data from a CSV file hosted on GitHub using the `d3.csv` API from d3.v7. The code retrieves the CSV, counts the number of rows, and writes a message with that metadata to a `<pre>` element via `document.getElementById`. The page uses CSS for styling and is built with React, though the current implementation only shows static text output.

83% match

ICE5

This visualization displays a summary of used car data loaded from a remote CSV file, showing its size in kilobytes, row count, and column count. The page also embeds an external SVG image. The code uses the D3.js library, specifically the `d3.csv` function to fetch and parse the data, along with `d3.csvFormat` to calculate the data size. The message is rendered into an HTML `<pre>` element. The visualization utilizes D3 v7 within a React framework, though the displayed content focuses on basic data characteristics.

GGARIDIDEEKSHITHREDDY

ICE5

This page shows metadata about an electronics sales dataset, summarizing its size, row count, and column count in a text overlay. The visualization loads a CSV file from a GitHub gist using D3 v7’s `d3.csv` method, then computes the file size from the formatted CSV string’s length in kilobytes. It also counts the number of rows and columns from the parsed data, displaying all three metrics in a large red monospace block. A background SVG image and a link to the raw dataset are included as supplementary information.

Ddheeraj1509

ICE 5

This example shows tenant data from a linked CSV file, displaying the dataset’s size in kilobytes, row count, and column count. The page loads the CSV using the d3.csv method, then formats and computes the statistics with d3.csvFormat and the data’s length and columns properties. The visualization is built with D3 v7 and React, presenting the information as plain text. The background is a static SVG image of apartments, with the title and link displayed prominently.

RReyden Harris

ICE5

This visualization presents a summary of an Amazon product dataset, displaying the dataset's file size and row count on a page with a background image. It uses d3.csv to fetch a remote CSV file and d3.csvFormat to calculate the data size. The page displays the total number of rows and the size in kilobytes, providing a basic overview of the data about product names, prices, and ratings. The visualization is a simple text-based summary rather than a graphical chart.

Ggeethikal