DATA VISUALIZATION

DATA VISUALIZATION

This example displays a text summary of a population dataset from the 2018 United Nations World Population Prospects, presenting the file size, row count, and column count in a terminal-style black-and-green interface. It loads a CSV file from a GitHub gist using the `d3.csv` method, then computes the data’s size in kilobytes with `d3.csvFormat` and appends the tabular dimensions to a `<pre>` element. The visualization relies on D3 v5 and demonstrates basic data loading, formatting, and DOM manipulation.

Aajaysonu

93% match

Data Table Summary

This example displays a plain-text summary of a CSV dataset containing 2018 population estimates for the most populous countries, sourced from the United Nations World Population Prospects. It shows the total row and column counts, the dataset size in kilobytes, and the first ten rows as formatted JSON. The visualization uses D3 v5’s `csv` loader to fetch the data, `csvFormat` to calculate file size, and `select` to append `<pre>` elements with the summary information. A minimal black-and-green terminal aesthetic is applied via CSS.

MMukund Khandelwal

Data Table Summary

This example summarizes a CSV of 2018 population estimates from the United Nations World Population Prospects. It displays the number of rows, columns, and file size in kilobytes, followed by the first ten rows as formatted JSON. The code uses `d3.csv` to load the data, `d3.csvFormat` to calculate its byte size, and D3 selections to append `<pre>` elements to the page body. The data is shown in a monospaced, green-on-black terminal style.

Data Table Summary

This example displays a plain-text summary of a small CSV dataset containing the 2018 populations of the ten most populous countries, sourced from the United Nations World Population Prospects 2017. It shows the row and column counts, file size in kilobytes, and the first ten rows formatted as JSON. The implementation uses d3.csv to load the data, d3.csvFormat to compute its byte length, and d3.select to append <pre> elements to the body, with the result styled in a terminal-like green-on-black theme.

Data Table Summary

This example displays a plain-text summary of a CSV data table, revealing the total row and column counts, file size in kilobytes, and a formatted JSON preview of the first 10 rows. The data comes from the 2018 United Nations World Population Prospects and lists populous countries with their populations. The code uses `d3.csv` to load the data, `d3.csvFormat` to calculate its byte size, and `d3.select` to append the output to the page. The rendering is minimal, with a monochrome green-on-black styling defined in CSS.

CCurran Kelleher

Data Table Summary

This example displays a plain-text summary of a CSV dataset listing the most populous countries in 2018, showing the row count, column count, file size in kilobytes, and the first ten rows as JSON. It loads the data with `csv` from D3 v5, formats the data back to CSV using `csvFormat` to calculate its size, and appends the results as `<pre>` elements. The data originates from the United Nations’ World Population Prospects 2017 estimates.

Data Table Summary

This visualization displays a plain-text summary of a CSV dataset containing population and economic indicators for the most populous countries from 2018, sourced from the United Nations World Population Prospects. It reports the total row count, column count, and file size in kilobytes, followed by the first ten rows formatted as JSON. The code uses D3 v5’s `csv` loader and `csvFormat` to parse and measure the data, then appends pre-formatted text elements to the page body. Styling applies a monochrome green-on-black terminal aesthetic via external CSS.

MMukund Khandelwal

Data Table Summary

This example displays a plain-text summary of a CSV data table, showing the row count, column count, and file size in kilobytes, followed by the first 10 rows formatted as JSON. It uses D3 v5’s `csv` loader to fetch `data.csv`, which contains 2018 population estimates from the United Nations World Population Prospects. The code relies on `select` to append `<pre>` elements and `csvFormat` to compute the data’s size, presenting the results with a terminal-style green-on-black styling.