Countries of the world

Data Table Summary

This example summarizes a CSV dataset of World Bank GDP figures for 264 countries from 1970 to 2017. It displays the row count, column count, and file size in kilobytes, followed by a JSON-formatted preview of the first 10 rows. The visualization uses D3 v5’s `csv` and `csvFormat` functions to load and measure the data, and appends the summary to the page as `pre` elements with a monospace terminal aesthetic.

82% match

Data Table Summary

This example displays a textual summary of a dataset of the world’s most populous countries from 2018, sourced from the United Nations. It shows the total row count, column count, file size in kilobytes, and the first ten rows as pretty-printed JSON. The code uses d3.csv, d3.csvFormat, and d3.select to load and format data, then appends text to the page via pre elements. A black background with green monospace text mimics a terminal output.

MMukund Khandelwal

82% match

Data Table Summary

This example summarizes a dataset of the most populous countries in 2018, sourced from the United Nations World Population Prospects. It displays the total number of rows, columns, and file size in kilobytes, followed by the first ten rows formatted as JSON. The visualization uses D3 v5’s `csv` and `csvFormat` methods to load and measure the data, then appends `<pre>` elements to the body, styling the output in a monospace green-on-black terminal aesthetic.

Data Table Summary

This example summarizes a CSV of World Bank GDP data for all countries from 1960–2017. It displays the total row and column counts, the file size in kilobytes, and a JSON-formatted preview of the first 10 rows. The code uses `d3.csv` to load the data, `d3.csvFormat` to calculate the file size, and `d3.select` to append `<pre>` elements showing the summary. The output appears in monospace green text on a black background.

Data Table Summary

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 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 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.