Data Summary

Data Summary

This example uses the D3 v4 library to load a CSV file of automobile data and render a plain-text summary of the dataset. The code displays the total number of rows, columns, and file size, followed by a column-by-column breakdown generated by the Datalib `dl.format.summary` API. The summary is printed to the page and the console.

CCurran Kelleher

Data Summary

This example displays a plain-text summary of a tabular dataset, listing the row count, column count, file size, and a per-column statistical breakdown. A CSV containing New York City housing development records is loaded with `d3.csv`, then processed by the `dl.format.summary` method from Datalib to generate the column descriptions. The resulting text is rendered inside a `pre` element appended to the body using standard D3 selections in version 4.

Data Summary

This example displays a plain-text summary of a car dataset from the UCI Machine Learning Repository, showing the total row count, column count, file size in kilobytes, and per-column statistics like type, min, max, and mean. The code loads the CSV with `d3.csv`, formats the data with `d3.csvFormat`, and uses Datalib’s `dl.format.summary` to generate the statistical breakdown. The result is rendered in a `<pre>` element and also logged to the browser console.

Data Summary

Data Summary

This visualization presents a plain-text data summary of the Auto MPG dataset, listing the table’s number of rows, columns, and file size before displaying per-column statistical summaries. It loads the CSV using `d3.csv` and formats the output with Datalib’s `dl.format.summary` API, rendering the result as a `<pre>` element on the page. The example works entirely through text, providing a quick structural overview of the data without any graphical charts.

Data Summary

This example displays a text-based summary of a dataset about affordable housing projects in Los Angeles, sourced from DataLA. It lists the total number of rows, columns, and file size, followed by a per-column statistical breakdown. The code loads the CSV data using `d3.csv`, then employs Datalib's `dl.format.summary` function to generate the analysis. The resulting text is rendered into a `<pre>` element using `d3.select` and `append`.

Data Table Summary

This example displays a plain-text summary of a CSV dataset, showing the total number of rows, columns, and file size, followed by the first ten rows rendered as formatted JSON. It uses D3 v5’s `csv` and `csvFormat` functions to load and measure the data, and `select` to append `<pre>` elements to the page. The data, sourced from the World Happiness Report 2017, is displayed in a monospaced terminal style with green text on a black background.

CChooo4u

Data Table Summary

This example displays a plain-text summary of a loaded CSV file, showing the total row count, column count, and file size in kilobytes, followed by the first ten rows formatted as JSON. It imports `select`, `csv`, and `csvFormat` from D3 v5 to fetch `data.csv` and compute the byte length. The output renders in a monospace `<pre>` element styled with green-on-black terminal colors. The dataset describes daily high and low stock prices for several tickers, sourced from a 2018 United Nations population report.

Vveagy