Data Table Summary

Data Table Summary

This example displays a summary of a sleep-tracking dataset for a baby’s first 2.5 months, showing the total row count, column count, and file size in kilobytes, followed by the first ten rows formatted as JSON. The page renders the text output on a black background with green monospaced text. The code uses d3.csv to load the data, d3.csvFormat to compute the file size, and d3.select to append the summary elements to the body.

Ssrrajendran

88% match

Data Table Summary

This example displays a plain-text summary of a CSV data table, showing row count, column count, file size, and the first 10 rows as formatted JSON. It uses d3.csv to load the data and d3.csvFormat to compute its byte size. The page renders the information in green monospace text on a black background, with the data sourced from the United Nations World Population Prospects 2017.

87% match

Data Table Summary

This example displays a plain-text summary of a car dataset through D3 v5. It loads a CSV file with approximately 400 records and outputs the total row count, column count, and file size in kilobytes. The page then prints the first 10 rows as formatted JSON for quick inspection. Using `d3.csv` and `d3.csvFormat`, the code calculates data metrics and appends the results to the DOM with the `select` and `append` APIs.

Ssrrajendran

87% match

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.

87% match

Data Table Summary

This visualization displays a summary of a dataset loaded from a CSV file, showing the row and column counts alongside the file size in kilobytes. It then prints the first 10 rows of data as a formatted JSON object. The code uses `d3.csv` to fetch and parse the data, `d3.csvFormat` to measure the data size, and `d3.select` to append `<pre>` elements displaying the textual output.

SShane Carey

Data Table Summary

This example shows a plain-text summary of a tabular dataset. It prints the number of rows, columns, and file size in kilobytes, followed by the first ten rows displayed as formatted JSON. The code uses `d3.csv` to load the data, `csvFormat` to compute its size, and `JSON.stringify` to display the preview. Styled with black background and green monospace text, it renders the output into `pre` elements appended to the page body, drawing from the 2013 stock price dataset.

Data Table Summary

This example displays a plain-text summary of a CSV dataset, reporting the row count, column count, and file size in kilobytes, followed by a JSON-formatted preview of the first ten rows. It loads the data using `d3.csv` and formats the output with `csvFormat` from D3 v5. The data originates from the United Nations World Population Prospects 2017, containing population estimates for countries from 1970 to 2017. The visualization presents this information in a monospaced, terminal-like style on a black background.

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.