Data Table Summary

Data Table Summary

This example displays a plain-text summary of a CSV file, showing the row count, column count, and file size in kilobytes, followed by the first 10 rows as formatted JSON. The visualization uses D3 v5’s `select` and `csv` APIs to load and parse the data, then writes the output into `pre` elements on a black background with green monospace text. The data, sourced from a file about Mario game sales, is processed entirely in the browser without additional rendering libraries.

CChooo4u

Data Table Summary

This example summarizes a CSV dataset by displaying its row count, column count, and file size in kilobytes, followed by the first ten rows as formatted JSON. Two `pre` elements present this text output, styled with green monospace text on a black background. The data originates from the Lending Club loan dataset, though the code uses a simpler ten-country population sample. It loads the file with `d3.csv`, computes the size via `d3.csvFormat`, and renders the output using D3 selections with `select` and `append`.

MMukund Khandelwal

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 summarizes a CSV dataset by displaying its dimensions and a preview. It first shows the total row and column counts along with the file size in kilobytes, calculated using `csvFormat`. It then displays the first 10 rows as formatted JSON. The code loads the auto-mpg dataset via `d3.csv` and builds the text output using D3 selections to append `<pre>` elements.

MMinwoo Pak

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

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.

Data Table Summary

This example displays a plain-text summary of a tabular dataset, showing the total row count, column count, and file size in kilobytes. It then prints the first ten rows as formatted JSON. The visualization uses D3 v5 APIs such as `d3.csv` to load the data, `d3.csvFormat` to measure its size, and `d3.select` to append `<pre>` elements to the page. The data consists of daily high and low stock prices for five companies sourced from Yahoo Finance.

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 ten rows formatted as JSON. The visualization uses d3.csv to load the data, d3.csvFormat to compute the size, and d3.select to append the summaries to the page. The data comes from Yahoo Finance stock prices for five companies.