Skip to main content
SimilarExport ZIP
100%

Summarizing Coronavirus Data

✓ Published0🌍 Public
OOleg Zhernovoy
Last edited Dec 13, 2022
Created on Dec 13, 2022

This example summarizes the Johns Hopkins Coronavirus Dataset, displaying the total global death count and the latest recorded date in a large text format. It loads the time-series CSV, extracts the final column of data, and sums all values using JavaScript's `reduce` method. The `d3.csv` function parses the data, while the `d3.format` API formats the number with commas. The resulting message is rendered inside a `<pre>` element, providing a stark numerical overview of the pandemic's impact.

AI-generated description

This program loads and parses the Johns Hopkins Coronavirus Dataset

MIT Licensed

Similar vizzes

Loading thumbnail…

Summarizing Coronavirus Data

This example summarizes the global COVID-19 death toll from the Johns Hopkins Coronavirus Dataset. It loads the CSV file with `d3.csv`, extracts the last date column, sums all reported deaths using `Array.reduce`, and formats the total with `d3.format`. The resulting number and date are displayed as large text in a `<pre>` element, offering a concise numeric snapshot of cumulative deaths.

LLaura Johnson
95% match
Loading thumbnail…

Summarizing Coronavirus Data

This example summarizes the global death toll from the John Hopkins Coronavirus Dataset by displaying a single large number and the latest date in the data. It loads the CSV time-series file, maps the final date column to numeric values, and reduces them with a sum accumulator. The result is formatted with d3.format and rendered into a `<pre>` element. The visualization uses D3 v5’s `d3.csv` for parsing and the `format` function from the d3 library for comma-separated output.

PPorawoot Buranadilok
95% match
Loading thumbnail…

Summarizing Coronavirus Data

This example displays a single, large-text summary of the total global COVID-19 deaths from the Johns Hopkins Coronavirus Dataset, along with the most recent date column in the time-series data. It loads the CSV via `d3.csv` and uses `d3.format` to insert comma separators into the summed death count. The code iterates through each country row, converts the latest date’s value to a number, and reduces them with a simple accumulator function before updating the DOM’s text content.

KK3zter
94% match
Loading thumbnail…

Summarizing Coronavirus Data

This example displays the total number of global COVID-19 deaths as a large numeric counter, updated to the latest date in the Johns Hopkins time-series dataset. It loads the CSV data using d3.csv, extracts the final column, sums its values with JavaScript’s reduce method, and formats the result with d3.format. The comma-separated total and date are rendered as plain text in a pre element, with no charts or interactive elements.

WWolfgang
94% match
Loading thumbnail…

Summarising Coronavirus Data

This example summarizes the global death toll from the Johns Hopkins Coronavirus dataset. It displays a single large text element showing the total number of deaths and the date of the latest data column. The visualization loads the CSV with `d3.csv`, extracts the final column, and sums its numeric values using `Array.reduce`. It formats the result with `d3.format` and updates the page’s `pre` element via `getElementById`.

Vvmonney
94% match
Loading thumbnail…

Summarizing Coronavirus Data

This example uses D3.js to summarize the Johns Hopkins Coronavirus Dataset, fetching the global deaths time-series CSV and displaying the most recent total. The code loads the data with `d3.csv`, identifies the final date column, and sums all reported deaths for that date with `data.reduce`. It then formats the integer using `d3.format` and presents the result in a large red `<pre>` element. The visualization is a text-only summary, showing the cumulative death count and the corresponding date as plain text.

PPeter Krevenets
94% match
Loading thumbnail…

Summarizing Coronavirus Data

This example displays a single, large numeric summary of global COVID-19 deaths, updating in real time from the Johns Hopkins time-series dataset. It shows the total death count and the most recent date column, formatted with commas. The code uses d3.csv to load the data, then applies the array map and reduce methods to sum the latest column’s values, and d3.format to create the comma separator. The result is inserted into a pre element via the DOM’s textContent property.

AAndre J Denais
93% match
Loading thumbnail…

Summarizing Coronavirus Data

A plain-text visualization summarizes the global death toll from the John Hopkins Coronavirus Dataset by loading the time-series CSV with `d3.csv` and parsing the most recent date column. It calculates the total deaths using the array `reduce` method with a custom `sum` accumulator function, then formats the number with the `format` function from the d3 library. The result, displaying the death count and the latest date, is rendered as large red text inside a `<pre>` element using the DOM `textContent` property.

Ee-ines
93% match