Summarizing Coronavirus Data

Sumarizing Coronavirus Data

This visualization summarizes the global death toll from the Johns Hopkins Coronavirus Dataset. It displays a single large red number for the total deaths, followed by the latest recorded date, in a plain text format. The code loads the CSV data with d3.csv, extracts the last date column, and sums all values using array reduce. It then formats the result with d3.format and writes it to a pre element in the HTML.

RRMartins11

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

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

Summarising coronavirus data

This visualization summarizes COVID-19 death data from the John Hopkins coronavirus dataset by displaying the total number of deaths and the latest date as large red text. It loads a CSV file with `d3.csv`, extracts the last date column, and sums all death values using `Array.reduce`. The result is formatted with `d3.format` and injected into an HTML `<pre>` element via `textContent`, updating the page with a single, stark numeric summary.

Ccynichole

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

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

Summarizing Coronavirus Data

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.

OOleg Zhernovoy

Summarizing Coronavirus Data

This example displays the current global death toll from the COVID-19 pandemic as a large, plain-text message. It uses `d3.csv` to fetch the Johns Hopkins University time-series dataset from GitHub, extracts the last date column, and sums all reported deaths with a `reduce` operation. The final count and date are formatted using `d3.format` and written directly into the page’s DOM via `textContent`. The visualization is intentionally minimal, offering a stark numeric summary without charts or graphics.

MMichael Bergerson