Fork of Loading and Parsing CORONAVIRUS

100%

Fork of Loading and Parsing CORONAVIRUS

✓ Published1🌍 Public

Last edited Jan 4, 2021

Created on Jan 3, 2021

Forked from Loading and Parsing CSV Data

This example demonstrates how to load and parse global COVID-19 death data from a CSV file hosted on GitHub. Using d3.csv, it fetches the time-series dataset and calculates the total deaths from the most recent date column. The interface displays summary statistics, including the CSV file size in kilobytes, the number of rows, the number of columns, and the label of the latest data column. The code also includes commented-out alternatives using fetch with async/await and a nested promise chain.

AI-generated description

A program that loads and parses some CSV data: CSS Named Colors.

Similar vizzes

Loading thumbnail…

Fork of Fork of Loading and Parsing CORONAVIRUS

This example displays a text summary of COVID-19 global death data parsed from a CSV file hosted by the CSSE at Johns Hopkins. It uses `d3.csv` to fetch and parse the time-series data, then computes the total deaths from the latest date column using JavaScript’s `reduce`. The displayed message includes file size, row and column counts, the final date, and the formatted death total via `d3.format`. The results are rendered inside a styled `<pre>` element, with the code running in a React-based build using D3 v5.

Jjesramyep1263

91% match

Loading thumbnail…

Loading and Parsing Coronavirus Data

This example demonstrates how to load and parse a global coronavirus deaths time-series dataset. It fetches CSV data from the Johns Hopkins CSSE GitHub repository using the `d3.csv` method, which returns a Promise. After loading, the program computes and displays summary statistics—the file size in kilobytes, the number of data rows, and the number of columns—within a large HTML `<pre>` element. The visualization uses D3 v5’s `csvFormat` to calculate the byte length of the formatted data, highlighting a straightforward data-processing workflow without any graphical chart.

Ffjvoris

89% match

Loading thumbnail…

Loading and Parsing Coronavirus Data

This example demonstrates loading a global COVID-19 death time-series dataset using D3 v5. It fetches a CSV file from the Johns Hopkins CSSE GitHub repository and parses it with `d3.csv`. The visualization displays a large-text summary showing the data’s size in kilobytes, the number of rows, and the number of columns, computed via `d3.csvFormat` and the parsed array’s properties. It relies on the native `fetch` API and a promise handler, with commented alternatives using `async`/`await` and nested callbacks.

Wwindwaver

89% match

Loading thumbnail…

Loading and Parsing Coronavirus CSV Data

This example demonstrates loading and parsing the Johns Hopkins Coronavirus global deaths time-series CSV dataset, displaying its size in kilobytes, row count, and column count. It uses d3.csv to fetch and parse the remote CSV file, then calls d3.csvFormat on the resulting data to measure its formatted length. The interface presents these metrics in a large HTML `<pre>` element, with the React framework integrating the D3 v5 code. The code also comments on alternative approaches using fetch, async/await, and nested promises.

CChris Briggs

88% match

Loading thumbnail…

Fork of Loading and Parsing Coronavrius Data

This example demonstrates the size and structure of a COVID-19 global deaths dataset by displaying three metrics in a large text readout: file size in kilobytes, row count, and column count. It loads the Johns Hopkins University time-series CSV directly from GitHub using `d3.csv`, then calculates the formatted data’s byte length with `d3.csvFormat`. The results are written into a DOM element via `textContent`, showing how many rows and columns the dataset contains without any visual chart or rendering.

Jj-PGi

88% match

Loading thumbnail…

Fork of Loading and Parsing CSV Data

This example demonstrates how to load and parse CSV data from a remote source using D3 v5’s `d3.csv` method, which returns a promise. The code fetches a COVID-19 death time series dataset, identifies the latest date column, and aggregates the total deaths across all rows by mapping values to numbers and reducing them with a sum function. The result is logged to the console, while the HTML page displays a large, empty `<pre>` element intended for output. The implementation runs in a React framework and uses plain JavaScript promises for asynchronous data handling.

AAmnaRizvi-S

87% match

Loading thumbnail…

Loading and Parsing Corona-virus Data

This example loads a real-world COVID-19 death time-series CSV from the Johns Hopkins CSSE repository and extracts the death total from its most recent date column. It parses each row by converting the latest column’s string value to a number, then reduces the array to a single sum. The result—the total global deaths—is displayed as text in a React-managed DOM node. The code uses d3.csv for fetching and parsing, plus Array.reduce and Array.map, with React and OpenLayers libraries loaded via CDN.

Ssultanmirzapydev

87% match

Loading thumbnail…

Loading and Parsing Coronavirus Data

This example demonstrates the initial step of working with the COVID-19 time-series dataset from the CSSE at Johns Hopkins University, showing the file size, row count, and column count of the data. It loads a global deaths CSV via `d3.csv` with a promise, then extracts the latest date column from the data’s headers. The computed metadata is displayed in a large `<pre>` element using plain DOM manipulation. The code uses D3 v5’s `csv` and `csvFormat` APIs, with no additional visualization or rendering beyond text output.

MMichael Bruno

86% match