02Data for Corona Virus Daily data Covid-19

100%

02Data for Corona Virus Daily data Covid-19

✓ Published1🌍 Public

Last edited Sep 23, 2020

Created on Sep 9, 2020

This example displays basic metadata about a COVID-19 daily dataset, showing the file size, row count, and column count. The code loads the CSV file from a GitHub gist using `d3.csv`, then computes and displays these three values in an HTML pre element. The dataset, sourced from Data World, contains daily case and death figures with attributes like new cases, total cases, and weekly counts. The visualization confirms the data has been loaded and measures its dimensions using `d3.csvFormat` and array properties.

AI-generated description

This dataset about "Coronoavirus (COVID-19) data - updated daily" until sep 2020. Originally published at Data.world: Coronavirus daily data

This dataset from 31/12/2019 shows many attributes about Covid-19 cases for many countries in the world with daily updates until Sep 2020. Each row of the table represent a Covid-19 state in a specific country.

<dl> <dt> The attribute: </dt> <dd>data: the date for this Covid-19 cases</dd> <dd>location: the country</dd> <dd>new_cases: number of new peopel who efficted with COVID-19</dd> <dd>new_deaths: number of peopel who died by COVID-19</dd> <dd>total_cases: totlal number of cases since 1/1/2020</dd> <dd>total_deaths: totlal number of death since 1/1/2020</dd> <dd>weekly_cases: number of new peopel who efficted with COVID-19 during a week</dd> <dd>weekly_deaths: number of peopel who died by COVID-19 during a week</dd> <dd>biweekly_cases: number of new peopel who efficted with COVID-19 during a week</dd> <dd>biweekly_deaths: number of peopel who died by COVID-19 during a week</dd> </dl>

Types of the attributes

date
location is the name of the country (categorical)
number of cases and death is quantitative

Questions and tasks related to the dataset.

who many cases in each country
who much spread Covid-19 in each country.
what is the highest number of cases
what is the highest number of death during a month

source: Data World

note: this dataset is updated dalily in the orginal source but in this file the last month was septemper 2020. if you need latest update please visity Coronavirus Source Data

MIT Licensed

Similar vizzes

Loading thumbnail…

02_Covid-19 Daily data

This example displays basic metadata about the COVID-19 daily dataset, showing the file size in kilobytes, the number of rows, and the number of columns in a large pre-formatted text block. The visualization loads a CSV file from a remote GitHub gist using `d3.csv` and formats the data with `d3.csvFormat` to compute the byte size. It uses D3 v5 and is limited to textual output, providing a quick summary of the dataset's structure rather than a graphical chart. The data covers daily COVID-19 cases and deaths per country from December 2019 to September 2020.

AAbdul Salam Almadani

90% match

Loading thumbnail…

Loading and Parsing Corona Virus Data

This example displays basic statistics about a COVID-19 deaths time-series dataset. The visualization reports the file size in kilobytes, the number of data rows, and the number of data columns in large text. It loads the global death records from the CSSE at Johns Hopkins repository using the `d3.csv` method to fetch and parse the remote CSV file. The code then uses `d3.csvFormat` to measure the payload size and accesses the resulting data array and its `columns` property.

RRasike Abeyratne

82% match

Loading thumbnail…

CoronaViru Data

This example displays basic metadata about the Johns Hopkins University COVID-19 deaths time series dataset, showing the file size, row count, and column count as text. It fetches the global deaths CSV from GitHub using `d3.csv`, then reads the last column name to confirm the latest date, and formats the data with `d3.csvFormat` to estimate file size. The visualization is minimal, presenting only these three numeric facts in a large font, with no charts or graphs. The code relies on D3 v6’s `d3.csv` and `d3.csvFormat` methods to load and analyze the remote dataset.

AAmir

82% match

Loading thumbnail…

Loading and Parsing Coronavirus Data

This example demonstrates the size and structure of the Johns Hopkins Coronavirus Dataset by displaying three key metrics: the total file size in kilobytes, the number of rows, and the number of columns. It loads a global CSV file of COVID-19 deaths using `d3.csv`, then formats the data with `d3.csvFormat` to calculate its byte count. The resulting statistics are displayed in large text via a `<pre>` element, with values rounded using `Math.round`.

TThomas Cormican

80% match

Loading thumbnail…

Loading and Parsing Corona Virus Data

This example demonstrates the basic process of loading and parsing the Johns Hopkins Coronavirus dataset using D3.js. It fetches a CSV file containing global COVID-19 death statistics and reports the number of rows, columns, and file size in kilobytes. The visualization uses `d3.csv` to asynchronously retrieve and parse the remote data, then displays the summary information as large HTML text via `document.getElementById` and `textContent`. The output provides a quick overview of the data’s structure without any graphical charting.

SShanmukh

80% match

Loading thumbnail…

Corona Virus

This visualization reports basic statistics on a global COVID-19 deaths dataset, displaying file size, row count, and column count as plain text. Using React with hooks, the code fetches the CSV from the Johns Hopkins CSSE GitHub repository via `d3.csv`, then formats the parsed data with `d3.csvFormat` to calculate its size in kilobytes. The view updates after the asynchronous data load, showing a loading message until the fetch completes. It relies on D3 v6 for data parsing and formatting within a React 17 component tree.

CCarlos Caballero

79% match

Loading thumbnail…

Loading and Parsing Coronavirus Data

This example demonstrates the raw size and structure of the Johns Hopkins Coronavirus Dataset by displaying three key metrics: file size in kilobytes, row count, and column count. It loads the global deaths time-series CSV and parses it using `d3.csv`, then reports the number of columns from the dataset’s header. The code computes the file size from `d3.csvFormat(data).length` and renders the results as large text in a `<pre>` element via `textContent`. It uses D3 v5’s promise-based loading API.

AAndrea Picciau

79% match

Loading thumbnail…

Corona Deaths for May 14, 2021

This visualization displays basic statistics about the global COVID-19 death dataset from Johns Hopkins University, showing the file size, row count, and column count for the data as of May 14, 2021. Using D3 v5, the program loads the CSV file via `d3.csv` and accesses the parsed data's `.columns` property to determine the number of columns. The code formats the file size using `d3.csvFormat` and calculates the byte length, then displays the three metrics in a large `<pre>` element. This example demonstrates a minimal data-loading and summary-display pattern rather than a graphical chart.

Nnexus1058

79% match