Skip to main content
SimilarExport ZIP
100%

Untitled

✓ Published0🌍 Public
RRahulSai05
Last edited Apr 28, 2022
Created on Apr 28, 2022
Forked from HTML Starter

This example automatically generates a suite of exploratory data visualizations from the COVID-19 dataset in the provided CSV file. It uses the AutoViz Python library to analyze the data and produce charts such as histograms and scatter plots, rendered as SVG images. The process is triggered through the `AutoViz` class, which handles data loading, statistical analysis, and visualization creation in a single call. The code relies on the `pandas` library for data handling and runs within a Jupyter environment, with `chart_format="svg"` specifying the output format.

AI-generated description

A bare minimum HTML page demonstrating use of CSS and JavaScript.

See also React Starter.

MIT Licensed

Similar vizzes

Loading thumbnail…

Untitled

This visualization displays COVID-19 total cases by location using a bar chart rendered with SVG. It loads data from a CSV file via d3.csv, then uses d3.scaleBand for the categorical x-axis and d3.scaleLinear for the y-axis, with a fixed domain of 0 to 13. The bars are drawn as rectangles with a teal fill, and axis labels are rotated for readability. The chart is built with d3.v4 within a React framework, though the core logic is plain D3 JavaScript.

Bbhargav83
72% match
Loading thumbnail…

Untitled

A dashboard of linked COVID-19 visualizations shows global cases via a Leaflet map, interactive line charts of pandemic metrics, and scatter plots. Users can select countries on the map to filter data, while brushable axes and k-means clustering reveal relationships like GDP per capita versus case rates. Built with d3.v7 and SVG animations, the dashboard loads data from a CSV and GeoJSON files.

Bbhargav83
71% match
Loading thumbnail…

Untitled

This example presents a bar chart of total COVID-19 cases by location, using data from a remote CSV file. The chart uses an SVG rendering with a band scale for the categorical x-axis and a linear scale for the numeric y-axis, both configured with d3.scaleBand and d3.scaleLinear. Bars are drawn as SVG rect elements with a fixed fill color, and the x-axis labels are rotated for readability. The code loads data via d3.csv and applies margins to position the visualization.

Fferneyhoughedward@gmail.com
71% match
Loading thumbnail…

Untitled

This example loads a COVID-19 deaths time series from a GitHub-hosted CSV file using d3.csv, then displays summary statistics (kilobytes, column count, row count) via a React component. It uses React's useState and useEffect hooks to fetch and manage the data asynchronously, and the d3.range method to iterate once. The visualization ultimately renders a single face-like SVG shape—composed of circles with randomized eye, mouth, and stroke parameters—centered on a 960×500 canvas. The d3.csvFormat API is used to calculate the data size in kilobytes.

JJonas Carvalho
71% match
Loading thumbnail…

Untitled

This example presents a bar chart visualization rendered with D3.js, displaying monthly values and targets from the `bar-data.csv` dataset. The chart uses an SVG-based approach with a margin-defined plot area, an x-axis for dates, and a y-axis for numeric values, styled with sans-serif fonts and hidden domain lines. The code initializes the D3 library and loads the CSV data using the `d3.csv` method, though the actual bar-rendering logic is not implemented in the provided snippet. The visualization is built as a static HTML page with embedded CSS and JavaScript.

Aajitkumarjha85
70% match
Loading thumbnail…

Untitled

This example loads a CSV file from a GitHub Gist using the `d3.csv` method and displays a summary of its contents, including file size, row count, and column count, in a styled message area on an HTML page. The page is built with React and renders a static SVG illustration featuring colored shapes. The visualization demonstrates simple data loading and text-based output without interactive charts or graphs.

Ttarungunda
69% match
Loading thumbnail…

Visualisation

This example demonstrates loading and parsing a CSV file containing COVID-19 daily case data using D3 v5. The visualization sets up an SVG canvas with dimensions retrieved directly from the markup, and uses the `csv` and `select` APIs from D3 to fetch the data and log it to the console. Although no chart is rendered, it showcases the foundational workflow of importing D3 modules, loading external data via UNPKG, and preparing the SVG for future drawing operations.

Ssherman-wq
69% match
Loading thumbnail…

Untitled

This visualization shows the progression of confirmed COVID-19 cases, deaths, and recoveries across multiple countries from January to March 2020. It uses a multi-line chart with time on the x-axis and case counts on the y-axis. The code loads data from three CSV files and uses d3.csv, d3.scaleLinear, d3.line, d3.axisLeft, d3.axisBottom, and d3.curveBasis to render the chart. A timer updates the displayed date range, animating the lines as new data points appear over time.

RRodrigo Vallejos
69% match