Skip to main content
SimilarExport ZIP
100%

Chennai restaurants

✓ Published1🌍 Public
AAkanksha
Last edited Jan 23, 2024
Created on Jan 23, 2024

This visualization displays the first record from a penguins dataset as a JSON object in a pre-formatted text block. The code loads data from a local CSV file, converts its quantitative attributes to numbers using unary plus operators, and exports both the parsed data and a main function. The main function sets a large font size and inserts the JSON representation of the first data row into the container. It relies on the browser's native JSON.stringify method and HTML pre element for rendering. The data originates from the palmerpenguins GitHub repository.

AI-generated description

The Penguins Dataset, loaded and parsed as CSV.

Challenge

  • Find 3 datasets on a topic you are interested in
  • For each of those, fork this viz and replace the data
  • Parse the quantitative attributes into numbers
  • Update README.md to indicate the original data source
MIT Licensed

Similar vizzes

Loading thumbnail…

Chennai Restaurants

This example displays the first row of the Chennai Restaurants dataset as a formatted JSON object. The code imports the data from a CSV file, converts quantitative attributes like bill length and body mass to numbers, and uses a preformatted HTML block to render the output. It relies on the D3.js library for data loading and formatting, with the visualization built entirely through DOM manipulation rather than canvas or SVG rendering.

AAkanksha
87% match
Loading thumbnail…

Fork of Chennai restaurants

This fork of the Chennai restaurants visualization displays a single JSON record from the loaded penguins dataset, parsed into numeric attributes. The code imports data from a CSV file, converts measurement columns to numbers using unary plus operators, and renders the first data object as a formatted JSON string within an HTML `<pre>` element. The example uses raw JavaScript string interpolation to build the output, with no external visualization libraries.

AAkanksha
86% match
Loading thumbnail…

Chennai restaurants

This example reads a CSV of Chennai restaurant data and converts numerical fields like `Price_for_2`, `Dining_Rating`, `Dining_Rating_Count`, and `Delivery_Rating` to numbers. It then displays the first record as a formatted JSON object within a `<pre>` element using the Vega-Lite data loading and export API. The visualization is a static, text-based preview of the dataset, showcasing the raw structure of the data without any graphical encoding. The implementation relies on JavaScript string interpolation to set the font size and inject the JSON string into the container’s HTML.

AAkanksha
82% match
Loading thumbnail…

Penguins Dataset

This example displays the first row of the Palmer Penguins dataset as formatted JSON in a large monospace font. The code imports the data from a CSV file using a custom `import data from './data.csv'` statement, then converts each measurement column to a number with unary plus operators. The `main` function renders the JSON stringified object into an HTML `<pre>` element. The primary API used is `JSON.stringify` to serialize the data object, while the export `{ data }` makes the full dataset available externally.

SSubhendu Karmakar
72% match
Loading thumbnail…

Penguins

This example displays the first record of the Palmer Penguins dataset as a formatted JSON object. It loads the CSV data using Arquero, parses the quantitative columns into numbers, and renders the resulting object in a `<pre>` element with a large font size. The code imports the data preparation module and uses `JSON.stringify` to display the structured data.

SShad Frigui
72% match
Loading thumbnail…

Fork of Penguins

This example displays the first penguin record from the Palmer Penguins dataset as a formatted JSON object in large monospaced text. The Fork of Penguins visualization converts the CSV data into numeric values for bill length, bill depth, flipper length, and body mass using JavaScript’s unary plus operator. It renders the data structure with template literals inside a preformatted HTML element, leveraging the Observable framework’s data import and export syntax. The chart demonstrates a minimal, exploratory approach to inspecting raw quantitative attributes without additional visualization libraries.

AAkanksha
71% match
Loading thumbnail…

Fork of Penguins

This example displays the first penguin record from the Palmer Penguins dataset as a formatted JSON object in large monospaced text. The Fork of Penguins visualization converts the CSV data into numeric values for bill length, bill depth, flipper length, and body mass using JavaScript’s unary plus operator. It renders the data structure with template literals inside a preformatted HTML element, leveraging the Observable framework’s data import and export syntax. The chart demonstrates a minimal, exploratory approach to inspecting raw quantitative attributes without additional visualization libraries.

AAkanksha
71% match
Loading thumbnail…

Fork of Penguins

This fork displays the first record of the Palmer Penguins dataset as a JSON object, illustrating the data structure used by the visualization. The code imports the CSV file containing measurements of penguin species, including bill length, bill depth, flipper length, and body mass, and parses the quantitative attributes into numeric values. The main function renders the parsed data within a preformatted HTML element, using a template literal to display the JSON at a specified font size.

VVineet Chauhan
71% match