100%

Fork of CSV Dataset Template -Pngu

✓ Published1🌍 Public

Last edited Apr 8, 2024

Created on Apr 8, 2024

Forked from CSV Dataset Template - Penguins

This example demonstrates how to load and prepare the Palmer Penguins dataset for use in a VizHub visualization. It shows the parsed structure of a single penguin record, displaying attributes like species, island, and various body measurements. The code imports data from a local CSV file using JavaScript, converts quantitative columns like `bill_length_mm` and `body_mass_g` to numbers, and renders the first data point as a JSON object in an HTML `<pre>` element. It also exports the parsed data for use in other visualizations.

AI-generated description

The Penguins Dataset, loaded and parsed as CSV.

Fork and modify this template to import your data to VizHub and export it for use in other vizzes! To do that:

Fork this viz
Clear out the README
Update the README with details about your dataset (including original source)
Replace data.csv with your own data
Replace the parsing logic in index.js with your own
Set the custom URL so you can import from it easily

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…

Fork of CSV Dataset Template - Penguins

This example displays the raw contents of the Palmer Penguins dataset, parsed from a CSV file and shown as a formatted JSON object for the first row of data. It loads the data using an ES module import, converts the quantitative fields into numbers by applying unary plus operators, and renders the output as a styled `<pre>` element. The visualization serves as a template for importing and inspecting new datasets in VizHub.

RRuba Khan

90% match

Loading thumbnail…

Fork of CSV Dataset Template - Penguins

This gallery example presents a forkable CSV dataset template built around the Palmer Penguins data. It loads the penguins.csv file and parses its quantitative attributes into numbers for downstream visualization use. The code uses JavaScript's `d3.csv` parsing logic and provides a simple, reusable structure for importing custom datasets into VizHub. The visualization itself does not render a graphic; instead, it focuses on data preparation and export, with the README documenting the original source and instructions for forking.

Oocasfre@gmail.com

90% match

Loading thumbnail…

Fork of CSV Dataset Template - Penguins

This fork of the CSV Dataset Template loads the Palmer Penguins dataset from a local CSV file, parsing quantitative attributes like bill length, bill depth, flipper length, and body mass into numeric values while retaining categorical variables such as species, island, and sex. The visualization demonstrates how to import and prepare tabular data for use in VizHub, with parsing logic applied to the raw CSV before rendering. The example is intended as a reusable template for users to replace with their own datasets and customize the parsing logic accordingly.

PPavanmahaveer Singara

90% match

Loading thumbnail…

Fork of CSV Dataset Template - Penguins

This example loads the Palmer Penguins dataset from a CSV file and parses its quantitative measurements into numbers. It displays the first row of the parsed data as a formatted JSON object, making it easy to inspect the structure and types. The code uses the native `JSON.stringify` method to render the output and relies on the VizHub import system to access the `data.csv` file. The forkable template demonstrates how to prepare a dataset for use in other visualizations.

LLiuYipeng

89% match

Loading thumbnail…

CSV Dataset Template - Penguins

This visualization displays the first record from the Palmer Penguins dataset, a CSV file containing measurements of bill length, bill depth, flipper length, and body mass for three penguin species across multiple Antarctic islands. The code imports the data using VizHub’s built-in CSV loader, then coerces the quantitative attributes from strings to numbers with the unary plus operator. The parsed JSON output is rendered inside an HTML `<pre>` element, demonstrating the data structure for verification before further visualization. The example serves as a template for importing and parsing custom datasets in VizHub.

CCurran Kelleher

89% match

Loading thumbnail…

Fork of Fork of CSV Dataset Template - Penguins

This example demonstrates a minimal fork of the CSV Dataset Template, using the Palmer Penguins dataset loaded from a local `data.csv` file. The visualization parses quantitative attributes—such as bill length, bill depth, flipper length, and body mass—into numbers, while retaining categorical fields like species, island, and sex. The data is rendered in a simple scatter plot (or similar) using D3, and the template includes instructions for forking, replacing data, and updating the README. The code is available under the MIT license, authored by NYARANGA-ROB, and is intended as a starting point for importing and exporting custom datasets in VizHub.

Rrobertotienonyaranga@gmail.com

88% match

Loading thumbnail…

Fork of CSV Dataset Template - Penguins

This example demonstrates how to display a parsed CSV dataset by rendering the first row of the Palmer Penguins data as formatted JSON. It shows the raw structure of a single data record, including both quantitative and categorical attributes, before any further analysis. The visualization uses the `data.csv` import and parses numeric fields like `bill_length_mm`, `bill_depth_mm`, `flipper_length_mm`, and `body_mass_g` with unary plus operators. The code then inserts a `<pre>` element with the JSON string into the container, leveraging the `main` export function and the `data` export for reuse.

Hharichandanamone21@gmail.com

87% match

Loading thumbnail…

Fork of CSV Dataset Template - Penguins

This example displays the first row of a penguin dataset as formatted JSON, demonstrating how CSV data is parsed and prepared for visualization. The code loads the data from `data.csv`, converts measurement columns like `bill_length_mm` and `body_mass_g` from strings to numbers, and then uses the `main` function to render the JSON string into the container. The dataset originates from the palmerpenguins GitHub repository, and the example uses D3.js conventions for data import and processing.

LLuca Liverani

87% match