Loading and Parsing PS4 Games Sales Dataset

100%

Loading and Parsing PS4 Games Sales Dataset

✓ Published0🌍 Public

Last edited Sep 23, 2021

Created on Sep 3, 2021

Forked from Loading and Parsing CSV Data

This example shows the raw size and structure of a PS4 games sales dataset by displaying three statistics: total file size in kilobytes, number of rows, and number of columns. Using D3 v5’s `d3.csvParse`, it converts fetched CSV text into a parsed data array, then extracts `data.length` for row count and `data.columns.length` for column count. The data is retrieved asynchronously via the Fetch API with `async`/`await`, and the results are rendered as large text inside a `<pre>` element.

AI-generated description

A visualization of the structure of a CSV file.

This program loads and parses a CSV file of a dataset that contains sales of PS4 games (in millions of dollars) around different regions, from multiple genres and publishers: PS4 Games Sales Dataset.

MIT Licensed

Similar vizzes

Loading thumbnail…

Loading and Parsing PS4 Games Sales CSV Data

This example demonstrates loading and parsing the PS4 Game Sales Dataset, displaying file size, row count, and column count on a black background. It uses d3.csv to fetch the CSV from a GitHub gist, then d3.csvFormat to calculate the data size in kilobytes. The code also includes commented alternatives using fetch, async/await, and d3.csvParse, alongside a nested Promise example, illustrating different asynchronous parsing approaches in D3 v5.

YYichen Li

92% match

Loading thumbnail…

Loading and Parsing vgsales.csv

This example loads a CSV file of video game sales data and displays basic file statistics: the dataset’s size in kilobytes, row count, and column count. The page uses D3 v5’s `d3.csv` method to fetch and parse the data from a GitHub Gist, then renders the summary in a large `<pre>` element. The code also includes commented alternatives using `fetch` with `async`/`await` and `d3.csvParse` to demonstrate different parsing approaches.

DDaniel Ribaudo

81% match

Loading thumbnail…

Loading data - vgsales.csv

This example loads the Video Games Sales dataset from a GitHub-hosted CSV and displays its size, row count, and column count in large text. It demonstrates two approaches to fetching and parsing data: the primary method uses `d3.csv` to load and parse the file, while an alternative commented implementation uses `fetch` with `async`/`await` and `d3.csvParse`. The page also includes a commented “pyramid of doom” example showing nested promise callbacks. All results are rendered into a `<pre>` element via `document.getElementById`.

VVarun Eranki

80% match

Loading thumbnail…

Video Game Sales

This example reads a CSV file of video game sales data from a public GitHub gist, originally sourced from Kaggle, and displays a plain-text summary of its size and structure. It shows the file’s approximate size in kilobytes, the row count, and the number of columns. The code uses D3.js v5’s `d3.csv` to parse the remote data and `d3.csvFormat` to measure its length, then writes the summary into a large `<pre>` element. Alternate commented approaches demonstrate `fetch` with `async/await` and `d3.csvParse`.

Ggeorgeeeee

80% match

Loading thumbnail…

Loading and Parsing VGSales.csv

This example loads and parses the VGSales.csv dataset, displaying the raw file size, row count, and column count in large text. It shows how D3 fetches and parses CSV data to summarize its structure. The code uses `d3.csv` to load the remote file, then formats the data with `d3.csvFormat` to calculate its size. An alternative approach using `fetch`, `async/await`, and `d3.csvParse` is also included. The dataset, sourced from Kaggle, contains video game sales metrics across global regions.

TT-Reiser

79% match

Loading thumbnail…

Video Game sales

This example displays basic metadata about a video game sales dataset, showing its size in kilobytes, row count, and column count in large text. It loads a CSV file from a GitHub gist using the D3.js v5 `d3.csv` method, then formats the content with `d3.csvFormat` to calculate the data’s byte size. The code also includes commented alternatives using the Fetch API and async/await with `d3.csvParse`. The dataset originates from Kaggle’s video game sales collection, with the visualization serving primarily to demonstrate CSV loading and summary statistics.

RRochelle

78% match

Loading thumbnail…

video game sales

This example displays the raw contents of the video game sales dataset as a JSON-formatted text dump, showing sales figures across regions and user scores for each title. The visualization initially loads data from a remote CSV file hosted on GitHub using `fetch()` and parses it with D3 v7’s `csvParse`. It uses a simple `pre` element bound to the parsed data array through a data join, with the `select`, `join`, and `text` APIs to render the dataset exactly as structured. The state management via `setState` handles the asynchronous loading sequence from `undefined` to `'LOADING'` to the final parsed array.

QQingyang Wang Profolio

77% match

Loading thumbnail…

Videogame sales

This example presents a minimal summary of the Videogame Sales dataset, displaying its size in kilobytes, row count, and column count as large text. It uses D3 v5 to load the remote CSV file via `d3.csv`, converts the data with `d3.csvFormat`, and reports the byte length before updating the page content. The visualization focuses on data loading and parsing rather than graphical representation, showcasing D3’s CSV utilities.

VVamsi Bhargav Sukamanchi

75% match