Weather Dataset Loading

100%

Weather Dataset Loading

✓ Published0🌍 Public

Last edited Sep 4, 2025

Created on Sep 3, 2025

This example demonstrates loading a weather dataset from a local CSV file and displaying its contents as raw JSON text. The visualization initially shows a loading state before fetching the data, then parses the CSV into an array of objects using D3’s `csvParse` function. The viewed data includes daily measurements such as temperature in Celsius, Kelvin, and Fahrenheit, precipitation in millimeters, and wind speed in kilometers per hour, for an unknown location. D3’s `select` and `join` methods are used to render the parsed data within an HTML `<pre>` element.

AI-generated description

This dataset contains 20,000 records of weather information for an unkown location. Some of the data points include precipitation, temperature, windspeed, etc. This dataset could be used to visualize seasons/temperature change throughout a year.

Here is the link to the Kaggle Dataset:

s.no -- index (not data that will be used)
date -- the date that the weather was recorded at (time attribute)
temperature (celsius) -- temperature that day measured in celsius (quantitative attribute)
temperature (kelvin) -- temperature that day measured in kelvin (quantitative attribute)
temperature (fahrenheit) -- temperature that day measured in fahrenheit (quantitative attribute)
precipitation (mm) -- amount of rain/snow measured on that day in milimeters (quantitative variable)
wind speed (km/h) -- the speed of the wind measured in kilometers per an hour (quantitative variable)

MIT Licensed

Similar vizzes

Loading thumbnail…

Loading Data

This example demonstrates how to load and parse a CSV file in D3.js, displaying the Iris dataset as formatted JSON text in a `<pre>` element. The visualization initially shows a "LOADING" state, then fetches `data.csv` via the Fetch API and parses it using `d3.csvParse`. The code explicitly converts string measurements into numbers for all four numeric columns. State management is handled through a simple `setState` pattern, where the `viz` function checks whether data is loaded, triggers the asynchronous fetch, and re-renders once the parsed array of objects is available.

CCurran Kelleher

77% match

Loading thumbnail…

Loading Data

This example demonstrates how to load and parse a CSV file in D3.js, displaying the raw parsed data as a stringified JSON object in a `<pre>` element. The visualization uses a state management pattern with a `setState` function to handle asynchronous data loading, initially showing a "LOADING" placeholder. It fetches `data.csv`, parses it with `d3.csvParse`, and converts numeric columns to numbers before updating the display. The Iris flower dataset is used as the data source, with the rendering approach being a simple text-based output rather than a graphical chart.

IIshaChid76

76% match

Loading thumbnail…

Fork of Loading and Parsing CSV Data

This example demonstrates how to load and parse CSV data using D3 v5 in a React application. It fetches a dataset containing weather and flight delay information for Logan Airport, then transforms the raw CSV strings into JavaScript Date objects and numeric values for variables like daily precipitation, wind speed, and departure delays. The code uses `d3.csv` with Promise chaining to asynchronously retrieve the data, and displays the parsed results in the browser console. The visualization serves primarily as a data preprocessing step for downstream charting.

CChengwei Ye

76% match

Loading thumbnail…

Loading CSV

This example demonstrates loading a CSV dataset by fetching the Iris Dataset from a remote URL and displaying its raw JSON structure in the browser. The code uses d3.json to retrieve the data, then chains a promise to append a `<pre>` element to the body, formatting the response with JSON.stringify and indentation. The visualization itself is minimal, focusing solely on the data-loading workflow rather than rendering charts or graphs. It relies on D3 v5’s `json` method and standard DOM selection via `select`, making the asynchronous data-fetching pattern explicit.

Vvaynexie

76% match

Loading thumbnail…

Loading CSV

This example demonstrates loading an external CSV dataset—the Iris Dataset—and displaying its contents as formatted JSON in the browser. Using D3 v5’s `csv` function, it fetches the data asynchronously and, upon resolution, appends a `<pre>` element to the body with `JSON.stringify` to render the parsed array with indentation. The code imports `select` and `csv` directly from the D3 module, relying on Promises to handle the data load.

LLinkous

76% match

Loading thumbnail…

Loading and Parsing CSV Data

This example demonstrates how to load and parse a CSV file from a remote URL using D3.js, displaying key dataset statistics in a large text format. It uses `d3.csv` to fetch and parse the data, then computes the formatted file size with `d3.csvFormat`, as well as the row and column counts. The dataset comes from a GitHub gist containing CSS named color values, and the results are shown as three lines of text in a `<pre>` element.

LLaura Johnson

75% match

Loading thumbnail…

Loading and Parsing CSV Dataset

This example demonstrates loading and parsing a CSV dataset to display a summary of its contents. The visualization shows the number of rows, number of columns, and estimated file size in kilobytes. The code uses D3.js v7's `d3.csv` method to fetch and parse the data asynchronously, then updates the DOM with a summary using `d3.select` and `.html()`. The file size is estimated by converting the JSON stringified data length from bytes to kilobytes. The data source is a local CSV file, and the interface displays text-based summary information rather than graphical charts.

Yyvarshachowdary@gmail.com

75% match

Loading thumbnail…

Loading and Parsing CSV Data

This example demonstrates how to load and parse remote CSV data, displaying basic dataset statistics as plain text. It fetches a raw CSV file from a GitHub gist using the Fetch API, then parses the text with `d3.csvParse` to produce an array of objects and column metadata. The visualization shows the file size in kilobytes, row count, and column count in a simple `<pre>` element. The code uses D3 v7’s parsing utilities alongside native JavaScript async functions, without any graphical rendering.

GGimmi45

75% match