Effects of climate change

dataset 1 - Climate Change Impact on Agriculture

This example presents a dataset summary by displaying the first record from the Climate Change and Agriculture dataset as formatted JSON using the browser’s built-in `JSON.stringify` function. It loads the CSV data with the `data.csv` import and converts all numeric fields to numbers. The visualization is a static, text-based overview, showing raw data structure rather than graphical analysis, and uses no external charting libraries.

80% match

Weather Dataset Loading

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.

EEmily Hudson

Oomniaabouhassan@gmail.com

Data on CO2 and Greenhouse

This example displays the first row of a CSV dataset on CO2 and greenhouse gas emissions by Our World in Data. The code loads the data, parses it, and formats it as a JSON object, which is then rendered in a `<pre>` element using `JSON.stringify`. The main visualization shows how the data is structured and highlights the various metrics tracked, including emissions by source, per-capita values, and cumulative totals.

Scatter Plot for Climate Data - v1

This scatter plot visualizes climate impacts on agriculture for a selected year, showing pesticide usage on the x-axis and fertilizer usage on the y-axis. Circle radius encodes soil health index, while color depth represents crop yield, with a dropdown menu filtering data by year. The visualization uses D3 scales like `scaleLinear`, `scaleSqrt`, and `scaleSequential` with an `interpolateBlues` color scheme, plus interactive tooltips. Data comes from the Climate Change Impact on Agriculture dataset, rendered using D3’s `select`, `join`, and axis label utilities.

Scatter Plot for Climate Data - v2

This interactive scatter plot visualizes climate change impacts on agriculture, showing pesticide use against fertilizer use for a selected year. Circle size encodes soil health index, while color depth represents crop yield, with hover tooltips revealing exact values. The visualization uses D3.js scales, including `scaleLinear`, `scaleSqrt`, and `scaleSequential`, alongside an SVG-based rendering with a dropdown for year selection. Data comes from a preloaded Climate Dataset, and each circle maps to a data point filtered by the selected year.

Daily Surface Air Temperature

This example displays the first row of a CSV dataset containing daily global surface air temperatures from 1940 to 2024. The code loads the data, converts the values to numbers, and renders the first data point as a JSON object in a large-font `<pre>` element. The visualization uses Svelte and D3.js, though it currently only shows the underlying data structure rather than a chart. The dataset originates from Climate Reanalyzer.

CCurran Kelleher

65% match

Scatter Plot for Climate Data - v3

This interactive scatter plot visualizes the impact of climate on agriculture, plotting pesticide usage against fertilizer usage. Circle size encodes soil health, while color depth represents crop yield, using `d3.scaleSqrt` and `d3.scaleSequential` with `interpolateBlues`. Hovering reveals detailed metrics via a tooltip. Dropdown menus, built with `d3.select`, filter the displayed data by year and region, allowing exploration of the Climate Change Impact on Agriculture dataset.

65% match