Displaying 1 to 15 from 15 results

textures - Textures.js is a JavaScript library for creating SVG patterns

  •    Javascript

Textures.js is a javascript library for creating SVG patterns. Made on top of d3.js, it is designed for data visualization. Read more on http://riccardoscalco.github.io/textures/.

ggplot2 - An implementation of the Grammar of Graphics in R

  •    R

ggplot2 is a system for declaratively creating graphics, based on The Grammar of Graphics. You provide the data, tell ggplot2 how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details. It’s hard to succinctly describe how ggplot2 works because it embodies a deep philosophy of visualisation. However, in most cases you start with ggplot(), supply a dataset and aesthetic mapping (with aes()). You then add on layers (like geom_point() or geom_histogram()), scales (like scale_colour_brewer()), faceting specifications (like facet_wrap()) and coordinate systems (like coord_flip()).

f2 - 📱📈An elegant, interactive and flexible charting library for mobile.

  •    Javascript

F2 is born for mobile, developed for developers as well as designers. It is Html5 Canvas-based, and is also compatible with Node.js, Weex and React Native. Based on the grammar of graphics, F2 provides all the chart types you'll need. Our mobile design guidelines enable better user experience in mobile visualzation projects. Special thanks to Leland Wilkinson, the author of The Grammar Of Graphics, whose book served as the foundation for F2 and G2.

naniar - Tidy data structures, summaries, and visualisations for missing data

  •    R

For more details on the workflow and theory underpinning naniar, read the vignette Getting started with naniar. For a short primer on the data visualisation available in naniar, read the vignette Gallery of Missing Data Visualisations.

streamgraph - :wavy_dash: htmlwidget for creating streamgraph visualizations in R

  •    HTML

streamgraph is an htmlwidget for making, well, streamgraphs. The x axis values can be continous or dates.

voteogram - U.S. House and Senate Voting Cartogram Generators in R

  •    R

‘ProPublica’ https://projects.propublica.org/represent/ makes United States Congress member votes available and has developed their own unique cartogram to visually represent this data as has ‘GovTrack’ <URL_AT_SOME_POINT> . Tools are provided to retrieve voting data, prepare voting data for plotting with ‘ggplot2’, create vote cartograms and theme them. You can grab the results of a roll call vote (House or Senate) with roll_call(). It returns a list with a ton of information that you can use outside this package. One element of that list is the data.frame of vote results. You can pass in the entire object to either _carto() function and it’ll “fortify” it before shunting it off to ggplot2. Try to cache this data (I do, below, in R markdown chunk) as you’re ticking credits off of ProPublica’s monthly free S3 allotment each call. Consider donating to them if you’re too lazy to cache the data).

treemapify - 🌳 Draw treemaps in ggplot2

  •    R

‘treemapify’ provides ‘ggplot2’ geoms for drawing treemaps. ‘treemapify’ includes an example dataset containing statistics about the G-20 group of major world economies.

wind-js-server - Service to expose Grib2 wind forecast data as JSON

  •    Javascript

Simple demo rest service to expose GRIB2 wind forecast data (1 degree, 6 hourly from NOAA) as JSON. Consumed in wind-js-leaflet. Contains a pre-packaged copy of grib2json for conversion.

data-journalism - Data journalism and easy to replicate notebooks using Python, R, and Web visualisations

  •    HTML

If you are a Data Journalist looking to improve your coding skills, or you work as a developer giving support in a newsroom, you arrived to the right place. This is a repository of articles and tutorials, as IPython/Jupyter notebooks or web products, about doing data journalism. The articles presented here, apart from analysing data to present some facts about the current, past, and sometimes future world situation, will show programming instructions explaining how to repeat the analysis by yourself. We live in a world where governments and the media, more often than not, serve the interests of a few. Our belief is that to empower people to do their own analysis and arrive to conclusions based on facts (data), is a way to make us all more aware and strong as a society.

d3-iconarray - A D3 module for making grids of icons

  •    Javascript

A D3 plugin targeting V4 helping you to draw an array of icons. There are two parts to this plugin. First a layout which will assign x,y coordinates to elements of an array given some parameters. Second a scale which will put regular breaks in the array of icons to aid legibility.

twitter-sentiment-visualisation - :earth_africa: The research and development of a sentiment analysis module, and the implementation of it on real-time social media data, to generate a series of live visual representations of sentiment towards a specific topic or by location in order to find trends

  •    CoffeeScript

A web app that uses data from Twitter combined with sentiment analysis and emotion detection to create a series of data visualisations to illustrate the happy and less happy locations, topics and times. This project aims to make Twitter data more understandable. It streams real-time tweets, or can fetch tweets about a specific topic or keyword - it then analyses this data using a custom-written sentiment analysis algorithm, and finally displays the results with a series of dynamic D3.js data visualisations.

GithubVisualizer - CS 7450: Visualization of a Github organization

  •    Python

CS 7450: Visualization of a Github organization. Please post issues to give your feedback about the project.

travel - Visualization of Sourabh's adventures

  •    Javascript

This is a simple visualization of the world map using HighCharts. It is a static page with no backend and the dark color represents the countries that I have visited. It allows one to zoom within US and India and highlights the visited states. As I have never lived longterm in any other country I didn't add the ability to zoom into them. This was purely a fun project for me in trying to read more about data visualization and also thinking more about my future vacations.