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textures - Textures.js is a JavaScript library for creating SVG patterns
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/.
svg-pattern patterns textures d3 svg dataviz data-visualisation maps visualggplot2 - An implementation of the Grammar of Graphics in 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()).
r visualisation data-visualisationf2 - 📱📈An elegant, interactive and flexible charting library for mobile.
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.
mobile charts visualization grammar antv f2 html5-canvas data-visualization data-visualisation canvas 2d-draw mobile-visualization interactiveBokeh - Interactive Data Visualization in the browser, from Python
Bokeh is an interactive visualization library for modern web browsers. It provides elegant, concise construction of versatile graphics, and affords high-performance interactivity over large or streaming datasets. Bokeh can help anyone who would like to quickly and easily make interactive plots, dashboards, and data applications.
visualization javascript python plots jupyter visualisation data-visualisation bokeh plotting notebooks interactive-plots numfocus charting-library chartscovid19-dashboard - A site that displays up to date COVID-19 stats, powered by fastpages.
This project showcases how you can use fastpages to create a static dashboard that update regularly using Jupyter Notebooks. Using fastpages, data professionals can share dashboards (that are updated with new data automatically) without requiring any expertise in front end development. The content of this site shows statistics and reports regarding Covid-19.
github-pages data-science jupyter analytics nteract data-visualisation matplotlib pymc3 fastai altair papermill github-actions covid-19 covid19 covid-data fastpagesIntermine - A powerful open source data warehouse system
A powerful open source data warehouse system. InterMine allows users to integrate diverse data sources with a minimum of effort, providing powerful web-services and an elegant web-application with minimal configuration. InterMine powers some of the largest data-warehouses in the life sciences.
data-warehouse bioinformatics genomics genetics clojurescript biology perl postgresql lgplv3 tomcat data-visualization data-visualisation life-science genome biologistswaffle - :maple_leaf: Make waffle (square pie) charts in R
It uses ggplot2 and returns a ggplot2 object.
r waffle-charts square-pie-charts rstats ggplot2 datavisualization data-visualisation data-visualizationnaniar - Tidy data structures, summaries, and visualisations for missing data
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.
missing-data data-visualisation ggplot2 missingness tidy-data r-packagechart-fx - A scientific charting library focused on performance optimised real-time data visualisation at 25 Hz update rates for data sets with a few 10 thousand up to 5 million data points
The chart-fx charting library is an extension in the spirit of Oracle's XYChart and performance/time-proven JDataViewer charting functionalities. Emphasis was put on plotting performance for both large number of data points and real-time displays, as well as scientific accuracies leading to error bar/surface plots, and other scientific plotting features (parameter measurements, fitting, multiple axes, zoom, ...). The library also contains a small set of math routines that can operate directly on the DataSet primitive for fitting, computing spectra, linear algebra, FIR/IIR filtering, and other functionalities common to signal processing.
javafx scientific-visualization data-visualisation hacktoberfest large-dataset chart-fx charting-librariesstreamgraph - :wavy_dash: htmlwidget for creating streamgraph visualizations in R
streamgraph is an htmlwidget for making, well, streamgraphs. The x axis values can be continous or dates.
r rstats streamgraph htmlwidgets data-visualization data-visualisationvoteogram - U.S. House and Senate Voting Cartogram Generators in 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).
r rstats datavisualization data-visualisation data-visualizationtreemapify - 🌳 Draw treemaps in ggplot2
‘treemapify’ provides ‘ggplot2’ geoms for drawing treemaps. ‘treemapify’ includes an example dataset containing statistics about the G-20 group of major world economies.
r treemap ggplot2 data-visualisationwind-js-server - Service to expose Grib2 wind forecast data as JSON
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.
grib wind grib2json weather data-visualization data-visualisation wind-js node grib2data-journalism - Data journalism and easy to replicate notebooks using Python, R, and Web visualisations
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.
data-journalism data-analysis notebook exploratory-data-analysis data-visualisation data-visualizationd3-iconarray - A D3 module for making grids of icons
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.
d3 icon-array scale grid data-visualisation visualization iconarray layouttwitter-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
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.
sentiment-analysis sentiment-visualisation twitter data-visualisation trends stream-tweetsGithubVisualizer - CS 7450: Visualization of a Github organization
CS 7450: Visualization of a Github organization. Please post issues to give your feedback about the project.
visualization github data-visualisation d3travel - Visualization of Sourabh's adventures
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.
data-visualisation visualization travel countrieselucidate - convenience functions to help researchers elucidate patterns in their data
This package is currently maintained by Craig Hutton, a Data Scientist working with the Research Branch of the British Columbia Ministry of Social Development & Poverty Reduction. Interrogate data in search of row duplications and anomalous values with dupes(), copies(), and the counts* set of functions.
data-science r data-visualisation data-analysis convenience-functions sdpr
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