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38 Tools For Beautiful Data Visualisations

38 Tools For Beautiful Data Visualisations
As we enter the Big Data era, it becomes more important to properly expand our capacity to process information for analysis and communication purposes. In a business context, this is evident as good visualisation techniques can support statistical treatment of data, or even become an analysis technique. But also, can be used as a communication tool to report insights that inform decisions. Today there are plenty of tools out there that can be used to improve your data visualisation efforts at every level. Below we list a non-exhaustive list of resources. Javascript Libraries Circular Hierarchy – D3.js Python Libraries Kartograph.py – Mapsigraph – Node-link, treesMatplotlib – Most types of statistical plotsPycha – Pie chart, bar chart, area chartNetworkX – Node-link Java / PHP Web Applications TileMill – Running Map Programming Languages Hyperbolic Tree – NYTimes 365/360 Generated with Processing Desktop Applications Treemap – Tableau

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» Beyond Tag Clouds: TagArcs for Wordpress Tag Visualization (part I) Beyond Tag Clouds: TagArcs for WordPress Tag Visualization Tag clouds are very use­ful to vi­sua­lize the most fre­quently used tags on a web­site, e.g. a blog. This is done by stee­ring at­ten­tion through em­pha­si­zed words whose font size, co­lor or po­si­tion stands out. But not­hing can be found out about tem­po­ral re­la­tion of a tag's posts. Data Visualization: Modern Approaches Data presentation can be beautiful, elegant and descriptive. There is a variety of conventional ways to visualize data – tables, histograms, pie charts and bar graphs are being used every day, in every project and on every possible occasion. However, to convey a message to your readers effectively, sometimes you need more than just a simple pie chart of your results.

Essential Resources: Mapping applications, frameworks and libraries This is part of a series of posts to share with readers a useful collection of some of the most important, effective and practical data visualisation resources. This post presents the many different options for visualisation spacial data. Please note, I may not have personally used all the packages or tools presented but have seen sufficient evidence of their value from other sources. Whilst some inclusions may be contentious from a quality/best-practice perspective, they may still provide some good features and provide value to a certain audience out there. Finally, to avoid re-inventing the wheel, descriptive text may have been reproduced from the native websites if they provide the most articulate descriptions. Your feedback is most welcome to help curate this collection, keep it up to date and preserve its claim to be an essential list of resources!

KeyLines Geospatial KeyLines Geospatial is a unique integration for visualizing connected data on maps. As long as your graph data has a location property (latitude and longitude), you can: View your network data on a mapTransition seamlessly from a network view to a map viewZoom in and out, and pan around the mapIntegrate maps with other KeyLines functionality, like filters, social network analysis and the time bar. Unlock richer data insight KeyLines geospatial unlocks an important aspect to your graph data – the location – without losing sight of the connections you need to understand.

ImagePlot visualization software: explore patterns in large image collections What is ImagePlot? ImagePlot is a free software tool that visualizes collections of images and video of any size. It is implemented as a macro which works with the open source image processing program ImageJ. ImagePlot was developed by the Software Studies Initiative with support from the National Endowment for Humanities (NEH), the California Institute for Telecommunications and Information Technology (Calit2), and the Center for Research in Computing and the Arts (CRCA). See your whole image collection in a single visualization.

Tips, tricks and resources to make your own gorgeous infographics Infographics (or Information Graphics) are graphic visual representations of data or information, presented in a way to make it easier to consume information. Infographics gained popularity in the mid-2000′s with the advent of sites like Digg and Reddit, and have quickly become one of the most popular methods to display researched data. There are three main types of infographics – where data is presented in a timeline, where statistical data is presented in graphs or with icons, or where data is presented on a map. In order to create an infographic which will be widely shared, think about your typography, colours, and layout. christopheviau Intro Data-Driven Documents, or D3 for short, is a new visualization library to build visualizations in SVG. But in my opinion, it's also the best javascript multipurpose SVG library when it comes to animation, interaction and above all for binding data to graphics. The community is very responsive, source code is very clean and the API is well written.

Pattern Pattern is a web mining module for the Python programming language. It has tools for data mining (Google, Twitter and Wikipedia API, a web crawler, a HTML DOM parser), natural language processing (part-of-speech taggers, n-gram search, sentiment analysis, WordNet), machine learning (vector space model, clustering, SVM), network analysis and <canvas> visualization. The module is free, well-document and bundled with 50+ examples and 350+ unit tests.

Features Gephi is a tool for data analysts and scientists keen to explore and understand graphs. Like Photoshop™ but for graph data, the user interacts with the representation, manipulate the structures, shapes and colors to reveal hidden patterns. The goal is to help data analysts to make hypothesis, intuitively discover patterns, isolate structure singularities or faults during data sourcing. It is a complementary tool to traditional statistics, as visual thinking with interactive interfaces is now recognized to facilitate reasoning.

mkweb.bcgsc.ca/schemaball/?home Schemaball is a flexible schema visualizer for SQL databases. The purpose of Schemaball is to help visualize the relationships between tables. Tables are related by foreign keys, which are fields which store the value of a record field from another table. Foreign keys create a lookup relationship between two tables. Large schemas can have hundreds of tables and table relationships. Keeping track of them call can be tedious, error-prone and slow down the schema development process.

Teaching data visualization: Recommended readings and resources I want to share the reading/resource list in my data visualization course; the list breaks into six sections: intro to data viz, choosing the right chart, designing a nice-looking visulization, communicating your message, tools/tips, and resources. This list will be a work in progress and all suggestions are welcomed. Intro to data visualization

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