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Introduction to Using Chart Tools - Google Chart Tools

Introduction to Using Chart Tools - Google Chart Tools
Google Charts provides a perfect way to visualize data on your website. From simple line charts to complex hierarchical tree maps, the chart gallery provides a large number of ready-to-use chart types. The most common way to use Google Charts is with simple JavaScript that you embed in your web page. You load some Google Chart libraries, list the data to be charted, select options to customize your chart, and finally create a chart object with an id that you choose. Then, later in the web page, you create a <div> with that id to display the Google Chart. That's all you need to get started. Charts are exposed as JavaScript classes, and Google Charts provides many chart types for you to use. All chart types are populated with data using the DataTable class, making it easy to switch between chart types as you experiment to find the ideal appearance. Ready to create your first chart? Related:  Data Vizualizationvisualisation

JpGraph - Most powerful PHP-driven charts StatPlanet StatPlanet (formerly StatPlanet Map Maker) is a free, award-winning application for creating fully customizable interactive maps. StatPlanet can be used to visualize location-based statistical data, such as life expectancy by country or demographic statistics and voting patterns by US state. In addition to maps, StatPlanet also has the option of including interactive graphs and charts to create feature-rich interactive infographics. If you wish to use StatPlanet for commercial purposes, please contact us. Restrictions: StatPlanet comes with only two maps: a world map (country level) and a US map (state level). Create an interactive map in 5 steps Open StatPlanet.exe to view the results offline, or open StatPlanet.html to view the results in a web-browser. For further details, see the StatPlanet User Guide (PDF) Create an interactive map in 5 minutes instructional video Enable macros in Excel If you do not receive this message, the macro security level in Excel is set to high.

SVG Graphics Library for JavaScript HTML5 :jsDraw2DX Cube Time Series Data Collection & Analysis Cube is a system for collecting timestamped events and deriving metrics. By collecting events rather than metrics, Cube lets you compute aggregate statistics post hoc. Collecting Data An event in Cube is simply a JSON object with a type, time, and arbitrary data. Cube’s collector receives events and saves them to MongoDB. Querying Events Cube defines a simple language for querying events. You can intersect filters and customize which event fields are returned. request(browser).gt(duration, 250).lt(duration, 500) Cube supports both HTTP GET and WebSockets for retrieving events. Querying Metrics You can also use Cube to group events by time, map to derived values, and reduce to aggregate metrics. The first few results of which appear as: Or, to count requests to the path "/search", change the expression: sum(request.eq(path, "/search")) sum(request(duration)) Want to learn more?

Gallery · mbostock/d3 Wiki Wiki ▸ Gallery Welcome to the D3 gallery! More examples are available for forking on Observable; see D3’s profile and the visualization collection. Please share your work on Observable, or tweet us a link! Visual Index Basic Charts Techniques, Interaction & Animation Maps Statistics Examples Collections The New York Times visualizations Jerome Cukier Jason Davies Jim Vallandingham Institute for Health Metrics and Evaluation Peter Cook Charts and Chart Components Bar Chart Histogram Pareto Chart Line and Area Chart Pie Chart Scatterplot and Bubble chart Parallel Coordinates, Parallel sets and Sankey Sunburst and Partition layout Force Layout Tree Misc Trees and Graphs Chord Layout (Circular Network) Maps Misc Charts Miscellaneous visualizations Charts using the reusable API Useful snippets Tools Interoperability Online Editors Products Store Apps

Read Alice's Adventures in Wonderland Note that this program is new research, and will not work on all machines. It has been tested to run on a machine of the following description: 600 Mhz Pentium III or faster, or a recent Mac 1024 x 768 pixel screen or higher resolution, 16 bit color Windows NT, Windows 2000, Windows XP operating systems, or Mac OS X 256 Mb of RAM A fast internet connection No other memory-intensive programs running Microsoft Internet Explorer (5 or later) Netscape (6.2 or later) TextArc will often stop working the second time it is run in the same browser session. This is caused by the browser remembering parts of the program after it should have exited. Note: TextArc will open a window that covers your primary monitor's desktop. Enjoy! Click this link to start TextArc Click this link to start TextArc in a window, or just look at the still screen shots.

D3.js - Data-Driven Documents Gephi, an open source graph visualization and manipulation software Springy - A force directed graph layout algorithm in JavaScript. kennethkufluk/js-mindmap Convert Files - free online file converter and flash video downloader.Convert videos, audio files, documents and ebooks.YouTube to MP3 Parallel Sets Parallel Sets (ParSets) is a visualization application for categorical data, like census and survey data, inventory, and many other kinds of data that can be summed up in a cross-tabulation. ParSets provide a simple, interactive way to explore and analyze such data. Even though the screenshots here show the Mac version, the program also runs on Windows and Linux. Links to the executables are in the Download Section. Basic Operation To open an existing dataset, select it in the list and either double-click it or click the Open button. The horizontal bars in the visualization show the absolute frequency of how often each category occurred: in this example, the top line shows the distribution between the passenger classes on the Titanic and the crew. The middle dimension shows a male to female ratio of almost 4 to 1. Between the dimension bars are ribbons that connect categories and split up. Interaction Move your mouse over the display to see the tooltip telling you more about the data.

Addepar | Ember Charts A charting library built with the Ember.js and d3.js frameworks. It includes time series, bar, pie, and scatter charts which are easy to extend and modify. The out-of-the-box behavior these chart components represents our thoughts on best practices in chart interactivity and presentation. Features Highly customizable and extensible. Rich with features - add legends, labels, tooltips, and mouseover effects. You can contribute to this project in one of two ways: Browse the ember-charts issues and report bugs Clone the ember-charts repo, make some changes according to our development guidelines and issue a pull-request with your changes. We keep the ember-charts.js code to the minimum necessary, giving users as much control as possible.

Chartkick Simplify your admin dashboard - create new charts in seconds! Works with Rails, Sinatra and most browsers (including IE 6) A perfect companion to groupdate, hightop, and active_median Get handcrafted updates for new features Usage Line chart You must have groupdate installed to use the group_by_day method Pie chart Grape Column chart Bar chart Area chart Geo chart Timeline Multiple series breakfast or Say Goodbye To Timeouts Make your pages load super fast and stop worrying about timeouts. And in your controller, pass the data as JSON. class ChartsController < ApplicationController def completed_tasks render json: Task.group_by_day(:completed_at).count endend Note: This feature requires jQuery or Zepto at the moment. For multiple series, add chart_json at the end. render json: Task.group(:goal_id).group_by_day(:completed_at).count.chart_json Options Id and height Min and max values min defaults to 0 for charts with non-negative values. Colors Stacked columns or bars Discrete axis Global Options Customize the html

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