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Software: Visualization and Data Mining

Software: Visualization and Data Mining

Homepage Online Charts Builder Hohli Online Charts Builder New version: Try new version of Charts Builder, it based on new Google Charts API Load From Image URL: Chart Data can't equal to original, but very similar to it. Only for images on Chart Type: 3D Pie charts Lines Bar charts Pie charts For Pie Charts with labels choose 1000x300 or 800x375 size Venn diagrams Scatter plots Radar charts Chart Size: 320x240 Horizontal 1000x300 800x375 600x500 320x240 Vertical 300x1000 375x800 500x600 240x320 Square 546x546 400x400 300x300 200x200 Chart Ads: Data: Should be consists only positive numbers, use minus one (-1) for missing value, separated by coma, space or semi(,; ), e.g.: 23, 432, 456, 341 For Lines (pairs): Input data as x-axis and y-axis coordinates, e.g.: x1,y1, x2,y2, x3,y3 Title: Use a pipe character (|) to force a line break in title. Background: Chart is ready you can save it as image Right click on the chart Select "Save image as" Save the image to your computer © 2011 Charts Builder. Developed by Anton Shevchuk

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

How to Visualize and Compare Distributions There are a lot of ways to show distributions, but for the purposes of this tutorial, I’m only going to cover the more traditional plot types like histograms and box plots. Otherwise, we could be here all night. Plus the basic distribution plots aren’t exactly well-used as it is. Before you get into plotting in R though, you should know what I mean by distribution. It’s basically the spread of a dataset. What happens in between the maximum value and median? Want more? If you don’t have R installed yet, do that now. Box-and-Whisker Plot This old standby was created by statistician John Tukey in the age of graphing with pencil and paper. The method might be old, but they still work for showing basic distribution. To get started, load the data in R. Remove the District of Columbia from the loaded data. Oh, and you don’t need the national averages for this tutorial either. Now all you have to do to make a box plot for say, robbery rates, is plug the data into boxplot(). Histogram Look, ma! Rug