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A podcast on data visualization with Enrico Bertini and Moritz Stefaner

A podcast on data visualization with Enrico Bertini and Moritz Stefaner
Related:  Data VisualizationTheory

Cartograma Un cartograma es un mapa o diagrama que muestra datos de cantidad asociados a respectivas áreas, mediante la modificación de los tamaños de las unidades de enumeración. La información es aportada mediante la distorsión de las superficies reales, utilizando cada superficie de enumeración como un símbolo proporcional, el cual aumenta o disminuye en función de los valores correspondientes. Un ejemplo podría ser la representación de los países, donde su tamaño en el diagrama dependiera del número de habitantes.[1] Al aumentar o disminuir las dimensiones en función de otra variable diferente al área, se pueden obtener mapas con un aspecto disparatado y chocante, lo que afectará a la comunicación cartográfica.[1] Características[editar] Clasificación[editar] El mismo cartograma realizado sin contigüidad. Se pueden distinguir dos tipos principales de cartogramas: los cartogramas con contigüidad y los cartogramas sin contigüidad, cada uno de los cuales tienen sus ventajas y desventajas.[1]

Set Measurements... Use this dialog box to specify which measurements are recorded by Analyze/Measure and Analyze/Analyze Particles. Area - Area of selection in square pixels. Area is in calibrated units, such as square millimeters, if Analyze>Set Scale was used to spatially calibrate the image. Mean Gray Value - Average gray value within the selection. This is the sum of the gray values of all the pixels in the selection divided by the number of pixels. Reported in calibrated units (e.g., optical density) if Analyze>Calibrate was used to calibrate the image. Standard Deviation - Standard deviation of the gray values used to generate the mean gray value. Modal Gray Value - Most frequently occurring gray value within the selection. Min & Max Gray Value - Minimum and maximum gray values within the selection. Centroid - The center point of the selection. Center of Mass - This is the brightness-weighted average of the x and y coordinates all pixels in the selection. Fit Ellipse - Fit an ellipse to the selection.

DataIsBeautiful Fell in Love with Data — Radio Ambulante #08b9c9 hex color In a RGB color space, hex #08b9c9 is composed of 3.1% red, 72.5% green and 78.8% blue. Whereas in a CMYK color space, it is composed of 96% cyan, 8% magenta, 0% yellow and 21.2% black. It has a hue angle of 185 degrees, a saturation of 92.3% and a lightness of 41%. #08b9c9 color hex could be obtained by blending #10ffff with #007393. Closest websafe color is: #00cccc. #08b9c9 color description : Strong cyan. The hexadecimal color #08b9c9 has RGB values of R:8, G:185, B:201 and CMYK values of C:0.96, M:0.08, Y:0, K:0.21. Hex triplet 08b9c9 #08b9c9 RGB Decimal 8, 185, 201 rgb(8,185,201) RGB Percent 3.1, 72.5, 78.8 rgb(3.1%,72.5%,78.8%) CMYK 96, 8, 0, 21 HSL 185°, 92.3, 41 hsl(185,92.3%,41%) HSV (or HSB) 185°, 96, 78.8 Web Safe 00cccc #00cccc CIE-LAB 68.725, -32.546, -19.067 XYZ 27.989, 38.964, 61.301 xyY 0.218, 0.304, 38.964 CIE-LCH 68.725, 37.72, 210.364 CIE-LUV 68.725, -51.153, -25.001 Hunter-Lab 62.421, -29.2, -14.531 Binary 00001000, 10111001, 11001001

SOFTWARE FOR DIGITAL HUMANITIES Software Studies Initiative researchers exploring a video collection using the tools developed in the lab. NEW: Guide to using ImagePlot in Polish by Radosław Bomba We have developed a number software tools for working with big image and video collections, including preparing image data, automatically analyzing it, and using visualization for the exploration of the collections. All tools are free and provided as open source. To see these tools in action, visit the projects page. GUIDE TO VISUALIZING VIDEO AND IMAGE SEQUENCES | How to prepare images and video collections for visualization; use of ImageJ built-in commands and our custom plug-ins. ImagePlot documentation (English) ImagePlot tutorial (Polish) ImagePlot video tutorials Below we list some of out tools by category, with links for download: workflow 1: First, use one of the tools listed in "digital image processing" section to process your image (or video) collection. These tools have been created and tested for our own projects.

Extreme Presentations Enrico Bertini Peity • progressive <canvas> pie charts Peity (sounds like deity) is a jQuery plugin that converts an element's content into a <svg> mini pie 2/5 donut 5,2,3 line 5,3,9,6,5,9,7,3,5,2 or bar chart 5,3,9,6,5,9,7,3,5,2 and is compatible with any browser that supports <svg>: Chrome, Firefox, IE9+, Opera, Safari. Download version 3.2.1 Uncompressed 8.7Kb jquery.peity.js Minified 3.6Kb (+gzipped 1.7Kb) jquery.peity.min.js Source Pie Charts Call peity("pie") on a jQuery selection. You can also pass delimiter, fill, height, radius and width options. <span class="pie">1/5</span><span class="pie">226/360</span><span class="pie">0.52/1.561</span><span class="pie">1,4</span><span class="pie">226,134</span><span class="pie">0.52,1.041</span><span class="pie">1,2,3,2,2</span> JavaScript $("span.pie").peity("pie") Donut Charts Donut charts are the same as pie charts and take the same options with an added innerRadius option which defaults to half the radius. $('.donut').peity('donut') Line Charts $(".line").peity("line") Events

ImageJ User Guide - IJ 1.46r | Installation The downloaded package may not contain the latest bug fixes so it is recommended to upgrade ImageJ right after a first installation. Updating IJ[?] consists only of running , which will install the latest ij.jar in the ImageJ folder (on Linux and Windows) or inside the (on Mac OS X). can be used to upgrade (or downgrade) the ij.jar file to release updates or daily builds. 2.1 ImageJDistributions ImageJ alone is not that powerful: it’s real strength is the vast repertoire of Plugins↓ that extend ImageJ’s functionality beyond its basic core. Below is a list of the most relevant projects that address the seeming difficult task of organizing and maintaining ImageJ beyond its basics. Fiji Fiji (Fiji Is Just ImageJ—Batteries included) is a distribution of ImageJ together with Java, Java 3D and several plugins organized into a coherent menu structure. MBF ImageJ Note that you can add plugins from MBF ImageJ to Fiji, combining the best of both programs. 2.2 Related Software 2.3 ImageJ2

storytelling with data

Related:  Enrico Bertini