Creating Animations and Transitions With D3

Construção de visualizações de dados em java

Construção de visualizações de dados em java

In interactive visualisation, there is the word reactive. Well, maybe not literally, but close enough.

The fact is that reactivity, or the propension of a visualisation to respond to user actions, can really help engage the user in a visualisation, and help them understand its results. Both of which are usually good things. How can this reactivity be achieved? Through animations.

So I’ll go ahead and state that animation, if done right, can make any interactive data visualization better.

How is that?

  • When coupled with interaction, it’s a very useful way to give feedback to the user. What has changed since their last command? If what’s on screen animates from one state to another, it’s obvious, it stands out and it makes sense. Or, when showing any form of real-time data, animation is pretty much required.
  • Animation can bring focus on the important things as a chart loads. Our vision is very sensitive to movement, so using these introduction transitions sensibly helps a lot to ease the effort required to get the right information off a chart.

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Handbook of Statistical Analysis and Data Mining Applications

Livro completo no google books com as ligações entre a estatística e o DM

Livro completo no google books com as ligações entre a estatística e o DM

Índice

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Novel Views: Les Miserables

Visualizações de dados inovadoras baseadas em text mining

Visualizações de dados inovadoras baseadas em text mining

Jeff Clark took a detailed look at Victor Hugo’s Les Miserables via character mentions, word connections, and word usage. The above is character mentions with color showing sentiment. Red means negative, and blue positive.

Characters are listed from top to bottom in their order of appearance. The horizontal space is segmented into the 5 volumes of the novel. Each volume is subdivided further with a faint line indicating the various books and, finally, small rectangles indicate the chapters within the books. In the 5 volumes there are a total of 48 books and 365 chapters. The height of the small rectangles indicate how frequently that character is mentioned in that particular chapter.

There’s a good amount of blue towards the end, when everyone decides everyone else isn’t so bad.

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Women as Academic Authors, 1665-2010

Exemplo de representação gráfica interativa com bolhas num eixo

Exemplo de representação gráfica interativa com bolhas num eixo

The Chronicle of Higher Education has a look at the percentage of academic papers published by women, over the past five centuries.

The articles and authors described in this data were drawn from the corpus of JSTOR, a digital archive of scholarly papers, by researchers at the Eigenfactor Project at the University of Washington. About two million articles, representing 1765 fields and sub-fields, were examined, spanning a period from 1665 to 2011. The data are presented here for three time periods, the latest one ending in 2010, and a view that combines all periods.

Percentage of female authors is on the horizontal, and each bubble is a subfield sized by total number of authors. The graphic starts with publishing for all years, but be sure to click on the tabs for each time span to see changes.

The data is based on the archive of about two million articles from JSTOR, and a hierarchical map equation method is used to determine subfields.

The gender classification they used for names seems like it could be nifty for some applications. Gender is inferred by comparing names against the ones kept by the U.S. Social Security Administration, which includes gender. If a name was used for female at least 95 percent of the time, it was classified as a female name, and the same was done with male. Anything ambiguous was not included in the study

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Advanced Statistics

Bons slides e outros materiais sobre clusters, AFE, SEM, reg logistica, meta-análise, MANOVA, Reliability

Bons slides e outros materiais sobre clusters, AFE, SEM, reg logistica, meta-análise, MANOVA, Reliability

Welcome to Malbowges, the part of Nether Hell dominated by thieves, counsellors of Fraud (or should that just be counsellors), falsifiers and sowers of discord. It’s not a nice place for Sunday lunch. You must wade through rivers of Lucifer’s sputum to reach the answers you seek, and when you find those answers, you’ll probably wish you hadn’t bothered. Revenge is mine, ah ha ha, yah ha ha, ya ha ha ha ha ha ha ha ha ha …

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Introductory Statistics

Muito boas aulas e slides sobre testes não paramétricos e SPSS

Muito boas aulas e slides sobre testes não paramétricos e SPSS

Welcome to Limbo, where the lustful, gluttonous and wrathful wander in endless torment. Here you can uncover the searing agony of SPSS, the stomach churning fear of central tendency and the rancid bile of z-scores. Good luck, you’ll need it.

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PANDA – Practical Analysis of Nutritional Data

Bom livro sobre análise de dados e testes estatísticos

Bom livro sobre análise de dados e testes estatísticos


Chapter 1 –
USING NUTRITIONAL DATA
Chapter 2 –
DATA CLEANING

Chapter 3 –
ONE-WAY ANALYSIS

Chapter 4 –
TWO-WAY ANALYSIS

Chapter 5 –
MULTI-WAY ANALYSIS

Chapter 6 –
SUBMODULES

Chapter 7 – ASSESS YOUR UNDERSTANDING
Chapter 8
KENYA REAL WORLD ANALYSIS

Building and presenting a situation analysis
Child Feeding Practices

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Determining the Number of Components and Factors Using Parallel Analysis and Velicer’s MAP Test

Softwere para análise do nº de componentes em ACP e AF

Softwere para análise do nº de componentes em ACP e AF

Popular statistical software packages do not have the proper procedures for determining the number of components or factors in correlation matrices. Parallel analysis and Velicer’s minimum average partial (MAP) test are validated procedures that are widely recommended by statisticians. This paper described brief and efficient programs for conducting parallel analyses and the MAP test using SPSS, SAS, and MATLAB.

Métodos para facilitar a interpretação da AFE

Métodos para facilitar a interpretação da AFE

Scale development using popular statistical software packages often produces results that are baffling or misunderstood by many users, which can lead to inappropriate substantive interpretations and item selection decisions. High internal consistencies do not indicate unidimensionality; item-total correlations are inflated because each item is correlated with its own error as well as the common variance among items; and the default number-of-eigenvalues-greater-than-one rule, followed by principal components analysis and varimax rotation, produces inflated loadings and the possible appearance of numerous uncorrelated factors for items that measure the same construct (Gorsuch, 1997a, 1997b). Concerned investigators may then neglect the higher order general factor in their data as they use misleading statistical output to trim items and fashion unidimensional scales.

These problems can be circumvented in exploratory factor analysis by using more appropriate factor analytic procedures and by using extension analysis as the basis for adding items to scales. Extension analysis provides correlations between nonfactored items and the factors that exist in a set of core items. The extension item correlations are then used to decide which factor, if any, a prospective item belongs to. The decisions are unbiased because factors are defined without being influenced by the extension items. One can also examine correlations between extension items and any higher order factor(s) in the core items. The end result is a comprehensive, undisturbed, and informative picture of the correlational structure that exists in a set of core items and of the potential contribution and location of additional items to the structure.

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How long will we live — and how well?

Gráfico animado de dispersão entre a esperança média de vida e a % de anos com saude

Gráfico animado de dispersão entre a esperança média de vida e a % de anos com saude

Circule entre os dois anos com informação para ver a animação.

For every year increase in life expectancy worldwide, healthy life expectancy increased about 9-1/2 months.

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OrgOrgChart: The Evolution of an Organization

As empresas são organismos vivos: animação do organigrama de uma grande empresa

As empresas são organismos vivos: animação do organigrama de uma grande empresa

The OrgOrgChart (Organic Organization Chart) project looks at the evolution of a company’s structure over time. A snapshot of the Autodesk organizational hierarchy was taken each day between May 2007 and June 2011, a span of 1498 days.

Each day the entire hierarchy of the company is constructed as a tree with each employee represented by a circle, and a line connecting each employee with his or her manager. Larger circles represent managers with more employees working under them. The tree is then laid out using a force-directed layout algorithm.

Each second in the animation is about one week of activity, and acquisitions are most obvious when big clumps of people join the company. The long-term changes are a little harder to see, because the branches in the network fade into the background. Recomputing the layout each week might be good for the next round.

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