Oscar: A Semantic-based Data Binning Approach

2002

Statisticians recommend graphical displays but often use tables to present their own research results. Could graphs do better? We study the question by going through the tables in a recent issue of the Journal of the American Statistical Association. We show how it is possible to improve the presentationsusing graphs that actually take up less space than the original tables. We nd a particularly effective tool to be multiple repeated line plots, with comparisons of interest connected by lines and separate comparisons isolated on different plots.

Teaching Statistics, 2007

numbers, but many people give little consideration to the order in which they present the data. This article illustrates the strengths and weaknesses of four criteria for organizing data -empirical, theoretical, alphabetical and a standardized reporting scheme.

Methods of Information in Medicine, 2014

Objectives-Graphical displays can make data more understandable; however, large graphs can challenge human comprehension. We have previously described a filtering method to provide high-level summary views of large data sets. In this paper we demonstrate our method for setting and selecting thresholds to limit graph size while retaining important information by applying it to large single and paired data sets, taken from patient and bibliographic databases.

2020

Statisticians recommend graphical displays but often use tables to present their own research results. Could graphs do better? We study the question by going through the tables in a recent issue of the Journal of the American Statistical Association. We show how it is possible to improve the presentationsusing graphs that actually take up less space than the original tables. We nd a particularly effective tool to be multiple repeated line plots, with comparisons of interest connected by lines and separate comparisons isolated on different plots.

Journal of Open Source Software, 2021

seaborn is a library for making statistical graphics in Python. It provides a high-level interface to matplotlib and integrates closely with pandas data structures. Functions in the seaborn library expose a declarative, dataset-oriented API that makes it easy to translate questions about data into graphics that can answer them. When given a dataset and a specification of the plot to make, seaborn automatically maps the data values to visual attributes such as color, size, or style, internally computes statistical transformations, and decorates the plot with informative axis labels and a legend. Many seaborn functions can generate figures with multiple panels that elicit comparisons between conditional subsets of data or across different pairings of variables in a dataset. seaborn is designed to be useful throughout the lifecycle of a scientific project. By producing complete graphics from a single function call with minimal arguments, seaborn facilitates rapid prototyping and exploratory data analysis. And by offering extensive options for customization, along with exposing the underlying matplotlib objects, it can be used to create polished, publication-quality figures.

Biometrics, 2008

2012

Visual overviews of tables of numerical and categorical data have been proposed for tables with a single value per cell. This paper addresses the problem of exploring tables whose columns consist of cells that are distributions, eg the distributions of movie ratings or trust ratings in recommender systems, age distributions in demographic data, usage distributions in logs of telephone calls etc. We expand on heatmap approaches and propose a novel way of displaying and interacting with distribution data. Our usability study ...

More and more researchers study large data sources. Solely through their size alone, getting insight into the data in these sources is difficult. A visualization method, commonly referred to as a tableplot, was found extremely useful for this purpose. A tableplot is a method that is able to display the aggregated distribution patterns of a dozen of variables in one single figure. We demonstrate that information on data quality and the presence and selectivity of missing data is obtained. In our opinion, the tableplot is an very valuable addition to the standard set of statistical tools commonly used for data exploration, processing, and analysis. A tool to create tableplots has been implemented as a package for the open source statistical software environment R and made publically available.

2010

Abstract���While visual overviews of tables of numerical and categorical data have been proposed for tables with a single value per cell, it is difficult to summarize tables containing columns of distributions (eg the distributions of ages or ethnicity across counties, or the distribution of movie ratings and trust ratings in recommender systems). We present a novel way of displaying and manipulating overviews of distribution columns to reveal interesting patterns and outliers or find possible correlations between columns.

Proceedings. 1997 IEEE Conference on Information Visualization (Cat. No.97TB100165), 1997

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