Whether you’re a professional Data Scientist, experienced academic researcher or a student learning the basics of data science, skills in creating publication-ready tables and graphics are essential. Visually-appealing, clear and error-free tables can help enhance any report or presentation, and for some publications such as scientific articles or white papers, formatting tables in line withContinue reading “How to Create Publication-Ready, Formatted Summary Statistics and Correlation Tables in R to Export to Excel or Word”
One of the major strengths of R and RStudio is the vast collection of packages to accomplish all sorts of specific tasks and larger projects. Whether you are trying to conduct advanced statistical analysis and machine learning, scrape data from the web, or create publication-ready graphics and visualizations, chances are R has a package availableContinue reading “How to Create and Publish a Nested Pie Chart in R with the Plotly Package (aka a Pie Chart within a Donut Chart)”
Whether you are just getting started in data science or have a wealth of experience, entering data science competitions is an excellent way to practice and demonstrate your skill with real world datasets. In the past few years, more and more organizations, companies and academic institutions have started offering contests for various data science projects,Continue reading “How to Enter and Win Data Science Competitions: 5 Insider Tips to Help You Succeed”
This is the fourth and final article in our series from Data Science for Anyone that covers ways in which ordinary people can develop skills in data science to apply in their day job, advance in their career or succeed in data science courses. Don’t miss the second featured article in our series, which coversContinue reading “How to Pick Your First Data Science Software Package: A Comparison of R, Python, Stata and SPSS”
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This is the third article in our series from Data Science for Anyone that covers ways in which ordinary people can develop skills in data science to apply in their day job, advance in their career or succeed in data science courses. Don’t miss the first featured article in our series which reviews the dataContinue reading “10 Essential Packages for Data Science in R”