Category Archives: Data Science

Using Excel for Data Entry

This article shows you how to enter data so that you can easily open in statistics packages such as R, SAS, SPSS, or jamovi (code or GUI steps below). Excel has some statistical analysis capabilities, but they often provide incorrect answers. For … Continue reading

Posted in Data Science, R, SAS, SPSS | 4 Comments

Gartner’s 2018 Take on Data Science Tools

I’ve just updated The Popularity of Data Science Software to reflect my take on Gartner’s 2018 report, Magic Quadrant for Data Science and Machine Learning Platforms. To save you the trouble of digging though all 40+ pages of my report, … Continue reading

Posted in Analytics, Data Science, Python, R, SAS, Statistics, Uncategorized | 3 Comments

jamovi for R: Easy but Controversial

jamovi is software that aims to simplify two aspects of using R. It offers a point-and-click graphical user interface (GUI). It also provides functions that combines the capabilities of many others, bringing a more SPSS- or SAS-like method of programming … Continue reading

Posted in Data Science, R, SAS, SPSS, Statistics, Uncategorized | 4 Comments

Data Science Tool Market Share Leading Indicator: Scholarly Articles

Below is the latest update to The Popularity of Data Science Software. It contains an analysis of the tools used in the most recent complete year of scholarly articles. The section is also integrated into the main paper itself. New … Continue reading

Posted in Analytics, Data Science, Python, R, SAS, SPSS, Stata, Statistics, Uncategorized | 4 Comments

Dueling Data Science Surveys: KDnuggets & Rexer Go Live

What tools do we use most for data science, machine learning, or analytics? Python, R, SAS, KNIME, RapidMiner,…? How do we use them? We are about to find out as the two most popular surveys on data science tools have … Continue reading

Posted in Data Science, Python, R, SAS, Statistics | 4 Comments

Group-By Modeling in R Made Easy

There are several aspects of the R language that make it hard to learn, and repeating a model for groups in a data set used to be one of them. Here I briefly describe R’s built-in approach, show a much … Continue reading

Posted in Data Mangement, Data Science, R, Uncategorized | 16 Comments

Keeping Up with Your Data Science Options

The field of data science is changing so rapidly that it’s quite hard to keep up with it all. When I first started tracking The Popularity of Data Science Software in 2010, I followed only ten packages, all of them classic … Continue reading

Posted in Analytics, Data Science, Python, R, Statistics, Uncategorized | 2 Comments

Python and R Vie for Top Spot in Kaggle Competitions

I’ve just updated the Competition Use section of The Popularity of Data Science Software. Here’s just that section for your convenience. Competition Use Kaggle.com is a web site that sponsors data science contests. People post problems there along the amount … Continue reading

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The Tidyverse Curse

I’ve just finished a major overhaul to my widely read article, Why R is Hard to Learn. It describes the main complaints I’ve heard from the participants to my workshops, and how those complaints can often be mitigated. Here’s the only … Continue reading

Posted in Data Science, R | 17 Comments

Forrester’s 2017 Take on Tools for Data Science

In my ongoing quest to track The Popularity of Data Science Software, I’ve updated the discussion of the annual report from Forrester, which I repeat here to save you from having to read through the entire document. If your organization … Continue reading

Posted in Analytics, Data Science, R, SAS, SPSS | 2 Comments