> "But it’s worth noting that for the most part, people already had tools for analyzing data. They came in the form of SAS, Stata, SPSS, Minitab, Microsoft Exce

> "But it’s worth noting that for the most part, people already had tools for analyzing data. They came in the form of SAS, Stata, SPSS, Minitab, Microsoft Excel, and my personal favorite, XLisp-Stat (thanks Luke Tierney!). But the commonly used data analysis packages had some key downsides: -The graphics were too “quick and dirty” and did not allow much control over the details; they plotted the data, but that was about it; -There was relatively little ability to build custom tools on top of what was available (although some capability was added to most packages later)." Besides the XLISP-Stat, none of those are open source, so you cant fix the bugs yourself and when there is a bug the company tries to hide it. I wouldn't even put any of those tools in the same category as R when it comes to serious data processing/analysis/stats. Its more R vs python.