It was really hard to run a lot of different analyses and then compare them. The for loops were there but not really intuitive. Stata was really good for academic data analysis but it didn't meet all of the needs for programming data analysis. I also loved that there was so much support online Moving from SPSS to Stata made me feel like I could actually keep track of the code myself. I liked that the syntax of the language was really intuitive. R works much better for the work I am doing now but Stata will always have a special place in my heart and I would recommend Stata to anyone who wants to start getting into data analysis but hasn't had a lot of programming training It was my favorite language until I learned R. Stata was really wonderful because it had a really low learning curve and I felt like it was a much better product than SPSS. Stata is really good for statistical analysis These issues mean that achieving what could be achieved in 3 lines of code in another language, might take 100s in Stata. It is quite un-intuitive for someone coming with a programming background, and has weird quirks - such as only being able to keep on dataset in memory at a time. For example, work with text etc is out of the picture. Furthermore, while this is excellent for canned statistical and econometric procedures, the programming language itself is not anywhere near as developed as something like R. But there are other free options, such as R. You're paying for something that is reliable, tried and true, with a great support network. Has a lot of related features like heatmaps, producing production-quality regression tables, etc. The graphics capabilities are also easy to use and very high quality.
It also has a matrix programming language (Mata). Online support through the statalist forum is also amazing. Reliable and fast, with a huge library of procedures built in, and an even bigger user-contributed library. This is statistical programming software that is excellent for canned econometric procedures. But for more general purpose statistical work, R is not only free, but better (even though it is more buggy). If you're willing to pay for it, performance is even better - using up to 64 cores. And it does these things reliably and fast, with a good support network. There are some things that Stata does extremely well - the statistics and econometrics in particular.
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