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Serious question: I've tried to use Pandas for some data analysis for my small business. Data sets are on the order of 10,000 data points or less. After struggling for days with Pandas, I've begun to wonder if it wouldn't be easier to code the analyses in raw Python. I wouldn't mind taking longer to complete the task at hand if in the process I was acquiring skills that will pay off down the road, but I wonder if Pandas isn't so esoteric and difficult that I may never reach the point that I can cash in that investment of time and effort as long as I am only a casual user.

In contrast, while I'm not an expert in JS or Python, I find that time spent struggling with those technologies pays dividends since the lessons learned make everything I do in the future easier.

This is highly subjective of course, but in your opinion, should I keep fighting with Pandas? Is it worth it?




Make sure you learn what a Series is and how it relates to the things in the DataFrame and how selection works, specifically .loc and .iloc. Then your life will be much easier. Try starting with this article: https://medium.com/dunder-data/selecting-subsets-of-data-in-...


10,000 data points is well within the range of what Excel can handle without needing PowerQuery. What type of analyses are you attempting?


Linear optimization and generating some simple graphs. I would like to be able to at least generate the graphs automatically from my database.


> Linear optimization

Did you mean linear regression? Linear optimization isn't a use case that Pandas covers, but there are other tools that I can recommend.


Yes, that's what I meant.


I would recommend to "keep fighting with Pandas". Many of its feature seem confusing at first, but later on you see the value of them.




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