You can apply hundreds of computations to millions of data points instantly with pandas. It is also easier to create and use complex equations and calculations on your data.
It's limited only by the computing power and memory of the computer it is running on. Pandas, however, has no limitation to the number of data points you can have in a DataFrame (their version of a data set). A million rows may seem like a lot of data, but for data scientists, this is but a drop in a bucket. At that point, your calculations would take forever to compute. In terms of pure space, Excel caps a single spreadsheet at 1,048,576 rows exactly. Pandas, on the other hand, has no real limit and handles millions of data points seamlessly. In Excel, once you exceed 10,000 rows, it starts to slow down - considerably. As a result, is extremely fast and efficient. Pandas operates right on the back of Python. Start training Analyze Large Data Sets Easily
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