Thank you for purchasing the MEAP for Pandas Workout. This book is all about improving your understanding of the “pandas” library for Python — but not by telling you about it. Rather, you’ll become more fluent with “pandas” as you work through numerous exercises, improving your skill a little bit at a time.
I’ve been using Python for about 30 years, and was a bit skeptical when I heard about using NumPy and “pandas” for data analysis. After all, Python is many things, but speedy and efficient aren’t two of them. It turns out that NumPy and “pandas” are implemented in C, with a thin layer of Python that makes them easy to use. You can analyze large quantities of data from within Python, without
Many people use NumPy — but “pandas” extends NumPy, providing additional functionality that makes it easy, and even fun, to do data analysis. You can think of “pandas” as an automatic transmission, compared with NumPy’s manual transmission. Both work, but “pandas” makes it easier, and allows us to think at a higher level of abstraction.
The thing is, “pandas” uses data structures that look and act different from regular Python data structures. And many of the classic techniques for working with Python are a bad idea with “pandas”. So learning what you should (and shouldn’t) do with “pandas” can take some time, even if you’re an old hand with Python.