October 2015
Beginner
200 pages
3h 56m
English
book
Learning IPython for Interactive Computing and Data Visualization, Second Edition
by Cyrille Rossant
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Summary
In this chapter, we covered the basics of data analysis with pandas: loading a dataset, selecting rows and columns, grouping and aggregating quantities, and performing complex operations efficiently.
The next natural step is to conduct statistical analyses: hypothesis testing, modeling, predictions, and so on. Several Python libraries provide such functionality beyond pandas: SciPy, statsmodels, PyMC, and more. The IPython Cookbook contains many advanced examples of such analyses.
In the next chapter, we will introduce NumPy, the library underlying the entire SciPy ecosystem.
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.