March 2020
Beginner to intermediate
352 pages
8h 40m
English
Content preview from Hands-On Exploratory Data Analysis with Python
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Summary
In this chapter, we discussed several data wrangling techniques, including database-style frame merging, concatenation along an axis, combining different frames, reshaping, removing duplicates, renaming axis indexes, discretization and binning, detecting and filtering outliers, and transformation functions. We have used different datasets to understand different data transformation techniques.
In the next chapter, we are going to discuss in detail different descriptive statistics measures, including the measure of the central tendency and the measure of dispersion. Furthermore, we shall be using Python 3 with different libraries, including SciPy, Pandas, and NumPy, to understand such descriptive measures.
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