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Book Overview & Buying
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Table Of Contents
Python in Excel for Data Analytics
By :

https://packt.link/EarlyAccessCommunity
In the previous two chapters, you learned how to work with DataFrames in pandas and how to create visualizations with seaborn, respectively. Those chapters introduced each skill on its own. This chapter is about putting them together into a single, connected workflow that mirrors how data analysis actually happens in practice.
This workflow is known as the Exploratory data analysis, or EDA. It is the process of investigating a dataset before drawing conclusions or building models. It combines the data manipulation techniques from Chapter 2 with the visualization techniques from Chapter 3 into a practical workflow. The goal is to understand what your data contains, identify issues that need fixing, and spot patterns worth investigating further.
This chapter is organized as a series of practical techniques. Each section introduces a specific EDA task, shows you how to accomplish it with Python in Excel, and explains...