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Learning pandas

You're reading from   Learning pandas High performance data manipulation and analysis using Python

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Product type Paperback
Published in Jun 2017
Publisher
ISBN-13 9781787123137
Length 446 pages
Edition 2nd Edition
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Author (1):
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Michael Heydt Michael Heydt
Author Profile Icon Michael Heydt
Michael Heydt
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Table of Contents (16) Chapters Close

Preface 1. pandas and Data Analysis 2. Up and Running with pandas FREE CHAPTER 3. Representing Univariate Data with the Series 4. Representing Tabular and Multivariate Data with the DataFrame 5. Manipulating DataFrame Structure 6. Indexing Data 7. Categorical Data 8. Numerical and Statistical Methods 9. Accessing Data 10. Tidying Up Your Data 11. Combining, Relating, and Reshaping Data 12. Data Aggregation 13. Time-Series Modelling 14. Visualization 15. Historical Stock Price Analysis

Summary

In this chapter, we have examined various techniques of tidying data. We covered identifying missing data, replacing it with other values, or dropping it from the overall set of data. We then covered how to transform values into other values that may be better suited for further analysis.

Now that we have tidied up our data within DataFrame or series, we want to move from focusing on the cleanliness of the data to more elaborate forms of modifying the structure of the data, such as concatenation, merges, joins, and pivoting data. This will be the focus of the next chapter.

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