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Mastering pandas

You're reading from   Mastering pandas A complete guide to pandas, from installation to advanced data analysis techniques

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Product type Paperback
Published in Oct 2019
Publisher
ISBN-13 9781789343236
Length 674 pages
Edition 2nd Edition
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Author (1):
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Ashish Kumar Ashish Kumar
Author Profile Icon Ashish Kumar
Ashish Kumar
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Table of Contents (21) Chapters Close

Preface 1. Section 1: Overview of Data Analysis and pandas FREE CHAPTER
2. Introduction to pandas and Data Analysis 3. Installation of pandas and Supporting Software 4. Section 2: Data Structures and I/O in pandas
5. Using NumPy and Data Structures with pandas 6. I/Os of Different Data Formats with pandas 7. Section 3: Mastering Different Data Operations in pandas
8. Indexing and Selecting in pandas 9. Grouping, Merging, and Reshaping Data in pandas 10. Special Data Operations in pandas 11. Time Series and Plotting Using Matplotlib 12. Section 4: Going a Step Beyond with pandas
13. Making Powerful Reports In Jupyter Using pandas 14. A Tour of Statistics with pandas and NumPy 15. A Brief Tour of Bayesian Statistics and Maximum Likelihood Estimates 16. Data Case Studies Using pandas 17. The pandas Library Architecture 18. pandas Compared with Other Tools 19. A Brief Tour of Machine Learning 20. Other Books You May Enjoy

Summary

In this chapter, we discussed time series data and the steps you can take to process and manipulate it. A date column can be assigned as an index for Series or DataFrame and can then be used for subsetting them based on the index column. Time series data can be resampled—to either increase or decrease the frequency of the time series. For example, data generated every millisecond can be resampled to capture the data only every second or can be averaged for 1,000 milliseconds for each second. Similarly, data generated every minute can be resampled to have data every second by backfilling or forward filling (filling in the same value as the last or next minute value for all the seconds in that minute).

String to datetime conversion can be done via the datetime, strptime, and strftime packages , and each type of date entry (for example, 22nd July, 7/22/2019, and...

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