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Pandas Cookbook

You're reading from   Pandas Cookbook Recipes for Scientific Computing, Time Series Analysis and Data Visualization using Python

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Product type Paperback
Published in Oct 2017
Publisher Packt
ISBN-13 9781784393878
Length 532 pages
Edition 1st Edition
Languages
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Author (1):
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Theodore Petrou Theodore Petrou
Author Profile Icon Theodore Petrou
Theodore Petrou
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Toc

Table of Contents (12) Chapters Close

Preface 1. Pandas Foundations 2. Essential DataFrame Operations FREE CHAPTER 3. Beginning Data Analysis 4. Selecting Subsets of Data 5. Boolean Indexing 6. Index Alignment 7. Grouping for Aggregation, Filtration, and Transformation 8. Restructuring Data into a Tidy Form 9. Combining Pandas Objects 10. Time Series Analysis 11. Visualization with Matplotlib, Pandas, and Seaborn

Grouping by a Timestamp and another column

The resample method on its own, is unable to group by anything other than periods of time. The groupby method, however, has the ability to group by both periods of time and other columns.

Getting ready

In this recipe, we will show two very similar but different approaches to group by Timestamps and another column.

How to do it...

  1. Read in the employee dataset, and create a DatetimeIndex with the HIRE_DATE column:
>>> employee = pd.read_csv('data/employee.csv', 
parse_dates=['JOB_DATE...
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