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Jupyter Cookbook

You're reading from   Jupyter Cookbook Over 75 recipes to perform interactive computing across Python, R, Scala, Spark, JavaScript, and more

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788839440
Length 238 pages
Edition 1st Edition
Languages
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Author (1):
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Dan Toomey Dan Toomey
Author Profile Icon Dan Toomey
Dan Toomey
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Toc

Table of Contents (12) Chapters Close

Preface 1. Installation and Setting up the Environment 2. Adding an Engine FREE CHAPTER 3. Accessing and Retrieving Data 4. Visualizing Your Analytics 5. Working with Widgets 6. Jupyter Dashboards 7. Sharing Your Code 8. Multiuser Jupyter 9. Interacting with Big Data 10. Jupyter Security 11. Jupyter Labs

Reading text files

Text files, in contrast to those flat files, do not normally have column widths specified, nor do they have delimiters. The prototypical example would be programming logging files that are used by programmers to log the progress of their programs. The log files may have a consistent prefix to each record with a timestamp or such, but the rest of the record is completely up to the developer's needs.

Text files tend to be very large as well, easily running into many megabytes of storage.

An entirely new form of database has emerged for the storage and retrieval of text files, appropriately named text databases. Access to records in these databases is normally looking for strings that can be used to index the records. As before, log file entries normally have a consistent timestamp present, so you can order the results accordingly and file records occurring...

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