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Python Data Analysis, Second Edition

You're reading from   Python Data Analysis, Second Edition Data manipulation and complex data analysis with Python

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781787127487
Length 330 pages
Edition 2nd Edition
Languages
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Author (1):
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Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
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Table of Contents (16) Chapters Close

Preface 1. Getting Started with Python Libraries FREE CHAPTER 2. NumPy Arrays 3. The Pandas Primer 4. Statistics and Linear Algebra 5. Retrieving, Processing, and Storing Data 6. Data Visualization 7. Signal Processing and Time Series 8. Working with Databases 9. Analyzing Textual Data and Social Media 10. Predictive Analytics and Machine Learning 11. Environments Outside the Python Ecosystem and Cloud Computing 12. Performance Tuning, Profiling, and Concurrency A. Key Concepts
B. Useful Functions C. Online Resources

Apache Cassandra


Apache Cassandra mixes features of key-value and traditional relational databases. In a conventional relational database, the columns of a table are fixed. In Cassandra, however, rows within the same table can have different columns. Cassandra is, therefore, column-oriented, since it allows a flexible schema for each row. Columns are organized in so-called column families, which are equivalent to tables in relational databases. Joins and subqueries are not possible with Cassandra. Cassandra can be downloaded from http://cassandra.apache.org/download/. We used Cassandra version 3.9 at the time of writing this book. Please refer to http://wiki.apache.org/cassandra/GettingStarted to get started:

  1. Run the server from the command line as follows:

    $ bin/cassandra-f
    
  2. Create the directories listed in conf/cassandra.yaml or tweak them as follows:

    data_file_directories:
    /tmp/lib/cassandra/data
    commitlog_directory: /tmp/lib/cassandra/commitlog
    saved_caches_directory: /tmp/lib/cassandra...
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