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Python Data Analysis

You're reading from   Python Data Analysis Learn how to apply powerful data analysis techniques with popular open source Python modules

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Product type Paperback
Published in Oct 2014
Publisher
ISBN-13 9781783553358
Length 348 pages
Edition 1st Edition
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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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Toc

Table of Contents (17) Chapters Close

Preface 1. Getting Started with Python Libraries 2. NumPy Arrays FREE CHAPTER 3. Statistics and Linear Algebra 4. pandas Primer 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
Index

Dataset – databases for lazy people


Dataset is a Python library, which is basically a wrapper around SQLAlchemy. It claims to be so easy to use that even lazy people like it.

Install dataset as follows:

$ sudo pip install dataset
$ pip freeze|grep dataset
dataset==0.5.4

Create a SQLite in-memory database and connect to it:

import dataset
db = dataset.connect('sqlite:///:memory:')

Create a table called books:

table = db["books"]

Actually, the table in the database isn't created yet, since we haven't specified any columns. We only created a related object. The table schema is created automatically from calls to the insert() method. Give the insert() method dictionaries with book titles:

table.insert(dict(title="NumPy Beginner's Guide", author='Ivan Idris'))
table.insert(dict(title="NumPy Cookbook", author='Ivan Idris'))
table.insert(dict(title="Learning NumPy", author='Ivan Idris'))

These are all excellent books, of course! The read_sql() pandas function can query this table too:

print read_sql(...
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