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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 FREE CHAPTER 2. NumPy Arrays 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

Pony ORM


Pony ORM is another Python ORM package. Pony ORM is written in pure Python and has automatic query optimization and a GUI database schema editor. It also supports automatic transaction management, automatic caching, and composite keys. Pony ORM uses Python generator expressions, which are translated in SQL. Install it as follows:

$ sudo pip install pony
$ pip freeze|grep pony
pony==0.5.1

Import the packages we will need in this example. Refer to the pony_ride.py file in this book's code bundle:

from pony.orm import Database, db_session 
from pandas.io.sql import write_frame
import statsmodels.api as sm

Create an in-memory SQLite database:

db = Database('sqlite', ':memory:')

Load the sunspots data and write it to the database with the pandas write_frame() function:

with db_session:
    data_loader = sm.datasets.sunspots.load_pandas()
    df = data_loader.data
    write_frame(df, "sunspots", db.get_connection())
    print db.select("count(*) FROM sunspots")

The number of rows in the sunspots...

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