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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 2. NumPy Arrays FREE CHAPTER 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

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:

$ pip3 install pony

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  
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 DataFrame.to_sql function:

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

The number of rows in the sunspots table is printed as follows:

[309]
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