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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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Tools
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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

PyMongo and MongoDB


MongoDB (humongous) is a NoSQL document-oriented database. The documents are stored in the BSON format, which is JSON like. You can download a MongoDB distribution from http://www.mongodb.org/downloads. Installing should be just a matter of unpacking a compressed archive. The version at the time of writing was 2.6.3. In the bin directory of the distribution, we will find the mongod file, which starts the server. MongoDB expects to find a /data/db directory. This is the directory where data is stored. We can specify another directory from the command line as follows:

$ mkdir /tmp/db

Start the database from the directory containing its binary executables:

./mongod --dbpath /tmp/db

We need to keep this process running to be able to query the database.

PyMongo is a Python driver for MongoDB. Install PyMongo as follows:

$ sudo pip install pymongo
$ pip freeze|grep pymongo
pymongo==2.7.1

Connect to the MongoDB test database:

from pymongo import MongoClient
client = MongoClient...
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