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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

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 3.4.0. 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:

$ pip3 install pymongo

Connect to the MongoDB test database:

from pymongo import MongoClient 
client = MongoClient() 
db = client.test_database 

Remember that...

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