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Python Business Intelligence Cookbook

Python Business Intelligence Cookbook

By : Dempsey
3.6 (9)
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Python Business Intelligence Cookbook

Python Business Intelligence Cookbook

3.6 (9)
By: Dempsey

Overview of this book

The amount of data produced by businesses and devices is going nowhere but up. In this scenario, the major advantage of Python is that it's a general-purpose language and gives you a lot of flexibility in data structures. Python is an excellent tool for more specialized analysis tasks, and is powered with related libraries to process data streams, to visualize datasets, and to carry out scientific calculations. Using Python for business intelligence (BI) can help you solve tricky problems in one go. Rather than spending day after day scouring Internet forums for “how-to” information, here you’ll find more than 60 recipes that take you through the entire process of creating actionable intelligence from your raw data, no matter what shape or form it’s in. Within the first 30 minutes of opening this book, you’ll learn how to use the latest in Python and NoSQL databases to glean insights from data just waiting to be exploited. We’ll begin with a quick-fire introduction to Python for BI and show you what problems Python solves. From there, we move on to working with a predefined data set to extract data as per business requirements, using the Pandas library and MongoDB as our storage engine. Next, we will analyze data and perform transformations for BI with Python. Through this, you will gather insightful data that will help you make informed decisions for your business. The final part of the book will show you the most important task of BI—visualizing data by building stunning dashboards using Matplotlib, PyTables, and iPython Notebook.
Table of Contents (7 chapters)
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6
Index

Importing a CSV file into MongoDB

Importing data from a CSV file into MongoDB is one of the fastest methods of import available. It is also one of the easiest. With almost every database system exporting to CSV, the following recipe is sure to come in handy.

Getting ready

The UK Road Safety Data comprises three CSV files: accidents7904.csv, casualty7904.csv, and vehicles7904.csv. Use this recipe to import the Accidents7904.csv file into MongoDB.

How to do it…

Run the following command at the command line:

./Applications/mongodb-3.0.4/bin/mongoimport --db pythonbicookbook --collection accidents --type csv --headerline --file '/Data/Stats19-Data1979-2004/Accidents7904.csv' --numInsertionWorkers 5

After running that command, you should see something similar to the following screenshot:

How to do it…

The following command is what you would use for Windows:

C:\Program Files\MongoDB\Server\3.0\bin\mongoimport --db pythonbicookbook --collection accidents --type csv --headerline --file C:\Data\Stats19...
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Python Business Intelligence Cookbook
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