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You're reading from  Python Data Mining Quick Start Guide

Product typeBook
Published inApr 2019
Reading LevelBeginner
PublisherPackt
ISBN-139781789800265
Edition1st Edition
Languages
Python
Concepts
Data Mining
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Author (1)
Nathan Greeneltch
Nathan Greeneltch
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Nathan Greeneltch

Nathan Greeneltch, PhD is a ML engineer at Intel Corp and resident data mining and analytics expert in the AI consulting group. Hes worked with Python analytics in both the start-up realm and the large-scale manufacturing sector over the course of the last decade. Nathan regularly mentors new hires and engineers fresh to the field of analytics, with impromptu chalk talks and division-wide knowledge-sharing sessions at Intel. In his past life, he was a physical chemist studying surface enhancement of the vibration signals of small molecules; a topic on which he wrote a doctoral thesis while at Northwestern University in Evanston, IL. Nathan hails from the southeastern United States, with family in equal parts from Arkansas and Florida
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Types of data sources and loading into pandas

This part of the chapter will show you how to load data in the computer memory. This is, of course, essential to all the downstream work and analysis that you plan to do.

Databases

A relational database is one of the most common ways that enterprises can store data. So, loading from and interacting with databases is essential for most fieldwork. The Python library that we will use is sqlite3 and is included in Anaconda's package. Let's begin by connecting to the database, which is stored in a .db file, and included with the book materials. After we connect to the database, we will create a cursor object that we will use to traverse the object during a query. Next, we...

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Python Data Mining Quick Start Guide
Published in: Apr 2019Publisher: PacktISBN-13: 9781789800265
© 2019 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Nathan Greeneltch

Nathan Greeneltch, PhD is a ML engineer at Intel Corp and resident data mining and analytics expert in the AI consulting group. Hes worked with Python analytics in both the start-up realm and the large-scale manufacturing sector over the course of the last decade. Nathan regularly mentors new hires and engineers fresh to the field of analytics, with impromptu chalk talks and division-wide knowledge-sharing sessions at Intel. In his past life, he was a physical chemist studying surface enhancement of the vibration signals of small molecules; a topic on which he wrote a doctoral thesis while at Northwestern University in Evanston, IL. Nathan hails from the southeastern United States, with family in equal parts from Arkansas and Florida
Read more about Nathan Greeneltch

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