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Python Data Mining Quick Start Guide

You're reading from   Python Data Mining Quick Start Guide A beginner's guide to extracting valuable insights from your data

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Product type Paperback
Published in Apr 2019
Publisher Packt
ISBN-13 9781789800265
Length 188 pages
Edition 1st Edition
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Author (1):
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Nathan Greeneltch Nathan Greeneltch
Author Profile Icon Nathan Greeneltch
Nathan Greeneltch
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Table of Contents (9) Chapters Close

Preface 1. Data Mining and Getting Started with Python Tools 2. Basic Terminology and Our End-to-End Example FREE CHAPTER 3. Collecting, Exploring, and Visualizing Data 4. Cleaning and Readying Data for Analysis 5. Grouping and Clustering Data 6. Prediction with Regression and Classification 7. Advanced Topics - Building a Data Processing Pipeline and Deploying It 8. Other Books You May Enjoy

An end-to-end example of data mining in Python

Let's start with a full end-to-end example demonstrating the topics and strategies covered in the rest of the book. Subsequent chapters will go into further detail on each part of the analytical process. I suggest that you read through this example fully before moving on in the book.

Loading data into memory – viewing and managing with ease using pandas

First, we will need to load data into memory so that Python can interact with it. Pandas will be our data management and manipulation library:

# load data into Pandas
import pandas as pd
df = pd.read_csv("./data/iris.csv")

Let's use some built-in pandas features to do sanity checks on our data load and...

You have been reading a chapter from
Python Data Mining Quick Start Guide
Published in: Apr 2019
Publisher: Packt
ISBN-13: 9781789800265
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