Book Image

Practical Data Analysis - Second Edition

By : Hector Cuesta, Dr. Sampath Kumar
Book Image

Practical Data Analysis - Second Edition

By: Hector Cuesta, Dr. Sampath Kumar

Overview of this book

Beyond buzzwords like Big Data or Data Science, there are a great opportunities to innovate in many businesses using data analysis to get data-driven products. Data analysis involves asking many questions about data in order to discover insights and generate value for a product or a service. This book explains the basic data algorithms without the theoretical jargon, and you’ll get hands-on turning data into insights using machine learning techniques. We will perform data-driven innovation processing for several types of data such as text, Images, social network graphs, documents, and time series, showing you how to implement large data processing with MongoDB and Apache Spark.
Table of Contents (21 chapters)
Practical Data Analysis - Second Edition
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface

Getting started with pandas


The pandas library is a great library for data manipulation and analysis, written by Wes McKinney. The pandas library provides us with the optimized data structures, series and DataFrame, which are well-suited for descriptive statistics, indexing, and aggregation. Pandas is already installed in the Anaconda distribution used in Wakari. In this section, we will present the basic operations with pandas for Time Series and Multivariate data. We can find more information about pandas from its website:

http://pandas.pydata.org/

Working with Time Series

Time Series help us to understand the changes in a variable over time. Pandas include specific functionality in order to work with Time Series transparently. For this section, we need to upload the Gold.csv file used in Chapter 7, Predicting Gold Prices. The first five rows in the file will look like this:

date,price
1/31/2003,367.5
2/28/2003,347.5
3/31/2003,334.9
4/30/2003,336.8
5/30/2003,361.4
.  .  .

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