Getting Started with Python Data Analysis
by: Phuong Vo.T.H – Martin Czygan
ISBN-10: 1785285114
ISBN-13: 9781785285110
Released: 2015-10
Pages: 188
Book Description
Data analysis is the process of applying logical and analytical reasoning to study each component of data. Python is a multi-domain,high-level,programming language. It’s often used as a scripting language because of its forgiving syntax and operability with a wide variety of different eco-systems. Python has powerful standard libraries or toolkits such as Pylearn2 and Hebel,which offers a fast,reliable,cross-platform environment for data analysis.
With this book,we will get you started with Python data analysis and show you what its advantages are.
The book starts by introducing the principles of data analysis and supported libraries,along with NumPy basics for statistic and data processing. Next it provides an overview of the Pandas package and uses its powerful features to solve data processing problems.
Moving on,the book takes you through a brief overview of the Matplotlib API and some common plotting functions for DataFrame such as plot. Next,it will teach you to manipulate the time and data structure,and load and store data in a file or database using Python packages. The book will also teach you how to apply powerful packages in Python to process raw data into pure and helpful data using examples.
Finally,the book gives you a brief overview of machine learning algorithms,that is,applying data analysis results to make decisions or build helpful products,such as recommendations and predictions using scikit-learn.
Contents
1: INTRODUCING DATA ANALYSIS AND LIBRARIES
2: NUMPY ARRAYS AND VECTORIZED COMPUTATION
3: DATA ANALYSIS WITH PANDAS
4: DATA VISUALIZATION
5: TIME SERIES
6: INTERACTING WITH DATABASES
7: DATA ANALYSIS APPLICATION EXAMPLES
8: MACHINE LEARNING MODELS WITH SCIKIT-LEARN
What You Will Learn
Understand the importance of data analysis and get familiar with its processing steps
Get acquainted with Numpy to use with arrays and array-oriented computing in data analysis
Create effective visualizations to present your data using Matplotlib
Process and analyze data using the time series capabilities of Pandas
Interact with different kind of database systems,such as file,disk format,Mongo,and Redis
Apply the supported Python package to data analysis applications through examples
Explore predictive analytics and machine learning algorithms using Scikit-learn,a Python library
Authors
Phuong Vo.T.H
Phuong Vo.T.H has a MSc degree in computer science,which is related to machine learning. After graduation,she continued to work in some companies as a data scientist. She has experience in analyzing users’ behavior and building recommendation systems based on users’ web histories. She loves to read machine learning and mathematics algorithm books,as well as data analysis articles.
Martin Czygan
Martin Czygan studied German literature and computer science in Leipzig,Germany. He has been working as a software engineer for more than 10 years. For the past eight years,he has been diving into Python,and is still enjoying it. In recent years,he has been helping clients to build data processing pipelines and search and analytics systems.
