Python for Data Science for Dummies

John Paul Mueller,Luca Massaron

Verlag: Wiley India Pvt. Ltd, 2015
ISBN 10: 8126557397 / ISBN 13: 9788126557394
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This book is designed for beginners to data analysis and covers the basics of Python data analysis programming and statistics. It covers the Python fundamentals that are necessary to data analysis, including objects, functions, modules and libraries. The libraries that are integral to data science are explored and explained, including NumPy, SciPy, BeautifulSoup, Pandas and MatPlobLib. Introduction About This Book Foolish Assumptions Icons Used in This Book Beyond the Book Where to Go from Here Part I: Getting Started with Python for Data Science Chapter 1: Discovering the Match between Data Science and Python Defining the Sexiest Job of the 21st Century Considering the emergence of data science Outlining the core competencies of a data scientist Linking data science and big data Understanding the role of programming Creating the Data Science Pipeline Preparing the data Performing exploratory data analysis Learning from data Visualizing Obtaining insights and data products Understanding Python`s Role in Data Science Considering the shifting profile of data scientists Working with a multipurpose, simple and efficient language Learning to Use Python Fast Loading data Training a model Viewing a result Chapter 2: Introducing Python`s Capabilities and Wonders Why Python? Grasping Python`s core philosophy Discovering present and future development goals Working with Python Getting a taste of the language Understanding the need for indentation Working at the command line or in the IDE Performing Rapid Prototyping and Experimentation Considering Speed of Execution Visualizing Power Using the Python Ecosystem for Data Science Accessing scientific tools using SciPy Performing fundamental scientific computing using NumPy Performing data analysis using pandas Implementing machine learning using Scikit learn Plotting the data using matplotlib Parsing HTML documents using Beautiful Soup Chapter 3: Setting Up Python for Data Science Considering the Off the Shelf Cross Platform Scientific Distributions Getting Continuum Analytics Anaconda Getting Enthought Canopy Express Getting pythonxy Getting WinPython Installing Anaconda on Windows Installing Anaconda on Linux Installing Anaconda on Mac OS X Downloading the Datasets and Example Code Using IPython Notebook Defining the code repository Understanding the datasets used in this book Chapter 4: Reviewing Basic Python Working with Numbers and Logic Performing variable assignments Doing arithmetic Comparing data using Boolean expressions Creating and Using Strings Interacting with Dates Creating and Using Functions Creating reusable functions Calling functions in a variety of ways Using Conditional and Loop Statements Making decisions using the if statement Choosing between multiple options using nested decisions Performing repetitive tasks using for Using the while statement Storing Data Using Sets, Lists and Tuples Performing operations on sets Working with lists Creating and using Tuples Defining Useful Iterators Indexing Data Using Dictionaries Part II: Getting Your Hands Dirty with Data Chapter 5: Working with Real Data Uploading, Streaming and Sampling Data Uploading small amounts of data into memory Streaming large amounts of data into memory Sampling data Accessing Data in Structured Flat File Form Reading from a text file Reading CSV delimited format Reading Excel and other Microsoft Office files Sending Data in Unstructured File Form Managing Data from Relational Databases Interacting with Data from NoSQL Databases Accessing Data from the Web Chapter 6: Conditioning Your Data Juggling between NumPy and pandas Knowing when to use NumPy Knowing when to use pandas Validating Your Data Figuring out what`s in your data Removing duplicates Creating a data map and data plan Manipulating Categorical Variables Creating categorical variables Renaming levels Com Printed Pages: 440. Buchnummer des Verkäufers 98431

Bibliografische Details

Titel: Python for Data Science for Dummies
Verlag: Wiley India Pvt. Ltd
Erscheinungsdatum: 2015
Einband: Softcover
Zustand: New
Auflage: First edition.

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John Paul Mueller
Verlag: Wiley John & Sons Jul 2015 (2015)
ISBN 10: 1118844181 ISBN 13: 9781118844182
Neu Taschenbuch Anzahl: 1
(Einbeck, Deutschland)

Buchbeschreibung Wiley John & Sons Jul 2015, 2015. Taschenbuch. Buchzustand: Neu. 229x236x31 mm. Neuware - Unleash the power of Python for your data analysis projects with For Dummies!Python is the preferred programming language for data scientists and combines the best features of Matlab, Mathematica, and R into libraries specific to data analysis and visualization. Python for Data Science For Dummies shows you how to take advantage of Python programming to acquire, organize, process, and analyze large amounts of information and use basic statistics concepts to identify trends and patterns. You'll get familiar with the Python development environment, manipulate data, design compelling visualizations, and solve scientific computing challenges as you work your way through this user-friendly guide. Covers the fundamentals of Python data analysis programming and statistics to help you build a solid foundation in data science concepts like probability, random distributions, hypothesis testing, and regression models Explains objects, functions, modules, and libraries and their role in data analysis Walks you through some of the most widely-used libraries, including NumPy, SciPy, BeautifulSoup, Pandas, and MatPlobLib Whether you're new to data analysis or just new to Python, Python for Data Science For Dummies is your practical guide to getting a grip on data overload and doing interesting things with the oodles of information you uncover. 432 pp. Englisch. Artikel-Nr. 9781118844182

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