
Getting Started with Python Data Analysis
Description
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- 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
Who this book is forIf you are a Python developer who wants to get started with data analysis and you need a quick introductory guide to the python data analysis libraries, then this book is for you.
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Content
- Cover
- Preface
- Copyright
- Credits
- About the Authors
- About the Reviewers
- www.PacktPub.com
- Table of Contents
- Chapter 1: Introducing Data Analysis and Libraries
- Data analysis and processing
- An overview of the libraries in data analysis
- Python libraries in data analysis
- NumPy
- Pandas
- Matplotlib
- PyMongo
- The scikit-learn library
- Summary
- Chapter 2: NumPy Arrays and Vectorized Computation
- NumPy arrays
- Data types
- Array creation
- Indexing and slicing
- Fancy indexing
- Numerical operations on arrays
- Array functions
- Data processing using arrays
- Loading and saving data
- Saving an array
- Loading an array
- Linear algebra with NumPy
- NumPy random numbers
- Summary
- Chapter 3: Data Analysis with Pandas
- An overview of the Pandas package
- The Pandas data structure
- Series
- The DataFrame
- The essential basic functionality
- Reindexing and altering labels
- Head and tail
- Binary operations
- Functional statistics
- Function application
- Sorting
- Indexing and selecting data
- Computational tools
- Working with missing data
- Advanced uses of Pandas for data analysis
- Hierarchical indexing
- The Panel data
- Summary
- Chapter 4: Data Visualization
- The matplotlib API primer
- Line properties
- Figures and subplots
- Exploring plot types
- Scatter plots
- Bar plots
- Contour plots
- Histogram plots
- Legends and annotations
- Plotting functions with Pandas
- Additional Python data visualization tools
- Bokeh
- MayaVi
- Summary
- Chapter 5: Time series
- Time series primer
- Working with date and time objects
- Resampling time series
- Downsampling time series data
- Upsampling time series data
- Time zone handling
- Timedeltas
- Time series plotting
- Summary
- Chapter 6: Interacting With Databases
- Interacting with data in text format
- Reading data from text format
- Writing data to text format
- Interacting with data in binary format
- HDF5
- Interacting with data in MongoDB
- Interacting with data in Redis
- The simple value
- List
- Set
- Ordered set
- Summary
- Chapter 7: Data Analysis Application Examples
- Data munging
- Cleaning data
- Filtering
- Merging data
- Reshaping data
- Data aggregation
- Grouping data
- Summary
- Chapter 8: Machine Learning Models with scikit-learn
- An overview of machine learning models
- The scikit-learn modules for different models
- Data representation in scikit-learn
- Supervised learning - classification and regression
- Unsupervised learning - clustering and dimensionality reduction
- Measuring prediction performance
- Summary
- Index
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File format: PDF
Copy-Protection: Adobe-DRM (Digital Rights Management)
System requirements:
- Computer (Windows; MacOS X; Linux): Install the free reader Adobe Digital Editions prior to download (see eBook Help).
- Tablet/smartphone (Android; iOS): Install the free app Adobe Digital Editions or the app PocketBook before downloading (see eBook Help).
- E-reader: Bookeen, Kobo, Pocketbook, Sony, Tolino and many more (only limited: Kindle).
The file format PDF always displays a book page identically on any hardware. This makes PDF suitable for complex layouts such as those used in textbooks and reference books (images, tables, columns, footnotes). Unfortunately, on the small screens of e-readers or smartphones, PDFs are rather annoying, requiring too much scrolling.
This eBook uses Adobe-DRM, a „hard” copy protection. If the necessary requirements are not met, unfortunately you will not be able to open the eBook. You will therefore need to prepare your reading hardware before downloading.
Please note: We strongly recommend that you authorise using your personal Adobe ID after installation of any reading software.
For more information, see our eBook Help page.