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  • Book Overview & Buying Mastering Python Data Visualization
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Mastering Python Data Visualization

Mastering Python Data Visualization

By : Kirthi Raman
4.5 (4)
Buy this Book
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Mastering Python Data Visualization

Mastering Python Data Visualization

4.5 (4)
By: Kirthi Raman
Buy this Book

Overview of this book

Python has a handful of open source libraries for numerical computations involving optimization, linear algebra, integration, interpolation, and other special functions using array objects, machine learning, data mining, and plotting. Pandas have a productive environment for data analysis. These libraries have a specific purpose and play an important role in the research into diverse domains including economics, finance, biological sciences, social science, health care, and many more. The variety of tools and approaches available within Python community is stunning, and can bolster and enhance visual story experiences. This book offers practical guidance to help you on the journey to effective data visualization. Commencing with a chapter on the data framework, which explains the transformation of data into information and eventually knowledge, this book subsequently covers the complete visualization process using the most popular Python libraries with working examples. You will learn the usage of Numpy, Scipy, IPython, MatPlotLib, Pandas, Patsy, and Scikit-Learn with a focus on generating results that can be visualized in many different ways. Further chapters are aimed at not only showing advanced techniques such as interactive plotting; numerical, graphical linear, and non-linear regression; clustering and classification, but also in helping you understand the aesthetics and best practices of data visualization. The book concludes with interesting examples such as social networks, directed graph examples in real-life, data structures appropriate for these problems, and network analysis. By the end of this book, you will be able to effectively solve a broad set of data analysis problems.
Table of Contents (11 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
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1
1. A Conceptual Framework for Data Visualization
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1. A Conceptual Framework for Data Visualization
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Data, information, knowledge, and insight
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The transformation of data
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Data visualization history
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How does visualization help decision-making?
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Visualization plots
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Summary
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2. Data Analysis and Visualization
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2. Data Analysis and Visualization
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Why does visualization require planning?
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The Ebola example
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A sports example
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Creating interesting stories with data
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Perception and presentation methods
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Some best practices for visualization
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Visualization tools in Python
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Interactive visualization
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Summary
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3. Getting Started with the Python IDE
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3. Getting Started with the Python IDE
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The IDE tools in Python
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Visualization plots with Anaconda
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Interactive visualization packages
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Summary
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4. Numerical Computing and Interactive Plotting
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4. Numerical Computing and Interactive Plotting
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NumPy, SciPy, and MKL functions
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Scalar selection
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Slicing
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Array indexing
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Other data structures
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Visualization using matplotlib
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The visualization example in sports
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Summary
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5. Financial and Statistical Models
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5. Financial and Statistical Models
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The deterministic model
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The stochastic model
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The threshold model
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An overview of statistical and machine learning
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Creating animated and interactive plots
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Summary
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6. Statistical and Machine Learning
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6. Statistical and Machine Learning
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Classification methods
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Understanding linear regression
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Linear regression
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Decision tree
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The Bayes theorem
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The Naïve Bayes classifier
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The Naïve Bayes classifier using TextBlob
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Viewing positive sentiments using word clouds
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k-nearest neighbors
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Logistic regression
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Support vector machines
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Principal component analysis
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k-means clustering
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Summary
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7. Bioinformatics, Genetics, and Network Models
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7. Bioinformatics, Genetics, and Network Models
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Directed graphs and multigraphs
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The clustering coefficient of graphs
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Analysis of social networks
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The planar graph test
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The directed acyclic graph test
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Maximum flow and minimum cut
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A genetic programming example
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Stochastic block models
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Summary
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8. Advanced Visualization
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8. Advanced Visualization
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Computer simulation
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Summary
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A. Go Forth and Explore Visualization
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A. Go Forth and Explore Visualization
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An overview of conda
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Packages installed with Anaconda
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Packages websites
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About matplotlib
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Index
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Index

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