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> Python Data Visualization Cookbook（Second Edition）最新章節(jié)目錄
目錄(108章)
倒序
- 封面
- 版權(quán)頁
- Credits
- About the Authors
- About the Reviewer
- www.PacktPub.com
- Support files eBooks discount offers and more
- Preface
- What this book covers
- What you need for this book
- Who this book is for
- Sections
- Conventions
- Reader feedback
- Customer support
- Chapter 1. Preparing Your Working Environment
- Introduction
- Installing matplotlib NumPy and SciPy
- Installing virtualenv and virtualenvwrapper
- Installing matplotlib on Mac OS X
- Installing matplotlib on Windows
- Installing Python Imaging Library (PIL) for image processing
- Installing a requests module
- Customizing matplotlib's parameters in code
- Customizing matplotlib's parameters per project
- Chapter 2. Knowing Your Data
- Introduction
- Importing data from CSV
- Importing data from Microsoft Excel files
- Importing data from fixed-width data files
- Importing data from tab-delimited files
- Importing data from a JSON resource
- Exporting data to JSON CSV and Excel
- Importing and manipulating data with Pandas
- Importing data from a database
- Cleaning up data from outliers
- Reading files in chunks
- Reading streaming data sources
- Importing image data into NumPy arrays
- Generating controlled random datasets
- Smoothing the noise in real-world data
- Chapter 3. Drawing Your First Plots and Customizing Them
- Introduction
- Defining plot types – bar line and stacked charts
- Drawing simple sine and cosine plots
- Defining axis lengths and limits
- Defining plot line styles properties and format strings
- Setting ticks labels and grids
- Adding legends and annotations
- Moving spines to the center
- Making histograms
- Making bar charts with error bars
- Making pie charts count
- Plotting with filled areas
- Making stacked plots
- Drawing scatter plots with colored markers
- Chapter 4. More Plots and Customizations
- Introduction
- Setting the transparency and size of axis labels
- Adding a shadow to the chart line
- Adding a data table to the figure
- Using subplots
- Customizing grids
- Creating contour plots
- Filling an under-plot area
- Drawing polar plots
- Visualizing the filesystem tree using a polar bar
- Customizing matplotlib with style
- Chapter 5. Making 3D Visualizations
- Introduction
- Creating 3D bars
- Creating 3D histograms
- Animating in matplotlib
- Animating with OpenGL
- Chapter 6. Plotting Charts with Images and Maps
- Introduction
- Processing images with PIL
- Plotting with images
- Displaying images with other plots in the figure
- Plotting data on a map using Basemap
- Plotting data on a map using the Google Map API
- Generating CAPTCHA images
- Chapter 7. Using the Right Plots to Understand Data
- Introduction
- Understanding logarithmic plots
- Understanding spectrograms
- Creating stem plot
- Drawing streamlines of vector flow
- Using colormaps
- Using scatter plots and histograms
- Plotting the cross correlation between two variables
- Importance of autocorrelation
- Chapter 8. More on matplotlib Gems
- Introduction
- Drawing barbs
- Making a box-and-whisker plot
- Making Gantt charts
- Making error bars
- Making use of text and font properties
- Rendering text with LaTeX
- Understanding the difference between pyplot and OO API
- Chapter 9. Visualizations on the Clouds with Plot.ly
- Introduction
- Creating line charts
- Creating bar charts
- Plotting a 3D trefoil knot
- Visualizing maps and bubbles
- Index 更新時(shí)間：2021-07-30 10:06:13
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