Python Data Visualization Cookbook 2nd edition 2015.pdf

【实例截图】

【核心代码】

Table of Contents
Preface v
Chapter 1: Preparing Your Working Environment 1
Introduction 1
Installing matplotlib, NumPy, and SciPy 2
Installing virtualenv and virtualenvwrapper 4
Installing matplotlib on Mac OS X 7
Installing matplotlib on Windows 9
Installing Python Imaging Library (PIL) for image processing 10
Installing a requests module 11
Customizing matplotlib's parameters in code 12
Customizing matplotlib's parameters per project 14
Chapter 2: Knowing Your Data 17
Introduction 17
Importing data from CSV 18
Importing data from Microsoft Excel files 20
Importing data from fixed-width data files 23
Importing data from tab-delimited files 25
Importing data from a JSON resource 27
Exporting data to JSON, CSV, and Excel 29
Importing and manipulating data with Pandas 34
Importing data from a database 35
Cleaning up data from outliers 40
Reading files in chunks 45
Reading streaming data sources 47
Importing image data into NumPy arrays 49
Generating controlled random datasets 55
Smoothing the noise in real-world data 62
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Table of Contents
Chapter 3: Drawing Your First Plots and Customizing Them 69
Introduction 70
Defining plot types – bar, line, and stacked charts 70
Drawing simple sine and cosine plots 76
Defining axis lengths and limits 79
Defining plot line styles, properties, and format strings 82
Setting ticks, labels, and grids 87
Adding legends and annotations 90
Moving spines to the center 93
Making histograms 95
Making bar charts with error bars 97
Making pie charts count 100
Plotting with filled areas 102
Making stacked plots 104
Drawing scatter plots with colored markers 107
Chapter 4: More Plots and Customizations 111
Introduction 111
Setting the transparency and size of axis labels 112
Adding a shadow to the chart line 114
Adding a data table to the figure 118
Using subplots 120
Customizing grids 123
Creating contour plots 128
Filling an under-plot area 131
Drawing polar plots 134
Visualizing the filesystem tree using a polar bar 136
Customizing matplotlib with style 140
Chapter 5: Making 3D Visualizations 143
Introduction 143
Creating 3D bars 143
Creating 3D histograms 147
Animating in matplotlib 150
Animating with OpenGL 154
Chapter 6: Plotting Charts with Images and Maps 159
Introduction 159
Processing images with PIL 160
Plotting with images 166
Displaying images with other plots in the figure 171
Plotting data on a map using Basemap 174
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Table of Contents
Plotting data on a map using the Google Map API 179
Generating CAPTCHA images 185
Chapter 7: Using the Right Plots to Understand Data 191
Introduction 191
Understanding logarithmic plots 192
Understanding spectrograms 195
Creating stem plot 200
Drawing streamlines of vector flow 204
Using colormaps 208
Using scatter plots and histograms 213
Plotting the cross correlation between two variables 221
Importance of autocorrelation 224
Chapter 8: More on matplotlib Gems 229
Introduction 229
Drawing barbs 229
Making a box-and-whisker plot 233
Making Gantt charts 236
Making error bars 241
Making use of text and font properties 244
Rendering text with LaTeX 251
Understanding the difference between pyplot and OO API 255
Chapter 9: Visualizations on the Clouds with Plot.ly 261
Introduction 261
Creating line charts 262
Creating bar charts 266
Plotting a 3D trefoil knot 269
Visualizing maps and bubbles 272
Index 275