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Matplotlib plotting cookbook : learn how to create professional scientific plots using matplotlib, with more than 60 recipes that cover common use cases /

This book follows a cookbook style approach that puts orthogonal and non-redundant recipes in your hands. Rather than rehashing the user manual, the explanations expose the underlying logic behind Matplotlib. If you are an engineer or scientist who wants to create great visualizations with Python, r...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Devert, Alexandre
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham, UK : Packt Pub., 2014.
Colección:Quick answers to common problems.
Temas:
Acceso en línea:Texto completo
Texto completo

MARC

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245 1 0 |a Matplotlib plotting cookbook :  |b learn how to create professional scientific plots using matplotlib, with more than 60 recipes that cover common use cases /  |c Alexandre Devert. 
260 |a Birmingham, UK :  |b Packt Pub.,  |c 2014. 
300 |a 1 online resource (1 volume) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
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490 1 |a Quick answers to common problems 
588 0 |a Online resource; title from cover page (Safari, viewed Apr 11, 2014). 
500 |a Includes index. 
505 0 |a Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: First Steps; Introduction; Installing matplotlib; Plotting one curve; Using NumPy; Plotting multiple curves; Plotting curves from file data; Plotting points; Plotting bar charts; Plotting multiple bar charts; Plotting stacked bar charts; Plotting back-to-back bar charts; Plotting pie charts; Plotting histograms; Plotting boxplots; Plotting triangulations; Chapter 2: Customizing the Color and Styles; Introduction; Defining your own colors 
505 8 |a Using custom colors for scatter plotsUsing custom colors for bar charts; Using custom colors for pie charts; Using custom colors for boxplots; Using colormaps for scatter plots; Using colormaps for bar charts; Controlling line pattern and thickness; Controlling a fill pattern; Controlling a marker's style; Controlling a marker's size; Creating your own markers; Getting more control over markers; Creating your own color scheme; Chapter 3: Working with Annotations; Introduction; Adding a title; Using LaTeX-style notations; Adding a label to each axis; Adding text; Adding arrows; Adding a legend 
505 8 |a Adding a gridAdding lines; Adding shapes; Controlling ticks' spacing; Controlling ticks labeling; Chapter 4: Working with Figures; Introduction; Compositing multiple figures; Scaling both axes equally; Setting an axis range; Setting the aspect ratio; Inserting subfigures; Using a logarithmic scale; Using polar coordinates; Chapter 5: Working with a File Output; Introduction; Generating a PNG picture file; Handling transparency; Controlling the output resolution; Generating PDF or SVG documents; Handling multiple-page PDF documents; Chapter 6: Working with Maps; Introduction 
505 8 |a Visualizing the content of a 2D arrayAdding a colormap legend to a figure; Visualizing nonuniform 2D data; Visualizing a 2D scalar field; Visualizing contour lines; Visualizing a 2D vector field; Visualizing the streamlines of a 2D vector field; Chapter 7: Working with 3D Figures; Introduction; Creating 3D scatter plots; Creating 3D curve plots; Plotting a scalar field in 3D; Plotting a parametric 3D surface; Embedding 2D figures in a 3D figure; Creating a 3D bar plot; Chapter 8: User Interface; Introduction; Making a user-controllable plot; Integrating a plot to a Tkinter user interface 
505 8 |a Integrating a plot to wxWidgets user interfaceIntegrating a plot to GTK user interface; Integrating a plot in a Pyglet application; Index 
520 |a This book follows a cookbook style approach that puts orthogonal and non-redundant recipes in your hands. Rather than rehashing the user manual, the explanations expose the underlying logic behind Matplotlib. If you are an engineer or scientist who wants to create great visualizations with Python, rather than yet another specialized language, this is the book for you. While there are several very competent plotting packages, Matplotlib is ""just"" a Python module. Thus, if you know some Python already, you will feel at home from the first steps on. In case you are an application writer, you wo 
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830 0 |a Quick answers to common problems. 
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