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matplotlib for Python Developers:Build remarkable publication quality plots the easy way 1

2009年

作者： Sandro Tosi

ISBN: (数字)9781847197917

ISBN: (纸本)9781847197900

Build remarkable publication-quality plots the easy way Create high quality 2D plots by using matplotlib productivelyIncremental introduction to matplotlib, from the ground up to advanced levelsEmbed matplotlib in GTK+, Qt, and wxWidgets applications as well as web sites to utilize them in Python applicationsDeploy matplotlib in web applications and expose it on the Web using popular web frameworks such as Pylons and DjangoGet to grips with hands-on code and complete realistic case study examples along with highly informative plot screenshots In Detail Providing appealing plots and graphs is an essential part of various fields such as scientific research, data analysis, and so on. matplotlib, the Python 2D plotting library, is used to produce publication-quality figures in a variety of hardcopy formats and interactive environments across platforms. This book explains creating various plots, histograms, power spectra, bar charts, error charts, scatter-plots and much more using the powerful matplotlib library to get impressive out-of-the-box *** book gives you a comprehensive tour of the key features of the matplotlib Python 2D plotting library, right from the simplest concepts to the most advanced topics. You will discover how easy it is to produce professional-quality plots when you have this book to *** book introduces the library in steps. First come the basics: introducing what the library is, its important prerequisites (and terminology), installing and configuring matplotlib, and going through simple plots such as lines, grids, axes, and charts. Then we start with some introductory examples, and move ahead by discussing the various programming styles that matplotlib allows, and several key ***, the book presents an important section on embedding applications. You will be introduced to three of the best known GUI libraries--GTK+, Qt, and wxWidgets--and presented with the steps to implement to include matplotlib in an application writte

关键词： developers python matplotlib

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matplotlib in Python 11

Matplotlib in Python

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11th International Conference on Electronics, Computer and Computation (ICECCO)

作者： Ari, Niyazi Ustazhanov, Makhamadsulton Nigerian Turkish Nile Univ Abuja Nigeria

ISBN: (纸本)9781479941063

Python and one of plotting module matplotlib was explained briefly. Existing softwares may be enough to solve and display the results of scientific problems. But matplotlib also stepping with its Pythonic programming style to this area of the software technology. The use of matplotlib is illustrated with specific practical applications. The applied illustrations code and results have been suggested.

关键词： matplotlib Python PyLab numpy

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matplotlib 2.x By Example 1

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2017年

作者： Allen Yu Claire Chung Aldrin Yim

ISBN: (数字)9781788292139

ISBN: (纸本)9781788295260

Unlock deeper insights into visualization in form of 2D and 3D graphs using matplotlib 2.x About This Book • Create and customize live graphs, by adding style, color, font to make appealing graphs. • A complete guide with insightful use cases and examples to perform data visualizations with matplotlib's extensive toolkits. • Create timestamp data visualizations on 2D and 3D graphs in form of plots, histogram, bar charts, scatterplots and more. Who This Book Is For This book is for anyone interested in data visualization, to get insights from big data with Python and matplotlib 2.x. With this book you will be able to extend your knowledge and learn how to use python code in order to visualize your data with matplotlib. Basic knowledge of Python is expected. What You Will Learn • Familiarize with the latest features in matplotlib 2.x • Create data visualizations on 2D and 3D charts in the form of bar charts, bubble charts, heat maps, histograms, scatter plots, stacked area charts, swarm plots and many more. • Make clear and appealing figures for scientific publications. • Create interactive charts and animation. • Extend the functionalities of matplotlib with third-party packages, such as Basemap, GeoPandas, Mplot3d, Pandas, Scikit-learn, and Seaborn. • Design intuitive infographics for effective storytelling. In Detail Big data analytics are driving innovations in scientific research, digital marketing, policy-making and much more. matplotlib offers simple but powerful plotting interface, versatile plot types and robust customization. matplotlib 2.x By Example illustrates the methods and applications of various plot types through real world examples. It begins by giving readers the basic know-how on how to create and customize plots by matplotlib. It further covers how to plot different types of economic data in the form of 2D and 3D graphs, which give insights from a deluge of data from public repositories, such as Quandl Finance. You will learn to visualize

关键词： ggplot data visualization matplotlib seaborn basemap cartopy mplot3d

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matplotlib for Python Developers 2

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丛书名： []

2018年

作者： Aldrin Yim Claire Chung Allen Yu

ISBN: (数字)9781788628136

ISBN: (纸本)9781788625173

Leverage the power of matplotlib to visualize and understand your data more effectively Key Features Perform effective data visualization with matplotlib and get actionable insights from your data Design attractive graphs, charts, and 2D plots, and deploy them to the web Get the most out of matplotlib in this practical guide with updated code and examples Book Description Python is a general-purpose programming language increasingly being used for data analysis and visualization. matplotlib is a popular data visualization package in Python used to design effective plots and graphs. This is a practical, hands-on resource to help you visualize data with Python using the matplotlib library. matplotlib for Python Developers, Second Edition shows you how to create attractive graphs, charts, and plots using matplotlib. You will also get a quick introduction to third-party packages, Seaborn, Pandas, Basemap, and Geopandas, and learn how to use them with matplotlib. After that, you'll embed and customize your plots in third-party tools such as GTK+3, Qt 5, and wxWidgets. You'll also be able to tweak the look and feel of your visualization with the help of practical examples provided in this book. Further on, you'll explore matplotlib 2.1.x on the web, from a cloud-based platform using third-party packages such as Django. Finally, you will integrate interactive, real-time visualization techniques into your current workflow with the help of practical real-world examples. By the end of this book, you'll be thoroughly comfortable with using the popular Python data visualization library matplotlib 2.1.x and leveraging its power to build attractive, insightful, and powerful visualizations. What you will learn Create 2D and 3D static plots such as bar charts, heat maps, and scatter plots Get acquainted with GTK+3, Qt5, and wxWidgets to understand the UI backend of matplotlib Develop advanced static plots with third-party packages such as Pandas, GeoPandas, and Seaborn Create inter

关键词： Python data visualization Python Data Visualization matplotlib graphs charts plot Python 3.6 3D plot 2D plots Python Data science GTK Qt4 Embedding matplotlib matplotlib web plotting

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matplotlib for Python Developers: Effective techniques for data visualization with Python 2

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2018年

作者： Aldrin Yim Claire Chung Allen Yu

ISBN: (数字)9781788628136

ISBN: (纸本)9781788625173

Leverage the power of matplotlib to visualize and understand your data more effectively About This Book • Perform effective data visualization with matplotlib and get actionable insights from your data • Design attractive graphs, charts, and 2D plots, and deploy them to the web • Get the most out of matplotlib in this practical guide with updated code and examples Who This Book Is For This book is essentially for anyone who wants to create intuitive data visualizations using the matplotlib library. If you’re a data scientist or analyst and wish to create attractive visualizations using Python, you’ll find this book useful. Some knowledge of Python programming is all you need to get started. What You Will Learn • Create 2D and 3D static plots such as bar charts, heat maps, and scatter plots • Get acquainted with GTK+3, Qt5, and wxWidgets to understand the UI backend of matplotlib • Develop advanced static plots with third-party packages such as Pandas, GeoPandas, and Seaborn • Create interactive plots with real-time updates • Develop web-based, matplotlib-powered graph visualizations with third-party packages such as Django • Write data visualization code that is readily expandable on the cloud platform In Detail Python is a general-purpose programming language increasingly being used for data analysis and visualization. matplotlib is a popular data visualization package in Python used to design effective plots and graphs. This is a practical, hands-on resource to help you visualize data with Python using the matplotlib library. matplotlib for Python Developers, Second Edition shows you how to create attractive graphs, charts, and plots using matplotlib. You will also get a quick introduction to third-party packages, Seaborn, Pandas, Basemap, and Geopandas, and learn how to use them with matplotlib. After that, you’ll embed and customize your plots in third-party tools such as GTK+3, Qt 5, and wxWidgets. You’ll also be able to tweak the look and feel of your

关键词： Python data visualization Python Data Visualization matplotlib graphs charts plot Python 3.6 3D plot 2D plots Python Data science GTK Qt4 Embedding matplotlib matplotlib web plotting

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Web-Based Visualization of Marine Environmental Data: Performance Analysis of a matplotlib Implementation

Web-Based Visualization of Marine Environmental Data: Perfor...

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17th International Conference on Collaboration Technologies and Systems (CTS)

作者： James, Joseph A. Moh, Teng-Sheng Edwards, Christopher A. San Jose State Univ Dept Comp Sci San Jose CA 95192 USA Univ Calif Santa Cruz Ocean Sci Dept Santa Cruz CA 95064 USA

ISBN: (纸本)9781509022991

Vast amounts of environmental data, and specifically, ocean data are collected every day. These data are multi-dimensional, with longitude, latitude and depth coordinates and time at which it is collected. Numerous ocean variables are tracked including at least temperature, salinity, currents, sea surface height and chlorophyll concentration. The many uses of these data include weather forecasting, scientific research, and various uses by industries such as petroleum and fishing. Due to the size of the data sets and the dimensionality of the data, it is challenging to present it in useful formats and to make visual representations available real-time in a web-based app. In this paper we implement a web-based visualization system for environmental data using matplotlib that generates heat maps on demand for data sets up to 538,656 points in 6.1 seconds. We also analyze qualitative factors of this system.

关键词： visualization environmental matplotlib ocean netcdf

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Mastering matplotlib 2.x: Effective Data Visualization techniques with Python

引用

2018年

作者： Benjamin Walter Keller

ISBN: (数字)9781789618174

ISBN: (纸本)9781789617696

Understand and build beautiful and advanced plots with matplotlib and Python Key Features • Practical guide with hands-on examples to design interactive plots • Advanced techniques to constructing complex plots • Explore 3D plotting and visualization using Jupyter Notebook Book Description In this book, you’ll get hands-on with customizing your data plots with the help of matplotlib. You’ll start with customizing plots, making a handful of special-purpose plots, and building 3D plots. You’ll explore non-trivial layouts, Pylab customization, and more about tile configuration. You’ll be able to add text, put lines in plots, and also handle polygons, shapes, and annotations. Non-Cartesian and vector plots are exciting to construct, and you’ll explore them further in this book. You’ll delve into niche plots and visualize ordinal and tabular data. In this book, you’ll be exploring 3D plotting, one of the best features when it comes to 3D data visualization, along with Jupyter Notebook, widgets, and creating movies for enhanced data representation. Geospatial plotting will also be explored. Finally, you’ll learn how to create interactive plots with the help of Jupyter. Learn expert techniques for effective data visualization using matplotlib 3 and Python with our latest offering -- matplotlib 3.0 Cookbook What you will learn • Deal with non-trivial and unusual plots • Understanding Basemap methods • Customize and represent data in 3D • Construct Non-Cartesian and vector plots • Design interactive plots using Jupyter Notebook • Make movies for enhanced data representation Who this book is for This book is aimed at individuals who want to explore data visualization techniques. A basic knowledge of matplotlib and Python is required.

关键词： data visualization matplotlib 2d plots 3d plots histogram Python 3.7 plotting package

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matplotlib和Matlab在大学物理实验数据分析中的对比应用

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大学物理实验 2024年第5期37卷 97-102页

作者：辛政阳刘俊杰路超牛相宏南京邮电大学理学院江苏南京210023

在物理实验领域,对实验数据的精致且严格处理构成了实验研究的基石。尤其在对数据处理的精确性和作图质量有着极高要求的复杂物理实验中,借助专业的数据处理软件以执行数据解析、图像展现以及曲线拟合等任务显得尤为关键。首先,以弗兰... 详细信息

在物理实验领域,对实验数据的精致且严格处理构成了实验研究的基石。尤其在对数据处理的精确性和作图质量有着极高要求的复杂物理实验中,借助专业的数据处理软件以执行数据解析、图像展现以及曲线拟合等任务显得尤为关键。首先,以弗兰克赫兹实验为案例,实现了运用matplotlib与Matlab两款软件对实验数据进行直观且高效的可视化处理,发现在本实验中,Matlab软件做出的图像更加精细且代码更简单;其次,以铁磁材料的基本磁化曲线及其磁滞回线为例,进一步揭示了这两款软件在图像拟合方面的卓越性能,发现Matlab的拟合能力更强,可供选择的拟合方式更多;但Matlab更适用于简单绘制,matplotlib适用于精细地控制。将matplotlib与Matlab融入大学物理实验教学,不仅能够激发学生的创新意识,而且有助于培育其科学研究素养,更为他们未来投身科研工作奠定坚实的基础。

关键词： matplotlib Matlab 大学物理实验数据可视化处理数据图像拟合

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matplotlib在计算结果可视化中的应用

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现代计算机 2007年第1期13卷 81-84页

作者：李保源南通大学理学院南通226007

以设计课件为例,说明了matplotlib在计算结果可视化中的应用,充分展示了matplotlib高质量的作图功能和极其灵活的适用性。这种能力源自matplotlib先进的模块化设计思想和设计所采用的Python语言。

关键词： matplotlib 可视化 WxPython Zope 课件

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基于Python+matplotlib的成绩统计设计与实现

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智能计算机与应用 2020年第8期10卷 275-276,280页

作者：陈路陈道喜陆卫忠顾敏明苏州科技大学电子与信息工程学院苏州215009 苏州技师学院信息工程系苏州215009 江苏省建筑智慧节能重点实验室苏州215009

基于Python设计的学生成绩统计与分析系统,提出了使用matplotlib、Pandas、Numpy等库实现了对学生成绩的计算与统计分析,在系统中构建了学科成绩散点图、学科成绩分布饼图、学生成绩分布雷达图,并给出部分算法,最后根据所绘图形分析学... 详细信息

基于Python设计的学生成绩统计与分析系统,提出了使用matplotlib、Pandas、Numpy等库实现了对学生成绩的计算与统计分析,在系统中构建了学科成绩散点图、学科成绩分布饼图、学生成绩分布雷达图,并给出部分算法,最后根据所绘图形分析学生的学习成绩情况,以提高教师批改试卷和成绩分析的效率。

关键词： Python matplotlib 散点图雷达图

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