Matplotlib数据可视化章节教程

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资源摘要信息:"带有matplotlib的章节数据可视化" 本章节主要介绍了如何使用Python的matplotlib库进行数据可视化。matplotlib是Python的一个库,主要用于绘制2D图表,功能强大,操作简单,是数据分析和可视化的利器。 首先,我们需要了解matplotlib的基本概念。matplotlib中的数据可视化,主要是通过绘制图表来进行的。图表可以分为很多种类,如折线图、柱状图、饼图、散点图等,每一种图表都有其特定的用途。在matplotlib中,我们可以很方便地绘制出这些图表。 其次,我们需要掌握matplotlib的基本操作。在matplotlib中,主要的操作对象是figure和axes。figure是整个图表的容器,而axes则是图表中的一个子区域,可以包含一个或多个图表。在matplotlib中,我们可以通过操作figure和axes来绘制出我们需要的图表。 接着,我们需要学习如何在matplotlib中绘制各种图表。例如,我们可以使用matplotlib的plot函数来绘制折线图,使用bar函数来绘制柱状图,使用pie函数来绘制饼图,使用scatter函数来绘制散点图等。 最后,我们需要了解matplotlib的一些高级功能。例如,matplotlib支持自定义图表的样式,包括颜色、字体、边框等;matplotlib还支持交互式操作,例如放大、缩小、拖动等。 此外,本章节还提到了HTML标签。HTML标签是构成网页的基本元素,通过HTML标签,我们可以构建出一个完整的网页。在数据可视化中,我们可以将matplotlib生成的图表嵌入到网页中,从而实现更加丰富的数据展示效果。 总的来说,带有matplotlib的章节数据可视化,主要讲述了如何使用matplotlib库进行数据可视化,包括matplotlib的基本概念、基本操作、绘制各种图表以及一些高级功能。同时,本章节也简单介绍了HTML标签在数据可视化中的应用。通过本章节的学习,我们可以掌握如何使用matplotlib进行数据可视化,从而更好地分析和展示数据。
2017-08-25 上传
--------------------------- Qt Data Visualization 5.7.0 --------------------------- Qt Data Visualization module provides multiple graph types to visualize data in 3D space both with C++ and Qt Quick 2. System Requirements =================== - Qt 5.2.1 or newer - OpenGL 2.1 or newer (recommended) or OpenGL ES2 (reduced feature set) - Manipulating Qt Data Visualization graphs with QML Designer requires Qt Creator 3.3 or newer Building ======== Configure the project with qmake: qmake After running qmake, build the project with make: (Linux) make (Windows with MinGw) mingw32-make (Windows with Visual Studio) nmake (OS X) make The above generates the default makefiles for your configuration, which is typically the release build if you are using precompiled binary Qt distribution. To build both debug and release, or one specifically, use one of the following qmake lines instead. For debug builds: qmake CONFIG+=debug make or qmake CONFIG+=debug_and_release make debug For release builds: qmake CONFIG+=release make or qmake CONFIG+=debug_and_release make release For both builds (Windows/OS X only): qmake CONFIG+="debug_and_release build_all" make After building, install the module to your Qt directory: make install If you want to uninstall the module: make uninstall Building as a statically linked library ======================================= The same as above applies, you will just have to add static to the CONFIG: qmake CONFIG+=static Documentation ============= The documentation can be generated with: make docs The documentation is generated into the doc folder under the build folder. Both Qt Assistant (qtdatavisualization.qch) and in HTML format (qtdatavisualization subfolder) documentation is generated. Please refer to the generated documentation for more information: doc/qtdatavisualization/qtdatavisualization-index.html Known Issues ============ - Some platforms like Android and WinRT cannot handle multiple native windows properly, so only the Qt Quick 2 versions of graphs are available in practice for those platforms. - Shadows are not supported with OpenGL ES2 (including Angle builds in Windows). - Anti-aliasing doesn't work with OpenGL ES2 (including Angle builds in Windows). - QCustom3DVolume items are not supported with OpenGL ES2 (including Angle builds in Windows). - Surfaces with non-straight rows and columns do not always render properly. - Q3DLight class (and Light3D QML item) are currently not usable for anything. - Changing most of Q3DScene properties affecting subviewports currently has no effect. - Widget based examples layout incorrectly in iOS. - Reparenting a graph to an item in another QQuickWindow is not supported. - Android builds of QML applications importing QtDataVisualization also require "QT += datavisualization" in the pro file. This is because Qt Data Visualization QML plugin has a dependency to Qt Data Visualization C++ library, which Qt Creator doesn't automatically add to the deployment package. - Only OpenGL ES2 emulation is available for software renderer (that is, when using QCoreApplication::setAttribute(Qt::AA_UseSoftwareOpenGL))