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11#
發(fā)表于 2025-3-23 10:46:33 | 只看該作者
12#
發(fā)表于 2025-3-23 14:28:38 | 只看該作者
Data Analysiswith data handling while you’re learning visualisation), but in real life, datasets hardly ever come in exactly the right structure. To use ggplot2 in practice, you’ll need to learn some data wrangling skills. Indeed, in my experience, visualisation is often the easiest part of the data analysis pro
13#
發(fā)表于 2025-3-23 21:00:38 | 只看該作者
Programming with ggplot2ons, you need to be able to easily change many plots at once. The main inhibitor of flexibility is code duplication. If you have the same plotting statement repeated over and over again, you’ll have to make the same change in many different places. Often just the thought of making all those changes
14#
發(fā)表于 2025-3-24 00:23:48 | 只看該作者
https://doi.org/10.1007/978-3-662-36262-4rammar. This grammar, based on the Grammar of Graphics (Wilkinson,?.), is made up of a set of independent components that can be composed in many different ways. This makes ggplot2 very powerful because you are not limited to a set of pre-specified graphics, but you can create new graphics that are
15#
發(fā)表于 2025-3-24 03:03:39 | 只看該作者
Infektionen durch den Bacillus pyo-cyaneus,ome useful “recipes” to make the most important plots. . allows you to make complex plots with just a few lines of code because it’s based on a rich underlying theory, the grammar of graphics. Here we’ll skip the theory and focus on the practice, and in later chapters you’ll learn how to use the ful
16#
發(fā)表于 2025-3-24 09:43:49 | 只看該作者
Gesetze, Auslegungen und Entscheidungen,pter, and in this chapter you’ll get a more comprehensive task-based introduction. The goal here is not to exhaustively explore every option of every geom, but instead to show the most important tools for a given task. For more information about individual geoms, along with many more examples illust
17#
發(fā)表于 2025-3-24 10:49:53 | 只看該作者
18#
發(fā)表于 2025-3-24 16:35:01 | 只看該作者
https://doi.org/10.1007/978-3-642-58842-6 The theme system does not affect how the data is rendered by geoms, or how it is transformed by scales. Themes don’t change the perceptual properties of the plot, but they do help you make the plot aesthetically pleasing or match an existing style guide. Themes give you control over things like fon
19#
發(fā)表于 2025-3-24 20:40:40 | 只看該作者
Taschenbuch für Chemiker und Physikerwith data handling while you’re learning visualisation), but in real life, datasets hardly ever come in exactly the right structure. To use ggplot2 in practice, you’ll need to learn some data wrangling skills. Indeed, in my experience, visualisation is often the easiest part of the data analysis pro
20#
發(fā)表于 2025-3-25 02:13:01 | 只看該作者
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