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This article mainly talks about "R language data visualization tidyr and ggplot2 multi-variable hierarchical display of what is the implementation method", interested friends may wish to have a look. The method introduced in this paper is simple, fast and practical. Next let the editor to take you to learn "R language data visualization tidyr and ggplot2 multi-variable hierarchical display of what is the implementation of it?"

In the common drawing of R language, the subgraph of different variables can be realized on a graph by using the par () parameter. If we want to implement it in ggplot2, we need to sort out our raw data, which is usually very troublesome, and we need to use our tidyr to help us draw.

It may not be easy to understand the above paragraph, let's give an example of chestnut.

Density distribution of each variable y1% ggplot (aes (x = value)) + geom_histogram (fill = factor (var), y =.. density..), alpha = 0.3, colour = 'black') + stat_density (geom =' line', position = 'identity', size = 1.5, aes (colour = factor (var) + facet_wrap (~ var) Ncol = 2) + labs (y = 'histogram and density curve', x = 'value', title = 'title', fill = 'variable') + theme (plot.title = element_text (hjust = 0.5)) + guides (color = FALSE)

Here are basically the previous blogs: r language learning ggplot2 drawing statistical graphics package is mentioned in a comprehensive detailed explanation.

The only one is guides (color = FALSE), which represents the legend of the hidden line color, because the color of the line is specified with color =. Similarly, if you want to hide a legend with histogram colors, you can use guides (fill = FALSE).

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