在上面的代码中,我们已经通过labs(color = "Y Variable")设置了图例标题,并且每个y变量都通过aes(color = ...)被赋予了不同的标签。 细化图表样式: 最后,你可以根据需要调整图表的样式,包括标题、轴标签、网格线等: R p + ggtitle("Scatter Plot with Multiple Y Variables") + # 设置图表标题 xlab("X...
ggplot(data = iris, mapping = aes(x = Sepal.Length, y = Sepal.Width, shape = Species, color = Species)) + geom_point() 我们使用geom_point()绘制点图。 在美学中,我们定义x轴表示萼片长度,y轴表示萼片宽度; shape = Species和color = Species每种特定的花用不同的形状和不同的颜色。 散点图...
- Accepts X,Y and Z data as arrays, matrices or cells of arrays- Accepts grouping data as arrays or cellstr. Gramm works best with table-like data: separate variables/fields/columns for the variables of interest, with each variable having as many elements as observations. - Multiple ways ...
Finally, we can use our long data to draw a ggplot2 graph containing multiple lines as shown below: ggp2<-ggplot(data_long,# Create ggplot2 plotaes(x=x, y=value, color=variable))+geom_line()ggp2# Draw ggplot2 plot As shown in Figure 2, the previous R programming syntax created a...
Arrange multiple ggplots on the same page Place a box plot within a ggplot Create a scatter plot of y = “Sepal.Width” by x = “Sepal.Length” using the iris data set. R functionggscatter() [ggpubr] Create separately the box plot of x and y variables with transparent background. ...
ggcorrmat() correlation matrices for correlations between multiple variables ggpiestats() pie charts for categorical data ggbarstats() bar charts for categorical data ggcoefstats() dot-and-whisker plots for regression models and meta-analysis In addition to these basic plots, {ggstatsplot} also...
Consider Figure 3.1, one attempt to answer this question. It is a scatterplot of two continuous variables (engine displacement and highway mpg), with points coloured by a third variable (number of cylinders). From your experience in the previous chapter, you should have a pretty good feel fo...
Multiple panels figure using ggplot facet Facets divide a ggplot into subplots based on the values of one or more categorical variables. When you are creating multiple plots that share axes, you should consider using facet functions from ggplot2 ...
The alluvial plots implemented here can be used to visualize frequency distributions over time or frequency tables involving several categorical variables. The design is inspired by thealluvialpackage, but theggplot2framework induced several conspicuous differences: ...
Functions: coord_flip(), scale_x_reverse(), scale_y_reverse() Faceting: split a plot into a matrix of panels Facet with one variable Facet with two variables Facet scales Facet labels facet_wrap Functions: facet_grid(), facet_wrap(), label_both(), label_bquote(), label_parsed() Ext...