We can clearly see the linear relationship between gdpPercap and CO2, which was not clear until now. Now the scatter plot made by ggplot2 looks much better. We can make the variable on y-axis to be on log scale using scale_y_log10(). In this plot the variable on y-axis also needs to be on log scale. We can see that the variable on y-axis squished near zero. Scatter plot with ggplot2: log scale Scatter Plot tips: Log scale on x-axis and y-axis However, the plot is dominated by the outliers from variable on y-axis. On x-axis the data points are clearly spread out. Title="CO2 emission per person vs GDP per capita") + In ggplot2, we can easily make x-axis to be on log scale using scale_x_log10() function as an additional layer. Let us first make the variable on x-axis to log scale. This is often one of the best tips to make plot better and understand the relationship between two variables. One of the ways to make the plot better is to make the plot with log scale. Notice that the scales of the two variables are very different and there are more data points squished towards left because of few outlier data points. Scatter plot with ggplot2: labels and title Scatter Plot tip 2: Log scale on x-axis Now the scatter plot looks definitely better than our first attempt. Title="CO2 emission per person vs GDP per capita")+ Labs(x="GDP per capita", y= "CO2 Emission per person (in tonnes)", To make the labels and the tick mark labels more legible we use theme_bw() with base_size=16. And in addition, let us add a title that briefly describes the scatter plot. Scatter plot with ggplot2 in R Scatter Plot tip 1: Add legible labels and title Another thing to notice that is x-axis and y-axis labels and ticks seem bit tiny when compared to the rest of the scatter plot. However, that trend seems to be dominated by the outlier data points. A couple of things strike at first when look at the scatter plot.įirst is that we do see linear trend between the variables. Now we have made our first scatter plot with gdpPercap on x-axis and CO2 emission on y-axis. The geom_() function for scatter plot is geom_point() as we visualize the data points as points in a scatter plot. x-axis and y-axis variables.Īfter we specify the variables for scatter plot, we add a geom_() layer for scatter plot. The basic aesthetics of scatter plot is specifying the variables to be plotted as scatter plot, i.e. We will feed the data frame to ggplot2 using pipe operator and specify aesthetics of the scatter plot using aes(). Here are a few other ways to highlight data points with ggplot2.The way to make scatterplot with ggplot2 is simple. For example, we can add circles or ellipses around data points in ggplot2 using ggforce. A drawback of the convex hull is that when you multiple groups with outliers, the shapes of convex hulls can be bit confusing and not that useful.Īlso, check out other ways to highlight or add annotation in ggplot. It is often very useful to highlights the structure in a data inferred by PCA. Highlighting Groups in a ggplot with Convex Hull in RĪdding convex hull as a layer to plot is a great way to highlight multiple groups in a dataset. Ggsave("highlighting_groups_in_ggplot_with_Convex_hull.png") Now, when we add convex hull as extra layer, we get scatter plot with data points colored by grouping variable. Ggplot(aes(x=flipper_length_mm,y=bill_length_mm, color=species))+ Let us make a scatter plot coloring the points by a variable. This is because we did not add color to the original scatter plot we made first. Notice that the data points in the scatter plot are not colored by group. We also add color by filling and coloring the convex hulls.Īnnotating ggplot with Convex Hull Highlighting Groups with Convex Hull and Colors with ggplot2 In ggplot2, we can make convex hull using geom_polygon() geom with the data for convex hulls. # … with 18 more rows, and 2 more variables: sex, year Ĭonvex Hull Plot with ggplot2 using geom_polygon() # species island bill_length_mm bill_depth_mm flipper_length_mm body_mass_g Note that this is just the subset of the original dataset that covers the outline of each group. Our dataset to make convex hulls look like this. Slice(chull(flipper_length_mm, bill_length_mm))
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |