Scale_size_manual geom_line
SCALE_SIZE_MANUAL GEOM_LINE >> READ ONLINE
geom_text_repel( aes(point.size = cyl), # data point size size = 5, # font size in the text labels point.padding = 0, # additional padding theme_void() + theme(strip.text = element_text(size = 16)) + facet_wrap(~ factor(cyl)) + scale_color_discrete(name = "Cylinders") + scale_size_manual(values scale_manual: Create your own discrete scale. scale_size_manual(, values). As with other scales you can use breaks to control the appearance # of the legend. p + scale_colour_manual(values = cols) p + scale_colour_manual( values = cols, breaks = c("4", "6", "8"), labels = c("four", "six" Using geom_line(), a time series (or line chart) can be drawn from a data.frame as well. The X axis breaks are generated by default. This can be done using the scale_aesthetic_manual() format of functions (like, scale_color_manual() if only the color of your lines change). Here we manually set Hex color values in the scale_fill_manual function. These hex values I provided I know to be the default R values for four groups. With this named color vector and the scale_*_manual functions we can now manually override the fill and color schemes in a flexible way. #' `scale_discrete_manual()` is a generic scale that can work with any aesthetic or set. #' geom_point(aes(colour = factor(cyl))). #' p + scale_colour_manual(values = c("red", "blue" #' p + scale_colour_manual(values = cols). #' #' # You can set color and fill aesthetics at the same time. geom_line( aes(y=temperature)) + geom_line( aes(y=price / coeff)) + # Divide by 10 to get the same range than the temperature. scale_y_continuous( #. Features of the first axis name = "First Axis" scale_size_manual() : to change the size of points. # Line plot with multiple groups # Change line types and colors by groups (sex) ggplot(df2, aes(x=time, y=bill, group=sex)) + geom_line(aes(linetype = sex, color = sex))+ geom_point(aes(color=sex))+ theme(legend.position="top"). Here you use scale_size_manual() to set the line width for each category in the RTTYP attribute. Similar to the colors set above, ggplot() will apply the line You can layer multiple ggplot objects by adding a new geom_ function to your plot. For the roads data, you used geom_path() and for points Categorical variables: manually select the colors (scale_color_manual). If you don't use a `scale` function you will need to change the data itself so that it has the right format. # here there is no legend automatically ggplot(nmmaps, aes(x=date, y=o3))+geom_line(color="grey")+geom_point Chapter 4. Line Graphs Line graphs are typically used for visualizing how one continuous variable, on the y-axis, changes in relation to another continuous variable, on the x-axis. Use ggplot() with geom_line(), and specify what variables you mapped to x and y (Figure 4-1)
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