To add a regression line on a scatter plot, the functiongeom_smooth()is used in combination with the argumentmethod = lm.lmstands for linear model. p <- ggplot(cars, aes(speed, dist)) + geom_point()# Add regression linep + geom_smooth(method = lm)# loess method: local regression ...
# Add arrowp+annotate("segment",x =2,xend =4,y =15,yend =25,colour ="pink",size=3,alpha=0.6,arrow=arrow()) Add ablines withgeom_hline()andgeom_vline() An abline is a segment that goes from one chart extremity to the other.ggplot2offers thegeom_hline()andgeom_vline()functio...
Not that new, but I do love a good scatterplot, so I decided to try drawing some lines. I use the temperature and wind variables in the air quality data set (NA values removed). We will need Hadley Wickham’s ggplot2 and Bendix Carstensen’s, Lyle Gurrin’s and Claus Ekstrom’s Met...
After looking at the long term growth of the stock price, it occurred to me that visualizing the stock price data would be a great example ofhow to create a line chart in Rusingggplot2. So in this blog post, I’ll show you how to make a line chart withggplot2, step by step. Let...
In this post, we will learn how to draw a line connecting the mean (or median) values in a boxplot in R using ggplot2. Connecting mean or median values in each group i.e. each box in boxplot can help easily see the pattern across different groups. The ba
How to Make a Histogram with ggplot2 Now we can create the histogram. Regardless of the type of graph we are creating in ggplot2, we always start with theggplot()function, which creates a canvas to add plot elements to. It takes two parameters. ...
2D Plot Our journey of a 3D plot just begins with a normal 2D ggplot2 plot. We’ll build a density plot using geom_raster between waiting, eruptions to see how how the data is. faithful_dd = ggplot(faithfuld, aes(waiting, eruptions)) + geom_raster(aes(fill = density)) + ggtitle(...
Now that we have our dataset let’s use ggplot2 to visualize the normal probability plot. We’ll employ the stat_qq_point() function to add points to the plot and stat_qq_line() to include a reference line for the expected normal distribution. # Plotting the data without lines and labe...
Reveal data along a given dimension This transition allows you to let data gradually appear, based on a given time dimension. Static plot p <- ggplot( airquality, aes(Day, Temp, group = Month, color = factor(Month)) ) + geom_line() + scale_color_viridis_d() + labs(x ="Day of ...
Annotate ggplot with text labels using built-in functions and create non-overlapping labels with the ggrepel package.