If you are using the ggplot2 package to visualize data and forget to use a plus sign in the code, you will encounter the error: cannot add ggproto plots together.
This tutorial will go through how to solve the error with code examples.
Let’s look at an example of a data frame that contains the number of ice creams sold over ten days together with the temperature on each day in celsius.
df <- data.frame(day=c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10), temperature=c(10, 18, 22, 19, 28, 15, 20, 17, 13, 30), ice_cream_sold=c(5, 10, 40, 38, 100, 40, 120, 10, 30, 150)) df
day temperature ice_cream_sold 1 1 10 5 2 2 18 10 3 3 22 40 4 4 19 38 5 5 28 100 6 6 15 40 7 7 20 120 8 8 17 10 9 9 13 30 10 10 30 150
Let’s try to plot temperature and ice_cream_sold as two line plots on the same figure using ggplot2.
library(ggplot2) ggplot(df, aes(x = day)) geom_line(aes(y = temperature, color = 'temperature')) + geom_line(aes(y = ice_cream_sold, color = 'ice_cream_sold'))
Let’s run the code to see what happens:
Error in `+.gg`: ! Cannot add ggproto objects together. Did you forget to add this object to a ggplot object?
The error occurs because we are missing a + sign at the end of the first line.
We can solve this error by ensuring the plus signs are in place to create a ggplot chain. We need a + between the first
ggplot() call and
geom_point. Let’s look at the revised code:
library(ggplot2) coeff <- 1 ggplot(df, aes(x = day)) + geom_line(aes(y = ice_cream_sold, color = 'ice_cream_sold')) + geom_line(aes(y = temperature, color = 'temperature'))
Let’s run the code to get the result:
We successfully plotted the two variables ice_cream_sold and temperature on the same figure.
Congratulations on reading to the end of this tutorial!
For further reading on R related errors, go to the articles:
- How to Solve R Error: $ operator is invalid for atomic vectors
- How to Solve R Error in apply: dim(X) must have a positive length
- How to Solve R Error in Function: unused arguments
- How to Solve R Error: Unexpected else
Go to the online courses page on R to learn more about coding in R for data science and machine learning.
Have fun and happy researching!