Question
Answer and Explanation
To import a graph into R Markdown and modify its size, you'll typically embed R code chunks directly into your document. The size of the plot is often controlled using options within these code chunks. Here’s how you can achieve this:
1. Basic Graph Creation: First, you need to generate a plot using R. Let's take a basic scatter plot as an example.
- Example R code:
\`\`\`{r create_plot}
plot(1:10, 10:1, main="Sample Plot")
\`\`\`
This simple code chunk creates and displays a plot directly within your R markdown document.
2. Modifying Graph Size with chunk options:
You can alter the size of the plot by specifying chunk options. Use the fig.width
and fig.height
chunk options for this purpose. These parameters define the width and the height of the plot respectively.
Example code with modified size:
\`\`\`{r modified_plot, fig.width=6, fig.height=4}
plot(1:10, 10:1, main="Sized Plot")
\`\`\`
In this example, fig.width=6
will set the plot to have a width of 6 inches and fig.height=4
will set a height of 4 inches. Make adjustments as needed depending on how large or small you need it.
3. Different graph formats:
- Note that this method should work with ggplot2 plots, and other plot functions and methods also.
Example with a ggplot2
graph :
\`\`\`{r ggplot_example, fig.width=7, fig.height=5}
library(ggplot2)
data <- data.frame(x = 1:5, y = c(3,6,4,8,5))
ggplot(data, aes(x = x, y= y)) + geom_point() + ggtitle("Example of ggplot plot")
\`\`\`
Here is another simple plot as example:
\`\`\`{r, fig.width=5, fig.height=5 }
hist(rnorm(100))
\`\`\`
4. Output formats and limitations:
The visual size on the screen can vary slightly from what the values will actually indicate based on device or resolution, but by changing these arguments, it allows for good consistent control on plot sizes in the resulting HTML or other format rendered.
By adjusting the fig.width
and fig.height
parameters, you can ensure the graphs in your R Markdown documents are displayed at appropriate sizes, whether small and inlined or big standalone plots.