rmarkdown plot title outside plot window

Plotting with ggplot2: Customizing Plot Titles

Ggplot graphics are built step by step, allowing users to add new elements as needed. Well-structured data can save a significant amount of time when creating publication-quality plots with minimal changes required in the event of underlying data changes or changes in plot type from bar to scatterplots.

In this format, every dimension is represented by a column and every observation is represented by a row, making it easier to create complex plots. The ggplot2 package provides a programmatic interface for specifying what variables to plot, how they are displayed, and general visual settings.

For instance, let's consider a simple bar chart where we want to compare the number of items owned by individuals in different categories. We can use the `ggplot()` function to create this plot. In addition to plotting the data, we can also customize the title of our plot using the `labs()` function.

Here is an example of how you can do this:

```R

library(ggplot2)

# Not run, but can be used to load in data from previous lesson!

interviews_plotting %>%

pivot_wider(names_from = items_owned, values_from = items_owned_logical) %>%

pivot_wider(names_from = months_lack_food, values_from = months_lack_food_logical) %>%

mutate(number_items = rowSums(select(.)))

```

To customize the title of our plot, we can use the `labs()` function. For example:

```R

interviews_plotting %>%

pivot_wider(names_from = items_owned, values_from = items_owned_logical) %>%

pivot_wider(names_from = months_lack_food, values_from = months_lack_food_logical) %>%

mutate(number_items = rowSums(select(.))) %>%

ggplot(aes(x = bicycle:car)) +

geom_bar(stat = 'identity') +

labs(title = 'Number of Items Owned by Individuals in Different Categories')

```

In this example, we are using the `labs()` function to set the title of our plot to 'Number of Items Owned by Individuals in Different Categories'. We can also customize other aspects of our plot such as the x-axis label, y-axis label, and legend.

By following these steps, you can create a custom plot with a title that accurately reflects the data being displayed.

Rmarkdown plot title outside plot window