gf_density()

The gf_density() function will overlay a density plot onto a density histogram (i.e., gf_dhistogram(), not gf_histogram()). The density plot is a smoothed out version of the distribution. They can be helpful when you want to get a better idea of the approximate shape of the distribution (e.g., normal, bimodal, skewed, uniform).

Example 1:

# A density plot chained onto a density histogram

gf_dhistogram(~Thumb, data = Fingers) %>%

      gf_density()

Example of output from running the code above:

Example 2:

# A density plot with color arguments, chained onto a faceted density histogram

gf_dhistogram(~Thumb, data = Fingers, fill = "grey", color = "black") %>%

      gf_facet_grid(Sex ~ .) %>%

      gf_density(color = "red", fill = "blue")

Example of output from running the code above:

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• gf_histogram()

  The gf_histogram() function will create a frequency histogram for a quantitative variable. This means it will show the number of cases observed in the data for each value of the variable. (See gf_dhistogram() for information on density histograms). ...

• gf_dhistogram()

  The gf_dhistogram() function is very similar to the gf_histogram() function, however, the difference is that gf_dhistogram() will create a density histogram for a quantitative variable. This means it will show the percentage of cases for each value ...

• density

  In a histogram, density is roughly the same as proportion.

• gf_facet_grid()

  The gf_facet_grid() function will create separate plots for each group of a categorical variable. It can be chained onto plots such as gf_histogram(), gf_jitter(), and gf_bar(). Example 1: # Density histogram of Thumb faceted by Sex gf_dhistogram( ~ ...

• gf_lm()

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