Histograms are useful for seeing the distribution of data. It's even effective with continuous data. In a histogram, the data is divided into a limited number of buckets—10 is common—and the number of items in each bucket is counted. Histograms are especially useful for finding how much data are available for various percentiles. For instance, these charts can clearly show how much of your data was in the 90th percentile or lower.
We'll use the same dependencies in our project.clj
file as we did in the Creating scatter plots with Incanter recipe.
We'll use the following set of imports in our script or REPL:
(require '[incanter.core :as i] '[incanter.charts :as c] '[incanter.io :as iio])
For this recipe, we'll use the iris dataset that we used in the Creating scatter plots with Incanter recipe.
(def iris (incanter.datasets/get-dataset :iris))