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Histograms of Categorical and Continuous Data

Histograms of Categorical Data

The main categorical histogram chart types in Aabel are outlined below:

Frequency and relative frequency (%) of categorical or nominal data: The frequency is calculated by the number of unique occurrences of each data group within a variable (see the right-side image below).

Ogive Charts: This chart type is a plot of cumulative relative frequency of categorical data.

Pareto Charts: The Pareto Principle states that "not all of the causes of a particular phenomenon occur with the same frequency or with the same impact". The Pareto chart is designed to graphically display this principle. A Pareto chart is a histogram in which the categories are sorted by occurrence in decreasing order, to which is added a percent cumulative frequency curve.

A Pareto Chart

A Histogram of Categorical Data

Spine Charts: This chart type can be described as a univariate mosaic plot, or a histogram in which the height of all bars is the same, while their width is proportional to the number of observations of each level of a categorical variable (see the left hand-side image below). The main purpose of a spine plot is to compare the proportions of highlighted observations between the different categories to explore for patterns (see the image below).

Spine Chart: an Exploratory Plot

Histograms and Bihistograms of Continuous Data

These charts are used to display frequency (see the left hand-side image below), relative frequency (%), or cumulative histograms (see the right hand-side image below) of continuous data. You can create a single histogram to show the distribution of values of a single variable, or create a bihistogram for comparing the distribution of values of two variables.

A Histogram of Continuous Data

A Cumulative Histogram of Continuous Data

Binning, Data Brushing, Exploring

When using histograms, you can: