New Material

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A treemap displays hierarchical relationships through a set of rectangles, sized proportionately to each data point, clustered together into one large rectangle. The rectangular screen space is divided into regions, and then each region is divided again for each level in the hierarchy. Treemaps show part-to-whole relationships with each rectangle in the tree map representing a category from the dataset. The nested regions show hierarchical relationships and allow for quantitative comparisons of attribute values.  A second variable for each category can also be coded using colour.
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A pie chart is a divided circle, in which each slice of the pie represents a part of the whole. The categories that each slice represents are mutually exclusive and exhaustive. Data with negative values cannot be displayed as a pie chart.
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This type of visualisation depicts items stacked one on top (column) of the other or side-by-side (bar), differentiated by coloured bars or strips. A stacked graph is useful for looking at changes in, for example, expenditures added up over time, across several products or services. The graph integrates different data sets to create a richer picture of (the sum of) changes.
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A line graph is commonly used to display change over time as a series of data points connected by straight line segments on two axes. The line graph therefore helps to determine the relationship between two sets of values, with one data set always being dependent on the other set.
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Commonly used on maps, and x/y-axis plots, or no plot at all, bubble charts communicate the raw count, frequency, or proportion of some variable where the size of the bubble reflects the quantity. Color-coding bubbles can represent a further categorization of the variable being graphed. It is also possible to add another dimension by showing the movement of bubbles over time (referred to as a motion chart).
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A histogram is a graphical way of presenting a frequency distribution of quantitative data organised into a number equally spaced intervals or bins (e.g. 1-10, 11-20…). The interval range is selected to reduce the amount of information while still providing enough variability to picture the shape of the distribution.

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