Modifications to a table

There are various ways that a table can be modified to make the information clearer or to highlight particular aspects of the data.

Reordering categories
When there is a natural ordering of the row categories, the table should arrange the rows in this order. For example, annual data about rainfall, death rates, etc. must be ordered by year; data about educational achievement should be ordered by the achievement level (e.g. primary, secondary, tertiary). If there is no natural ordering, then it often helps to arrange the categories by the value, with the highest value first and the lowest last.

Alphabetic ordering of the categories is rarely best.


Combining categories
The information in the table may be clearer if the number of categories is reduced by combining some together. For example, published tables often categorise hospital operations into 50-100 different categories. A coarser categorisation (e.g. orthopaedic, cancer, ...) gives a more easily understood overview.

In tables of partitions, the value for a combined category is the sum of those for the categories that are being merged. The percentages are also added.


In tables that are not partitions, it is usually much harder to find the value corresponding to combined categories.
Looking at subsets of categories
It may be useful to 'hide' some categories in the table, and look only at a subset. For example, we may want to focus attention on a particular group of individuals or regions.

In tables of partitions, the values for the categories are unchanged, but the percentages should divide them by the total for the displayed categories, so they still add to 100%.

Tables that are not partitions must not be accompanied by percentages or totals, so further modification is required.

These techniques will be clearer in an example.

Road crashes by road feature

The table below shows the number of road crashes causing injury or death in New Zealand in 2005, categorised by the type of 'road feature' at the crash site.

The 'road features' were grouped into Intersections and Non-intersections in the report and are shown in different colours in the table. However the ordering of categories within the groups in the report was not particularly meaningful. Click the two checkboxes Sort by frequency to reorder the features by their frequency of accidents within each group.

Click the checkboxes Combine categories to combine the different types of intersections and non-intersections into a frequency table with two rows. This table highlights the differences between intersections and non-intersections.

Finally, expand the categories for Intersections and click Hide categories for the Non-intersections. This shows the distribution of road features for the accidents that occured at intersections. Note that hiding the non-intersection categories restricts attention to the accidents that occurred at intersections. The total therefore changes to the number of accidents at intersections and the percentages become percentages out of this new total.

Life expectancy in East Asian countries in 2005

The table of life expectancies is not a partition. However sorting the countries by life expectancy makes it far easier to understand.

Alphabetic order   Sorted by value
Country Life expectancy (years)
Brunei Darussalam
Cambodia
China
Hong Kong (China)
Indonesia
Japan
Laos
Macao (China)
Malaysia
Myanmar
North Korea
Philippines
Singapore
South Korea
Thailand
Timor-Leste
Vietnam
76.3
56.8
72.0
81.5
68.6
81.9
61.9
80.0
73.0
59.9
66.7
70.3
78.8
77.0
68.6
58.3
73.0
 
Country Life expectancy (years)
Japan
Hong Kong (China)
Macao (China)
Singapore
South Korea
Brunei Darussalam
Malaysia
Vietnam
China
Philippines
Indonesia
Thailand
North Korea
Laos
Myanmar
Timor-Leste
Cambodia
81.9
81.5
80.0
78.8
77.0
76.3
73.0
73.0
72.0
70.3
68.6
68.6
66.7
61.9
59.9
58.3
56.8

The table is not a partition since the sum of two life expectancies is meaningless. It is therefore non-trivial to combine countries. For example, the combined life expectancy for mainland China, Hong Kong and Macao would need to take into account the different populations in these three places. (We will discuss the combination of such values in a later chapter.)