Line Graphs

For the purpose of displaying evolution or deviation in time-series, line graphs are usually one of the best tools for you. The data is continuous – unless you are using a Pareto graph where the data is discreet. Discreet data means that the set of data is definite, for example the number of employees in your company.

If data is missing for some periods or intervals, you must clearly highlight that. Intervals need to be equal in size.

 

The best practice principles are:

  1. Do not include more than four lines in your graph. This will make your graph difficult to read and understand, especially if you are using multiple colors for your graphs. If you must include all lines in your graph, then break the graph down in individual smaller graphs, one graph for each “focus” line. Ensure all other lines are in one, discreet color, and choose a more “dominant” color for the “focus” line. Repeat the procedure for the other lines. An example is shown further below.
  2. Make sure the height of the y-axis and your lines are harmony and match. If the highest point in your line is, say 43, then the y-axis should be proportionate and close to 43, for example 50, and not way above, say 400.
  3. The line labels should sit next to the corresponding line, and outside the graph area.
  4. Do your best to start the y-axis at zero value if all values are greater than zero.
  5. Opt for solid lines. Dotted lines attract the focus to themselves.

 

Below are some examples:

 

This is an example of how not to display a line graph.

 

Line Bars 1

 

 

There are more than four lines in this graph, and therefor too many colors. The line labels are not next to their corresponding lines, but to the right of the graph. This makes us shift our focus from the graph to the legend and back to the graph, maybe several times even. The grid lines are a distraction. The graph title is a bit too big.

A solution to that would be to break it down into five graphs:

 

Line Bars 2

 

You have the option of deleting the grey lines in each graph, unless a direct comparison between the sales regions is important to you.

Line graphs are ideal to show evolution over time as below.

Line Bars 3

 

Similarly, line graphs can show the evolution of several categories.

Line Bars 4

 

Now look at the example below:

Line Bars 5

Because the title says “Last year vs Budget”, I am inclined to think we would rather want to see the deviation of last year against the budget, that means we are probably more interested in looking into how last year performed against the budget, and not the nominal values of the two categories.

When you are looking at deviations, it is better to index.

Line Bars 6