Scaling charts

In the previous recipes, while creating our first charts and enhancing them, we hardcoded the scaling of how those values are visually represented.

While this served us well for the values we were using, we often plot charts from very large databases.

Depending on the range of that data, our hardcoded values for the vertical y-dimension might not always be the best solution, and may make it hard to see the lines in our charts.

Getting ready

We will improve our code from the previous recipe, How to give the chart a legend. If you have not typed in all of the code from the previous recipes, just download the code for this chapter, and it will get you started (and then you can have a lot of fun creating GUIs, charts, and so on, using Python).

How to do it…

Modify the yValues1 line of code from the previous recipe to use 50 as the third value:

Matplotlib_labels_two_charts_not_scaled.py

    axis  = fig.add_subplot(111)        # 1 row, 1 column 
    xValues  = [1,2,3,4] 
    yValues0 =...