When we create a bar chart, we want each bar to be meaningful and correspond to a category of data. In the drinks chart from the last exercise, we could see that sales were different for different drink items, but this wasn’t very helpful to us, since we didn’t know which bar corresponded to which drink.

In the previous lesson, we learned how to customize the tick marks on the x-axis in three steps:

1. Create an axes object

   ax = plt.subplot()

2. Set the x-tick positions using a list of numbers

   ax.set_xticks([0, 1, 2, 3, 4, 5, 6, 7, 8])

3. Set the x-tick labels using a list of strings

   ax.set_xticklabels(['Mercury', 'Venus', 'Earth', 'Mars', 'Jupiter', 'Saturn', 'Uranus', 'Neptune', 'Pluto'])

4. If your labels are particularly long, you can use the rotation keyword to rotate your labels by a specified number of degrees:

   ax.set_xticklabels(['Mercury', 'Venus', 'Earth', 'Mars', 'Jupiter', 'Saturn', 'Uranus', 'Neptune', 'Pluto'],
   rotation=30)

Note: We have to set the x-ticks before we set the x-labels because the default ticks won’t necessarily be one tick per bar, especially if we’re plotting a lot of bars. If we skip setting the x-ticks before the x-labels, we might end up with labels in the wrong place.

Remember from Lesson I that we can label the x-axis (plt.xlabel) and y-axis (plt.ylabel) as well. Now, our graph is much easier to understand:

Let’s add the appropriate labels for the chart you made in the last exercise for the coffee shop, MatplotSip.