Ticks

The customizations you've coded up to now are available in the script, in a more concise form.

In the video, Hugo has demonstrated how you could control the y-ticks by specifying two arguments:

plt.yticks([0,1,2], ["one","two","three"])

In this example, the ticks corresponding to the numbers 0, 1 and 2 will be replaced by one, two and three, respectively.

Let's do a similar thing for the x-axis of your world development chart, with the xticks() function. The tick values 1000, 10000 and 100000 should be replaced by 1k, 10k and 100k. To this end, two lists have already been created for you: tick_val and tick_lab.

This exercise is part of the course

Intermediate Python

View Course

Exercise instructions

Use tick_val and tick_lab as inputs to the xticks() function to make the the plot more readable.
As usual, display the plot with plt.show() after you've added the customizations.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Scatter plot
plt.scatter(gdp_cap, life_exp)

# Previous customizations
plt.xscale('log') 
plt.xlabel('GDP per Capita [in USD]')
plt.ylabel('Life Expectancy [in years]')
plt.title('World Development in 2007')

# Definition of tick_val and tick_lab
tick_val = [1000, 10000, 100000]
tick_lab = ['1k', '10k', '100k']

# Adapt the ticks on the x-axis


# After customizing, display the plot

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