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.

# 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

plt.xticks(tick_val,tick_lab)

# After customizing, display the plot

plt.show()