I 1 Question 3.1 Our objective is to visualize the association between the mean years of educational attainment by women and fertility rates. However, you have likely noticed that there are many NAs in the column associated with educational attainment. This raises three considerations: 1. We can't relate fertility rate to education when there aren't values for each in given record (row). 2. There are different numbers of NAs in the education column for different countries. The rela- tionship between fertility rate and education may differ between countries and it is therefore sensable to distill the data to just one observation per country. 3. The relationship between fertility rate and education may differ through time. Because we only want one observation per country, we should ensure that the years associated with these observations are similar. Process your data in a way that takes into consideration the above. You should try to maximize your sample size i.e. make n as close to the number of unique countries in the data as possible, with an end product that has 252 rows. ed_clean = ed_clean.head()