age nr.employed          job  marital           education housing default emp.var.rate cons.price.idx cons.conf.idx
1   30      5099.1  blue-collar  married            basic.9y     yes      no         -1.8         92.893         -46.2
2   39      5191.0     services   single         high.school      no      no          1.1         93.994         -36.4
3   25      5228.1     services  married         high.school     yes      no          1.4         94.465         -41.8
4   38      5228.1     services  married            basic.9y unknown      no          1.4         94.465         -41.8
5   47      5195.8       admin.  married   university.degree     yes      no         -0.1         93.200         -42.0
6   32      4963.6     services   single   university.degree      no      no         -1.1         94.199         -37.5
7   32      4963.6       admin.   single   university.degree     yes      no         -1.1         94.199         -37.5
8   41      5195.8 entrepreneur  married   university.degree     yes unknown         -0.1         93.200         -42.0
9   31      5195.8     services divorced professional.course      no      no         -0.1         93.200         -42.0
10  35      5191.0  blue-collar  married            basic.9y      no unknown          1.1         93.994         -36.4

 

Order the data frame survey first on age and within each age on nr.employed. Store the result in a data frame called survey_ordered.