us_time_survey <-
structure(list(year = c(2009, 2010, 2011, 2012, 2013, 2014, 2015, 
2016, 2017, 2018, 2019), household_activities = c(1.8, 1.79, 
1.77, 1.74, 1.78, 1.77, 1.8400000000000001, 1.8200000000000001, 
1.8100000000000001, 1.78, 1.78), eating_and_drinking = c(1.22, 
1.25, 1.24, 1.25, 1.23, 1.1699999999999999, 1.1799999999999999, 
1.1699999999999999, 1.1799999999999999, 1.1899999999999999, 1.1799999999999999
), leisure_and_sports = c(5.25, 5.1799999999999997, 5.21, 5.3700000000000001, 
5.2599999999999998, 5.2999999999999998, 5.21, 5.1299999999999999, 
5.2400000000000002, 5.2699999999999996, 5.1900000000000004), 
    sleeping = c(8.6699999999999999, 8.6699999999999999, 8.7100000000000009, 
    8.7300000000000004, 8.7400000000000002, 8.8000000000000007, 
    8.8300000000000001, 8.7899999999999991, 8.8000000000000007, 
    8.8200000000000003, 8.8399999999999999), caring_children = c(1.3899999999999999, 
    1.3300000000000001, 1.3300000000000001, 1.3899999999999999, 
    1.3799999999999999, 1.3799999999999999, 1.3799999999999999, 
    1.4199999999999999, 1.4299999999999999, 1.3899999999999999, 
    1.3600000000000001), working_employed = c(5.0999999999999996, 
    5.1200000000000001, 5.2000000000000002, 5.21, 5.1500000000000004, 
    5.3300000000000001, 5.1699999999999999, 5.2199999999999998, 
    5.1699999999999999, 5.1100000000000003, 5.1600000000000001
    ), working_employed_days_worked = c(7.4800000000000004, 7.5, 
    7.6399999999999997, 7.6500000000000004, 7.5800000000000001, 
    7.75, 7.5999999999999996, 7.6299999999999999, 7.6900000000000004, 
    7.6200000000000001, 7.6200000000000001)), row.names = c(NA, 
-11L), class = c("tbl_df", "tbl", "data.frame"))