How to use "mutate if " on selected columns

Hi, got a new problem :')

I've try to change my df to numeric, it's work (jeunesu to jeunesut, BUT, it delete my geo/time columns or replace it by N/A.
So how can i use mutate without the first columns ?

dput(Jeunesu)
structure(list(geo\time = c("UE (28 pays)", "Zone euro (19 pays)",
"Belgique", "Bulgarie", "Tchéquie", "Danemark", "Allemagne",
"Estonie", "Irlande", "Grèce", "Espagne", "France", "Croatie",
"Italie", "Chypre", "Lettonie", "Lituanie", "Luxembourg", "Hongrie",
"Malte", "Pays-Bas", "Autriche", "Pologne", "Portugal", "Roumanie",
"Slovénie", "Slovaquie", "Finlande", "Suède", "Royaume-Uni",
"Islande", "Norvège", "Suisse", "Monténégro", "Macédoine du Nord",
"Serbie", "Turquie"), 2000 = c(":", "14.800000000000001", "17.199999999999999",
":", ":", "6.0999999999999996", "10.300000000000001", "18.199999999999999",
":", "20.800000000000001", "15.4", "13.4", ":", "21.899999999999999",
"11.800000000000001", ":", "18.899999999999999", "8.0999999999999996",
"19.100000000000001", "26.899999999999999", "6", "9.5999999999999996",
":", "10.1", "20.899999999999999", ":", ":", "11.800000000000001",
"6.9000000000000004", "12.5", "4.4000000000000004", "24.199999999999999",
"7.4000000000000004", ":", ":", ":", ":"), ...3 = c(NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, "(b)", NA, NA, NA, NA, "(u)", NA, NA, NA, NA,
NA, NA, NA, NA), 2001 = c(":", "14.300000000000001", "16.5",
"32.799999999999997", ":", "6.7000000000000002", "10.199999999999999",
"17.899999999999999", ":", "20", "14.9", "12.9", ":", "20.800000000000001",
"9.9000000000000004", ":", "19.100000000000001", "8.1999999999999993",
"18.5", "19.399999999999999", "5.7000000000000002", "9.3000000000000007",
"20.699999999999999", "10.199999999999999", "19.600000000000001",
"10.1", ":", "10.5", "7.2999999999999998", "12.6", "3.6000000000000001",
"23.600000000000001", "6.5", ":", ":", ":", ":"), ...5 = c(NA,
NA, "(b)", NA, NA, NA, NA, NA, NA, "(b)", "(b)", NA, NA, NA,
NA, NA, NA, NA, "(b)", NA, NA, NA, "(b)", NA, NA, NA, NA, NA,
"(b)", NA, NA, NA, NA, NA, NA, NA, NA), 2002 = c("15.6", "14.300000000000001",
"16.399999999999999", "31", "16.5", "6.5999999999999996", "10.9",
"15", "14.4", "19.100000000000001", "15.199999999999999", "13.199999999999999",
"21.699999999999999", "19.800000000000001", "9.5", "17.600000000000001",
"15.199999999999999", "7.5", "18.300000000000001", "18.5", "6.0999999999999996",
"8", "21.699999999999999", "11.5", "23.5", "10.1", "27.199999999999999",
"10.199999999999999", "7.5999999999999996", "12.6", "5.4000000000000004",
"23.5", "7.2000000000000002", ":", ":", ":", ":"), ...7 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "(b)",
NA, NA, NA, NA, NA, NA, NA, "(b)", NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA), 2003 = c("15.5", "14.4", "18", "30.600000000000001",
"17.5", "6.7999999999999998", "12.6", "14.199999999999999", "12.6",
"20.399999999999999", "14.800000000000001", "12.800000000000001",
"20.300000000000001", "19.5", "11.1", "16.100000000000001", "13.6",
"6.9000000000000004", "17.199999999999999", "20.5", "6.7000000000000002",
"7.5", "20.800000000000001", "12.4", "22.399999999999999", "9",
"21.399999999999999", "10.6", "7.2000000000000002", "9.5999999999999996",
"5.5999999999999996", "10.6", "8.6999999999999993", ":", ":",
":", ":"), ...9 = c("(b)", "(b)", NA, "(b)", "(b)", "(b)", "(b)",
"(b)", NA, "(b)", "(b)", "(b)", "(b)", NA, "(b)", "(b)", NA,
"(b)", "(b)", NA, "(b)", NA, "(b)", NA, "(b)", "(b)", "(b)",
"(b)", "(b)", NA, "(bu)", "(b)", "(b)", NA, NA, NA, NA), 2004 = c("15.300000000000001",
"14.4", "16.300000000000001", "28.699999999999999", "17.699999999999999",
"6.4000000000000004", "12.9", "15.4", "12.800000000000001", "19.699999999999999",
"14.4", "13.1", "19.199999999999999", "19.600000000000001", "10.199999999999999",
"15.6", "12.9", "8.0999999999999996", "16.899999999999999", "15.4",
"6.5999999999999996", "10.300000000000001", "19.600000000000001",
"12", "21.199999999999999", "8.1999999999999993", "21.199999999999999",
"10.699999999999999", "7.9000000000000004", "8.9000000000000004",
"6", "9.6999999999999993", "7.5999999999999996", ":", ":", ":",
":"), ...11 = c(NA, NA, "(b)", NA, NA, NA, NA, NA, "(b)", "(b)",
NA, NA, NA, "(b)", NA, NA, "(b)", NA, NA, "(b)", NA, "(b)", "(b)",
"(b)", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), 2005 = c("15",
"14.4", "14", "26.800000000000001", "16.899999999999999", "5.9000000000000004",
"13.800000000000001", "13.5", "11.800000000000001", "18.5", "14",
"13.199999999999999", "17.899999999999999", "20", "17.899999999999999",
"14.1", "10.699999999999999", "6.7999999999999998", "17.100000000000001",
"15", "7.7000000000000002", "10.1", "18.399999999999999", "12.300000000000001",
"18.399999999999999", "9.6999999999999993", "20.199999999999999",
"9.5", "10.4", "8.9000000000000004", "5.0999999999999996", "9.0999999999999996",
"7.7999999999999998", ":", ":", ":", ":"), ...13 = c(NA, NA,
NA, NA, NA, NA, "(b)", NA, NA, NA, "(b)", NA, "(b)", NA, NA,
NA, NA, NA, NA, "(b)", "(b)", NA, NA, NA, NA, NA, NA, NA, "(b)",
NA, NA, NA, NA, NA, NA, NA, NA), 2006 = c("14", "13.5", "12.9",
"23.899999999999999", "13.699999999999999", "4.7000000000000002",
"12.699999999999999", "10.800000000000001", "11.1", "15.5", "12.9",
"13.199999999999999", "15.800000000000001", "19.199999999999999",
"11.9", "13.699999999999999", "10.300000000000001", "8", "16.5",
"13.6", "6.2000000000000002", "9.5999999999999996", "16.600000000000001",
"12", "16.5", "9.6999999999999993", "18.100000000000001", "9.4000000000000004",
"9.5999999999999996", "8.9000000000000004", "5", "6", "8", ":",
"44.799999999999997", ":", "40.399999999999999"), ...15 = c("(b)",
"(b)", "(b)", "(b)", "(b)", NA, NA, NA, "(b)", "(b)", "(b)",
NA, "(b)", "(b)", "(b)", "(b)", "(b)", "(b)", "(b)", "(b)", "(b)",
"(b)", NA, "(b)", "(b)", "(b)", "(b)", NA, "(b)", NA, NA, "(b)",
NA, NA, NA, NA, NA), 2007 = c("13.199999999999999", "13", "13",
"20.300000000000001", "11.6", "5.2999999999999998", "11.6", "11.6",
"11.1", "15.199999999999999", "12.800000000000001", "12.800000000000001",
"14.5", "18.800000000000001", "10.300000000000001", "13.9", "10.1",
"7.2999999999999998", "15.699999999999999", "13.699999999999999",
"5.4000000000000004", "9.4000000000000004", "14.4", "12.699999999999999",
"14.800000000000001", "8.1999999999999993", "16.899999999999999",
"8.4000000000000004", "7.9000000000000004", "12.9", "4.5999999999999996",
"5.5999999999999996", "7.0999999999999996", ":", "38", ":", "40.799999999999997"
), ...17 = c(NA, NA, NA, NA, NA, "(b)", NA, NA, "(b)", NA, NA,
NA, NA, NA, NA, NA, NA, "(b)", NA, NA, NA, "(b)", NA, NA, NA,
NA, NA, NA, "(b)", "(b)", NA, NA, NA, NA, "(b)", NA, NA), 2008 = c("13.1",
"13.199999999999999", "12", "18.5", "10.699999999999999", "5",
"11", "11.4", "15.6", "14.800000000000001", "15.300000000000001",
"12.6", "13", "19.300000000000001", "10.9", "13.6", "11.9", "9.1999999999999993",
"15.9", "11.4", "5", "8.9000000000000004", "12.699999999999999",
"11.9", "13.199999999999999", "7.5", "15.300000000000001", "8.9000000000000004",
"8", "13.1", "5.2999999999999998", "5.2000000000000002", "6.9000000000000004",
":", "35.899999999999999", ":", "39.200000000000003"), ...19 = c(NA,
NA, NA, "(b)", NA, NA, "(b)", NA, NA, "(b)", NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, "(b)", NA, NA, NA, NA, NA, "(b)",
"(b)", NA, NA, NA, NA, NA, NA, NA), 2009 = c("14.800000000000001",
"15", "12.800000000000001", "20.800000000000001", "12.699999999999999",
"6.5", "11.4", "18.300000000000001", "20.199999999999999", "15.9",
"19.899999999999999", "14.699999999999999", "14.9", "20.5", "11.5",
"20.800000000000001", "15", "7.5", "17.899999999999999", "12.6",
"5.7999999999999998", "9.5999999999999996", "14", "12.5", "15.699999999999999",
"9.3000000000000007", "17.300000000000001", "11.300000000000001",
"9.9000000000000004", "14.4", "9.6999999999999993", "6.2000000000000002",
"8.8000000000000007", ":", "32.799999999999997", ":", "38.100000000000001"
), ...21 = c(NA, NA, NA, NA, NA, NA, NA, "(b)", NA, "(b)", NA,
NA, NA, NA, "(b)", NA, NA, "(b)", NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, "(b)", NA, NA, NA, NA, NA, NA), 2010 = c("15.199999999999999",
"15.300000000000001", "13", "23.5", "12.9", "7.2999999999999998",
"10.800000000000001", "18.100000000000001", "21.699999999999999",
"18.600000000000001", "20", "14.800000000000001", "17.600000000000001",
"22", "12.9", "20.699999999999999", "17", "6.0999999999999996",
"17.699999999999999", "12.199999999999999", "6.0999999999999996",
"9.0999999999999996", "14.800000000000001", "13.6", "18.899999999999999",
"9.4000000000000004", "19", "10.5", "8.3000000000000007", "14.6",
"10.1", "6.7000000000000002", "8.0999999999999996", ":", "31.800000000000001",
"24.800000000000001", "35.200000000000003"), ...23 = c(NA, NA,
NA, "(b)", NA, NA, "(b)", NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "(b)", NA, "(b)", NA, NA, NA, NA, NA,
NA, NA, "(b)", NA, NA, NA, NA), 2011 = c(15.4, 15.3, 13.8,
24.7, 12.1, 7.6, 9.7, 14.7, 22.4, 23, 20.6, 14.7, 19.1, 22.5,
14.8, 19.1, 14.7, 6.6, 17.6, 12.1, 5.9, 8.5, 15.2, 13.9, 19.5,
9.4, 18.7, 10, 7.9, 15.4, 7.6, 6.6, 8, 24.6, 31.6, 26.2, 32.7
), ...25 = c(NA, NA, "(b)", NA, "(b)", NA, "(b)", NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "(b)", NA,
NA, "(b)", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), 2012 = c(15.9,
15.9, 14.4, 24.7, 12.9, 8.2, 9.3, 15.1, 21.6, 26.8, 22.2, 15.1,
19.7, 23.8, 17.3, 17.2, 13.9, 7.6, 18.7, 12, 6.5, 8.2, 15.7,
15.6, 19.3, 11.8, 18.8, 10.4, 8.4, 15.3, 7, 6.4, 7.7, 24.4, 32.1,
26.2, 31.7), ...27 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), 2013 = c(15.9,
16, 14.9, 25.7, 12.8, 7.5, 8.7, 14.3, 18.8, 28.5, 22.5, 13.8,
22.3, 26, 20.4, 15.6, 13.7, 7.2, 18.4, 10.9, 7.5, 8.6, 16.2,
16.4, 19.6, 12.9, 19, 10.9, 7.9, 14.6, 6.4, 7, 8, 23.6, 31.3,
25.5, 29.3), ...29 = c(NA, NA, NA, NA, "(b)", NA, NA, NA, NA,
NA, NA, "(b)", NA, NA, NA, NA, NA, NA, NA, NA, "(b)", NA, "(b)",
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), 2014 = c(15.3,
15.6, 14.1, 24, 12.1, 7.3, 8.7, 13.8, 17.8, 26.7, 20.7, 14.1,
21.8, 26.2, 19.5, 15.2, 12.9, 6.5, 16.4, 11.6, 7.6, 9.3, 15.5,
14.6, 19.9, 12.9, 18.2, 11.8, 7.8, 13.4, 6.9, 7.1, 7.7, 22.5,
31.9, 25.5, 28.4), ...31 = c(NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, "(b)", "(b)", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "(b)", "(b)"
), 2015 = c(14.8, 15.2, 14.4, 22.2, 11.8, 7.7, 8.5, 12.5, 16.5,
24.1, 19.4, 14.7, 19.9, 25.7, 18.5, 13.8, 11.8, 7.6, 15.1, 11.8,
6.7, 8.7, 14.6, 13.2, 20.9, 12.3, 17.2, 12.4, 7.4, 12.7, 5.3,
7, 7.3, 23.4, 32.5, 24.6, 28.1), ...33 = c(NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "(b)", "(b)",
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA), 2016 = c(14.2, 14.5, 13, 22.4, 11.1, 7.4, 8.9, 13.8,
14.5, 22.2, 18.1, 14.4, 19.5, 24.3, 18, 13.3, 10.7, 6.8, 14.1,
9.4, 6.3, 8.9, 13.8, 12.8, 20.2, 10.9, 15.9, 11.7, 7.1, 12.3,
4.6, 7.1, 7.5, 22.3, 31.3, 22.3, 27.8), ...35 = c(NA, NA, NA,
NA, NA, "(b)", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA), 2017 = c(13.4, 13.9, 12.6, 18.9, 10, 9.1, 8.5,
11, 12.8, 21.3, 16.4, 13.9, 17.9, 24.1, 17.6, 12.3, 10.2, 6.6,
13.3, 8.8, 5.9, 8.4, 12.9, 10.6, 17.8, 9.3, 16, 10.9, 6.8, 11.4,
4.1, 6.4, 7.2, 21.4, 31.1, 21.7, 27.5), ...37 = c(NA, NA, "(b)",
NA, NA, "(b)", NA, NA, "(b)", NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, "(b)", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA), 2018 = c(12.9, 13.2, 12, 18.1, 9.5, 8.5,
7.9, 11.7, 11.6, 19.5, 15.3, 13.6, 15.6, 23.4, 14.9, 11.6, 9.3,
7.5, 12.9, 7.3, 5.7, 8.4, 12.1, 9.6, 17, 8.8, 14.6, 10.1, 7,
11.7, 5.4, 6.5, 6.6, 21, 29.8, 20.1, 27.6)), row.names = c(NA,
-37L), class = c("tbl_df", "tbl", "data.frame"))
dput(Jeunesut)
structure(list(2000 = c(NA, 14.8, 17.2, NA, NA, 6.1, 10.3,
18.2, NA, 20.8, 15.4, 13.4, NA, 21.9, 11.8, NA, 18.9, 8.1, 19.1,
26.9, 6, 9.6, NA, 10.1, 20.9, NA, NA, 11.8, 6.9, 12.5, 4.4, 24.2,
7.4, NA, NA, NA, NA), 2001 = c(NA, 14.3, 16.5, 32.8, NA, 6.7,
10.2, 17.9, NA, 20, 14.9, 12.9, NA, 20.8, 9.9, NA, 19.1, 8.2,
18.5, 19.4, 5.7, 9.3, 20.7, 10.2, 19.6, 10.1, NA, 10.5, 7.3,
12.6, 3.6, 23.6, 6.5, NA, NA, NA, NA), 2002 = c(15.6, 14.3,
16.4, 31, 16.5, 6.6, 10.9, 15, 14.4, 19.1, 15.2, 13.2, 21.7,
19.8, 9.5, 17.6, 15.2, 7.5, 18.3, 18.5, 6.1, 8, 21.7, 11.5, 23.5,
10.1, 27.2, 10.2, 7.6, 12.6, 5.4, 23.5, 7.2, NA, NA, NA, NA),
2003 = c(15.5, 14.4, 18, 30.6, 17.5, 6.8, 12.6, 14.2, 12.6,
20.4, 14.8, 12.8, 20.3, 19.5, 11.1, 16.1, 13.6, 6.9, 17.2,
20.5, 6.7, 7.5, 20.8, 12.4, 22.4, 9, 21.4, 10.6, 7.2, 9.6,
5.6, 10.6, 8.7, NA, NA, NA, NA), 2004 = c(15.3, 14.4, 16.3,
28.7, 17.7, 6.4, 12.9, 15.4, 12.8, 19.7, 14.4, 13.1, 19.2,
19.6, 10.2, 15.6, 12.9, 8.1, 16.9, 15.4, 6.6, 10.3, 19.6,
12, 21.2, 8.2, 21.2, 10.7, 7.9, 8.9, 6, 9.7, 7.6, NA, NA,
NA, NA), 2005 = c(15, 14.4, 14, 26.8, 16.9, 5.9, 13.8,
13.5, 11.8, 18.5, 14, 13.2, 17.9, 20, 17.9, 14.1, 10.7, 6.8,
17.1, 15, 7.7, 10.1, 18.4, 12.3, 18.4, 9.7, 20.2, 9.5, 10.4,
8.9, 5.1, 9.1, 7.8, NA, NA, NA, NA), 2006 = c(14, 13.5,
12.9, 23.9, 13.7, 4.7, 12.7, 10.8, 11.1, 15.5, 12.9, 13.2,
15.8, 19.2, 11.9, 13.7, 10.3, 8, 16.5, 13.6, 6.2, 9.6, 16.6,
12, 16.5, 9.7, 18.1, 9.4, 9.6, 8.9, 5, 6, 8, NA, 44.8, NA,
40.4), 2007 = c(13.2, 13, 13, 20.3, 11.6, 5.3, 11.6, 11.6,
11.1, 15.2, 12.8, 12.8, 14.5, 18.8, 10.3, 13.9, 10.1, 7.3,
15.7, 13.7, 5.4, 9.4, 14.4, 12.7, 14.8, 8.2, 16.9, 8.4, 7.9,
12.9, 4.6, 5.6, 7.1, NA, 38, NA, 40.8), 2008 = c(13.1,
13.2, 12, 18.5, 10.7, 5, 11, 11.4, 15.6, 14.8, 15.3, 12.6,
13, 19.3, 10.9, 13.6, 11.9, 9.2, 15.9, 11.4, 5, 8.9, 12.7,
11.9, 13.2, 7.5, 15.3, 8.9, 8, 13.1, 5.3, 5.2, 6.9, NA, 35.9,
NA, 39.2), 2009 = c(14.8, 15, 12.8, 20.8, 12.7, 6.5, 11.4,
18.3, 20.2, 15.9, 19.9, 14.7, 14.9, 20.5, 11.5, 20.8, 15,
7.5, 17.9, 12.6, 5.8, 9.6, 14, 12.5, 15.7, 9.3, 17.3, 11.3,
9.9, 14.4, 9.7, 6.2, 8.8, NA, 32.8, NA, 38.1), 2010 = c(15.2,
15.3, 13, 23.5, 12.9, 7.3, 10.8, 18.1, 21.7, 18.6, 20, 14.8,
17.6, 22, 12.9, 20.7, 17, 6.1, 17.7, 12.2, 6.1, 9.1, 14.8,
13.6, 18.9, 9.4, 19, 10.5, 8.3, 14.6, 10.1, 6.7, 8.1, NA,
31.8, 24.8, 35.2), 2011 = c(15.4, 15.3, 13.8, 24.7, 12.1,
7.6, 9.7, 14.7, 22.4, 23, 20.6, 14.7, 19.1, 22.5, 14.8, 19.1,
14.7, 6.6, 17.6, 12.1, 5.9, 8.5, 15.2, 13.9, 19.5, 9.4, 18.7,
10, 7.9, 15.4, 7.6, 6.6, 8, 24.6, 31.6, 26.2, 32.7), 2012 = c(15.9,
15.9, 14.4, 24.7, 12.9, 8.2, 9.3, 15.1, 21.6, 26.8, 22.2,
15.1, 19.7, 23.8, 17.3, 17.2, 13.9, 7.6, 18.7, 12, 6.5, 8.2,
15.7, 15.6, 19.3, 11.8, 18.8, 10.4, 8.4, 15.3, 7, 6.4, 7.7,
24.4, 32.1, 26.2, 31.7), 2013 = c(15.9, 16, 14.9, 25.7,
12.8, 7.5, 8.7, 14.3, 18.8, 28.5, 22.5, 13.8, 22.3, 26, 20.4,
15.6, 13.7, 7.2, 18.4, 10.9, 7.5, 8.6, 16.2, 16.4, 19.6,
12.9, 19, 10.9, 7.9, 14.6, 6.4, 7, 8, 23.6, 31.3, 25.5, 29.3
), 2014 = c(15.3, 15.6, 14.1, 24, 12.1, 7.3, 8.7, 13.8,
17.8, 26.7, 20.7, 14.1, 21.8, 26.2, 19.5, 15.2, 12.9, 6.5,
16.4, 11.6, 7.6, 9.3, 15.5, 14.6, 19.9, 12.9, 18.2, 11.8,
7.8, 13.4, 6.9, 7.1, 7.7, 22.5, 31.9, 25.5, 28.4), 2015 = c(14.8,
15.2, 14.4, 22.2, 11.8, 7.7, 8.5, 12.5, 16.5, 24.1, 19.4,
14.7, 19.9, 25.7, 18.5, 13.8, 11.8, 7.6, 15.1, 11.8, 6.7,
8.7, 14.6, 13.2, 20.9, 12.3, 17.2, 12.4, 7.4, 12.7, 5.3,
7, 7.3, 23.4, 32.5, 24.6, 28.1), 2016 = c(14.2, 14.5, 13,
22.4, 11.1, 7.4, 8.9, 13.8, 14.5, 22.2, 18.1, 14.4, 19.5,
24.3, 18, 13.3, 10.7, 6.8, 14.1, 9.4, 6.3, 8.9, 13.8, 12.8,
20.2, 10.9, 15.9, 11.7, 7.1, 12.3, 4.6, 7.1, 7.5, 22.3, 31.3,
22.3, 27.8), 2017 = c(13.4, 13.9, 12.6, 18.9, 10, 9.1,
8.5, 11, 12.8, 21.3, 16.4, 13.9, 17.9, 24.1, 17.6, 12.3,
10.2, 6.6, 13.3, 8.8, 5.9, 8.4, 12.9, 10.6, 17.8, 9.3, 16,
10.9, 6.8, 11.4, 4.1, 6.4, 7.2, 21.4, 31.1, 21.7, 27.5),
2018 = c(12.9, 13.2, 12, 18.1, 9.5, 8.5, 7.9, 11.7, 11.6,
19.5, 15.3, 13.6, 15.6, 23.4, 14.9, 11.6, 9.3, 7.5, 12.9,
7.3, 5.7, 8.4, 12.1, 9.6, 17, 8.8, 14.6, 10.1, 7, 11.7, 5.4,
6.5, 6.6, 21, 29.8, 20.1, 27.6)), class = c("tbl_df", "tbl",
"data.frame"), row.names = c(NA, -37L))

mutate_at() is more suitable for this scenario, you could do something like this:

library(dplyr)

Jeunesu %>%
    mutate_at(vars(-`geo\time`), as.numeric)

Unfortunately it's not working :

Error in is_character(x) : objet 'geo\time' introuvable

To help us help you, could you please prepare a reproducible example (reprex) illustrating your issue? Please have a look at this guide, to see how to create one:

The reprex

Jeunesu <- Jeunesu %>% pivot_longer(c(2000, 2001, 2002,
2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010,
2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018))
#> Error in Jeunesu %>% pivot_longer(c(2000, 2001, 2002, 2003, 2004, : impossible de trouver la fonction "%>%"

but when i do it, i've this error : Erreur : No common type for 2000 and 2011 .
and not impossible to find %>% fonction

That's because my data are in numeric format at 2011 to 2018 and character before, and i looking for a fonction to transform my data on numeric except for the first column

That is not a reproducible example and it is about a different topic, in your original question, you were asking about dplyr::mutate_if() not tidyr::pivot_longer()

Please don't go off-topic in your own thread and try to make a proper reprex as explained in the link I gave you before.

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