how can I change the plot order and width of just one line in geom_line

Question

I am trying to map the per capita healthcare spending by province. I would like the Canadian Average line to be a different color and width and plotted on top. I don't want to change the factor order to make it be plotted last, as the factor order is related to the numerical values.

Here is my 'raw' working code and plot, however I'd like to move the average to the top.

color_count<-length(levels(TabB42_melt$variable))
gg_color_hue <- function(n) {
  hues = seq(15, 375, length = n + 1)
  hcl(h = hues, l = 65, c = 100)[1:n]
}
col.pal<-gg_color_hue(color_count-1)
col.pal_wB<-c(col.pal[1:10],"black",col.pal[11:length(col.pal)])
# working plot        
main.plot.right.bottom<-ggplot(TabB42_melt, 
                                     aes(x=Year, y=value, group=variable, color=variable,size=variable))+
      geom_line()+
     scale_size_manual(values=c(rep(1,10),3,rep(1,3)))+
      scale_color_manual(values=col.pal_wB)+
    #  geom_line(data=subset(TabB42_melt,variable=="Average"),aes(x=Year,y=value,size=3,color="black"))+
      ylab("per capita health care spending (CDN)")+
      ggtitle("Per capita spending is increasing over the years")+
      labs(colour="Province")+
      guides(size=FALSE)+
      theme_bw()

So I tried two different layers of geom_line to get the average on top, but I think this is messing with the color scale of the lines. As I get this error "Error: Insufficient values in manual scale. 15 needed but only 14 provided." I have 14 variables. I tried adding 'black" to the end of the scale_color_manual but that didn't work.

Any help appreciated. Thanks

##  Here is one of my attempts to change the width and plotting order of the 'Average' variable  
main.plot.right.bottomv2<-ggplot()+
      # geom_line(lwd=c(rep(1,9),2,rep(1,4)))+
      geom_line(data=TabB42_melt, 
                aes(x=Year, y=value, group=variable, color=variable))+
      #scale_size_manual(values=c(rep(1,10),3,rep(1,3)))+
      scale_color_manual(values=col.pal_wB)+
      geom_line(data=subset(TabB42_melt,variable="Average"), 
                aes(x=Year, y=value, color="black",size=3))+
      #  geom_line(data=subset(TabB42_melt,variable=="Average"),aes(x=Year,y=value,size=3,color="black"))+
      ylab("per capita health care spending (CDN)")+
      ggtitle("Per capita spending is increasing over the years")+
      labs(colour="Province")+
      guides(size=FALSE)+
      theme_bw()

Here's my data:

> dput(TabB42_melt)
structure(list(Year = c(1975, 1976, 1977, 1978, 1979, 1980, 1981, 
1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 
1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 
2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 
2015, 2016, 2017, 2018, 2019, 2020, 2021, 1975, 1976, 1977, 1978, 
1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 
1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 
2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 
2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 1975, 
1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 
1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 
1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 
2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 
2020, 2021, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 
1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 
1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 
2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 
2017, 2018, 2019, 2020, 2021, 1975, 1976, 1977, 1978, 1979, 1980, 
1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 
1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 
2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 
2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 1975, 1976, 1977, 
1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 
1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 
2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 
2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 
1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 
1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 
1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 
2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 
2019, 2020, 2021, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 
1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 
1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 
2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 
2016, 2017, 2018, 2019, 2020, 2021, 1975, 1976, 1977, 1978, 1979, 
1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 
1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 
2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 
2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 1975, 1976, 
1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 
1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 
1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 
2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 
2021, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 
1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 
1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 
2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 
2018, 2019, 2020, 2021, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 
1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 
1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 
2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 
2015, 2016, 2017, 2018, 2019, 2020, 2021, 1975, 1976, 1977, 1978, 
1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 
1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 
2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 
2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 1975, 
1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 
1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 
1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 
2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 
2020, 2021), variable = structure(c(4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 
7L, 7L, 7L, 7L, 7L, 7L, 7L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 
14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 
14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 
14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 13L, 
13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 
13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 
13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 
13L, 13L, 13L, 13L, 13L, 13L, 13L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
10L, 10L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 
9L, 9L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
8L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 11L, 11L, 11L, 11L, 11L, 
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 
11L, 11L, 11L), .Label = c("Nun.", "N.W.T", "Y.T.", "N.L.", "N.S.", 
"Que.", "P.E.I.", "Alta.", "Sask.", "Man.", "Average", "B.C.", 
"Ont.", "N.B."), class = "factor"), value = c(357.92, 389.23, 
412.98, 455.02, 521.43, 588.11, 683.86, 805, 890.49, 921.67, 
969.15, 1060.54, 1147.31, 1216.36, 1302.73, 1447.9, 1485.43, 
1518.73, 1518.77, 1571.25, 1631.09, 1654.49, 1757.47, 1945.49, 
2232.1, 2361.57, 2554.73, 2739.82, 2889.46, 2973.8, 3093.19, 
3311.42, 3671.78, 3908.81, 4262.7, 4676.92, 4950.97, 5347.52, 
5429.27, 5449.55, 5637.18, 5723.97, 5799.18, 5989.03, 6358.77, 
6615.43, 6988.86, 352.59, 382.68, 419.5, 463.22, 508.78, 586.83, 
680.54, 796.93, 875.34, 920.53, 963.5, 1025.46, 1107.45, 1189.14, 
1253.34, 1331.76, 1454.39, 1499.89, 1552.83, 1502.18, 1511.41, 
1570.6, 1571.72, 1684.94, 1766.79, 1892.16, 2232.42, 2516.12, 
2583.01, 2525.88, 2689.21, 2797.3, 3042.09, 3261.94, 3638.25, 
3954.96, 4286.26, 4353.91, 4394.23, 4398.63, 4494.02, 4594.66, 
4705.94, 4843.34, 4997.89, 5178.54, 5433.98, 322.88, 362.39, 
398.29, 438.04, 486.34, 556.45, 669.59, 771.39, 839.18, 912.11, 
979.28, 1031.39, 1104.92, 1194.41, 1304.32, 1387.83, 1457.77, 
1475.64, 1431.86, 1381.14, 1403.47, 1414.88, 1664.5, 1777.72, 
1873.81, 1914.85, 2021.54, 2204.23, 2421.85, 2513.27, 2747.41, 
3044.14, 3311.35, 3457.21, 3610.8, 3973.09, 4220.21, 4332.4, 
4388.16, 4474.65, 4567.14, 4555.62, 4650.35, 4771.47, 4953.03, 
5424.16, 5702.53, 300.87, 351.6, 390.49, 427.56, 478.8, 559.39, 
676.9, 819.26, 877.41, 932.06, 982.59, 1047.13, 1151.39, 1233.45, 
1334.73, 1428.3, 1478.19, 1527.04, 1542.11, 1585.33, 1644.86, 
1640.92, 1613.12, 1691.45, 1824.89, 1955.5, 2129.81, 2240.94, 
2392.4, 2605.2, 2849.55, 3145.79, 3357.47, 3521.85, 3716.34, 
3884.34, 4075.05, 4195.99, 4191.83, 4184.63, 4311.75, 4363.55, 
4446.99, 4533.38, 4613.65, 4781.31, 4946.3, 399.86, 464.68, 508.18, 
568.57, 632.25, 708.24, 804.64, 927.13, 1020.88, 1080.57, 1136.73, 
1150.14, 1217.62, 1315.9, 1390.82, 1474.49, 1607.51, 1648.57, 
1657.31, 1676.15, 1685.96, 1649.61, 1672.38, 1799.5, 1844.39, 
1969.32, 2098.4, 2196.37, 2290.48, 2416.1, 2525.49, 2689.59, 
2900.32, 3012.24, 3202.49, 3312.79, 3418.21, 3483.25, 3607.15, 
3673.01, 4009.56, 4031.53, 4185.75, 4384.73, 4563.7, 5480.08, 
5437.07, 377.83, 429.35, 462.03, 492.35, 527.1, 590.51, 688.8, 
796.42, 887.12, 962.82, 1048.64, 1165.07, 1266.18, 1380.58, 1492.51, 
1573.06, 1720.9, 1779.22, 1741.64, 1733.36, 1694.01, 1686.97, 
1698.1, 1770.37, 1876.86, 2049.18, 2122.92, 2253.33, 2481.04, 
2636.77, 2788.45, 2928.65, 3170.64, 3306.74, 3487.16, 3617.1, 
3697.06, 3833.5, 3884.51, 3960.19, 4024.97, 4059.16, 4136.26, 
4237.47, 4337.11, 4889.25, 5042.08, 367.52, 435.49, 479.36, 504.31, 
549.26, 631.07, 756.03, 875.47, 963.68, 1028.27, 1092.5, 1163.15, 
1242.52, 1328.95, 1437.74, 1576.56, 1612.06, 1678.65, 1661.39, 
1657.61, 1685.66, 1695.27, 1739.74, 1848.64, 2096.61, 2293.04, 
2426.56, 2562.86, 2767.71, 2928.95, 3138.72, 3300.67, 3499.03, 
3702.16, 3960.29, 4119.05, 4245.72, 4433.22, 4571.21, 4550.51, 
4714.38, 4721.15, 4748.52, 4760.18, 4825.88, 5215.87, 5274.97, 
329.31, 390.82, 434.85, 468.12, 529.79, 624.78, 727.41, 870.71, 
964.38, 1008.2, 1074.5, 1189.28, 1224.32, 1312.28, 1471.6, 1623.81, 
1653.71, 1629.43, 1528.81, 1545.72, 1573.25, 1606.99, 1718.43, 
1823.56, 1971.33, 2083.39, 2279.61, 2416.3, 2560.15, 2759.2, 
3026.39, 3238.31, 3494.44, 3684.94, 3852.33, 4064.65, 4264.8, 
4401.23, 4581.07, 4652.92, 4783.14, 4893.97, 4926.76, 4855.19, 
5014.29, 5370.49, 5330.25, 384.21, 434.15, 451.21, 504.61, 600, 
689.25, 816.76, 1023.82, 1156.99, 1187.79, 1262.24, 1363.31, 
1355.29, 1395.33, 1518.19, 1587.17, 1635.98, 1711.66, 1669.19, 
1519.48, 1427.96, 1474.27, 1599.95, 1688.81, 1910.49, 2068.73, 
2300.06, 2471.17, 2603.45, 2812.99, 3069.91, 3290.63, 3615.13, 
3820.95, 3964.84, 4385.55, 4465.07, 4575.17, 4637.15, 4686.45, 
4811.95, 4935.6, 5070.89, 5166.64, 5184.18, 5540.48, 5343.45, 
371.34, 427.29, 464.19, 521.51, 583.99, 703.72, 840.17, 945.7, 
1008.5, 1043.32, 1075.79, 1146.37, 1200.79, 1277.23, 1393.9, 
1532.03, 1653.41, 1747.22, 1800.6, 1833.71, 1855, 1854.8, 1882.94, 
1947.81, 2091.74, 2268.94, 2481.86, 2624.9, 2711.99, 2751.55, 
2900.07, 2991.66, 3178.81, 3341.01, 3438.72, 3564.07, 3663.65, 
3733.93, 3723.32, 3787.74, 3871.96, 3967.37, 4043.52, 4136.49, 
4306.92, 4801.53, 5083.86, 281.7, 393.11, 444.82, 492.42, 538.34, 
590.83, 628.88, 908.05, 963.37, 982.67, 1019.67, 1127.93, 1142.33, 
1253.68, 1334.71, 1382.16, 1580.57, 1632.18, 1915.11, 2407.36, 
2258.1, 2153.88, 2187.45, 2380.77, 2547.98, 2755.14, 3213.64, 
3366.84, 3356.29, 3601.41, 3844.92, 4313.06, 4503.21, 4858.75, 
5521.38, 5745.98, 6010.87, 6197.59, 6443.51, 6529.87, 6967.44, 
8480.61, 9325.13, 8664.89, 8495.86, 9322.57, 8978.91, 355.89, 
427.6, 525.96, 619.82, 610.04, 631.38, 748.69, 1034.42, 1137.97, 
1184.06, 1325.52, 1668.05, 1916.6, 2636.14, 3050.94, 3188, 3513.43, 
3429.32, 3446.57, 3292.77, 3321.66, 2979.39, 3152.31, 3457.57, 
4104.62, 3758.43, 4180.85, 4585.45, 4490.68, 4875.03, 5006.24, 
5254.51, 5867.96, 6343.1, 6718.48, 7365.17, 8085.91, 8386.79, 
9403.26, 10093.24, 10667.29, 11775.22, 11238.25, 11823.46, 12068.37, 
12587.76, 13975.46, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 4303.64, 
4957.45, 5190.77, 5907.38, 8040.08, 8170.02, 7388.67, 8273.89, 
8772.8, 8599.52, 9145.4, 9436.84, 9985.63, 10544.22, 11072.15, 
11685.66, 12217.59, 12569.16, 13693.8, 14528.2, 15725.21, 16300.3, 
18114.16, 376.32, 431.98, 467.93, 512.01, 565.94, 644.24, 751.63, 
875.99, 966.24, 1024.87, 1091.35, 1168.63, 1241.06, 1336.46, 
1441.96, 1536.1, 1652.23, 1707.42, 1693.99, 1687.33, 1675.21, 
1669.98, 1710.37, 1803.16, 1922.23, 2074.98, 2209.45, 2341.71, 
2503.4, 2641.83, 2803.29, 2965.07, 3203.39, 3352.63, 3527.69, 
3701.48, 3808.3, 3922.67, 3993.35, 4058.53, 4206.86, 4261.68, 
4361.14, 4475.34, 4599.53, 5175.58, 5260.56)), row.names = c(NA, 
-658L), class = "data.frame")

It would be easier to help you if you provide [a minimal reproducible example](https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example) including a snippet of your data or some fake data. — stefan, Dec 04 '21 at 15:02
... this said. The issue with your second approach is that you use `color="black"` which adds an additional category. Hence you end up with insufficient values. Try with `color=variable`. — stefan, Dec 04 '21 at 15:05
The data/code you provided does not produce the plot you show in your question — neuron, Dec 04 '21 at 16:21

score 0 · Answer 1 · answered Dec 04 '21 at 16:49

gghighlight provides gghighlight() which can be used to selectively highlight some lines, points or other geom_. I couldn't get your dataset working, so I generated a random dataset. The code should work for your case as well.

Code

library(gghighlight)
year = 1970:2020
value = rnorm(length(year), 2000, 5)
x = c("A", "B", "C", "D", "E")
variable = sample(x, length(year), replace = T)
df = data.frame(year = year,
                value = value,
                variable = variable)

Now comes the cool part.

df %>%
  ggplot(aes(x = year, y = value, colour = variable)) +
  geom_line() + 
  gghighlight(variable == "A") +
  theme_minimal()

Voila!

wow. that's cool. but I can't seem to install it. Its having trouble with the dependencies. — user2814482, Dec 04 '21 at 21:17

score 0 · Answer 2 · answered Dec 04 '21 at 21:35

I got it figured out using the color=variable from Stefan, and I changed from size to lwd and moved it outside of the aes()

main.plot.right.bottomv2<-ggplot()+
  # geom_line(lwd=c(rep(1,9),2,rep(1,4)))+
  geom_line(data=TabB42_melt, 
            aes(x=Year, y=value, group=variable, color=variable))+
  #scale_size_manual(values=c(rep(1,10),3,rep(1,3)))+
  scale_color_manual(values=col.pal_wB)+
  geom_line(data=subset(TabB42_melt,variable=="Average",drop.levels=T), 
            aes(x=Year, y=value, color=variable),lwd=1.5)+
  ylab("per capita health care spending (CDN)")+
  ggtitle("Per capita spending is increasing over the years")+
  labs(colour="Province")+
  guides(size=FALSE)+
  theme_bw()+
  theme(axis.text = element_text(size = 12),
        axis.title = element_text(size = 12),
        legend.text=element_text(size=10),strip.text = element_text(size = 10),
        legend.title = element_blank(), legend.justification="left",
        legend.margin=margin(0,0,0,0),
        legend.box.margin=margin(-5,-5,-5,-5))

how can I change the plot order and width of just one line in geom_line

2 Answers2

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