ggplot2 two dataframes and two axes data not plotting-CodePudding

I have looked at similar questions and am trying to follow an example from a climate graph with temperature and precipitation.

I am on the correct track, as both of the axes seem to have the correct limits. For some reason the bar graph of the proportion of the population isn't showing up.

Im not getting any errors, I guess I'm just missing something. Any help appreciated thanks.

Here's my code:

  ## plot per capita spending and old people increase on same plot
  ##calculate a and b for scaling second axis
  ylim.prim=range(TA1_summ$Total.Health.Expenditure.per.Capita.in.Dollars)
  ylim.sec=range(Prop75pls_df$Prop_75pls)
  ## formula to scale axes for double axes
  b <- diff(ylim.prim)/diff(ylim.sec)
  a <- ylim.prim[1] - b*ylim.sec[1]
  ##


    ggplot() 
   geom_point(data=TA1_summ,aes(x=Year,y=Total.Health.Expenditure.per.Capita.in.Dollars)) 
    geom_col(data=Prop75pls_df,aes(x=Year,y=Prop_75pls)) 
    #
    scale_y_continuous("per capita health care spending (CDN)", sec.axis = sec_axis(~ (. - a)/b, name = "Proportion of population 75 "))  
    theme_bw()

Here's the graph, notice the points for the percapita spending are there, but the bars for the proportion 75 are not.

Below are the 2 dataframes. Thanks

 > dput(TA1_summ)
structure(list(Year = 1975:2021, Total.Health.Expenditure.in.Millions.of.Dollars = c(12199.4, 
14049.8, 15450, 17106.8, 19169.7, 22298.4, 26276.7, 30759.1, 
34038.6, 36743.1, 39842.4, 43338.1, 46789.2, 50960.1, 56096.2, 
61092.9, 66437.4, 69853.4, 71519.1, 73159.6, 74237.4, 75082.3, 
78741.4, 84066.9, 90467.9, 98609.9, 107201.8, 115055.9, 123591.3, 
131570.3, 140489.5, 151037.6, 162992.3, 171964.7, 182026, 192956, 
199383.5, 207501.6, 212366.5, 218591.2, 228095.8, 237351.6, 246090.5, 
255913.1, 267215.6, 301454.8, 308043.3), Total.Health.Expenditure.per.Capita.in.Dollars = c(527.1, 
599.1, 651.2, 713.9, 792.1, 909.6, 1058.7, 1224.6, 1341.9, 1434.9, 
1541.8, 1660.4, 1769.2, 1902.1, 2056.6, 2206.2, 2369.6, 2462.1, 
2493.3, 2522.7, 2533.5, 2535.7, 2633, 2787.8, 2975.8, 3213.5, 
3455.8, 3668.9, 3905.7, 4119.2, 4357.1, 4637.2, 4955.8, 5172.3, 
5412.8, 5674.4, 5806.3, 5977.4, 6053.3, 6168.4, 6388.7, 6573.1, 
6733.8, 6904.4, 7108, 7931.9, 8018.5), Total.Health.Expenditure.in.Constant.1997.Millions..of.Dollars = structure(c(22L, 
23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 
36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 
2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 
16L, 17L, 18L, 19L, 20L, 21L), .Label = c("", "100,842.1", "105,685.2", 
"110,371.9", "114,160.9", "119,135.3", "125,204.7", "128,118.1", 
"131,863.3", "137,580.0", "138,330.6", "141,924.8", "142,284.2", 
"144,006.1", "148,241.5", "154,367.0", "158,689.7", "162,505.5", 
"165,289.9", "177,972.0", "180,029.3", "39,684.0", "40,766.5", 
"41,609.5", "42,940.6", "44,203.5", "46,676.2", "51,123.1", "53,484.5", 
"55,455.0", "57,311.8", "59,558.8", "62,192.5", "63,808.3", "66,399.6", 
"69,198.5", "71,242.7", "73,922.6", "75,123.8", "75,381.6", "75,804.7", 
"76,063.2", "76,161.2", "78,741.4", "82,555.7", "86,940.8", "91,035.0", 
"96,707.7"), class = "factor"), Total.Health.Expenditure..per.Capita.in.Constant..1997.Dollars = structure(c(2L, 
3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 
18L, 23L, 24L, 21L, 20L, 19L, 17L, 22L, 25L, 26L, 27L, 28L, 29L, 
30L, 31L, 32L, 33L, 34L, 35L, 36L, 38L, 37L, 41L, 39L, 40L, 42L, 
43L, 44L, 45L, 46L, 47L, 48L), .Label = c("", "1,714.7", "1,738.5", 
"1,753.8", "1,791.9", "1,826.5", "1,903.9", "2,059.8", "2,129.4", 
"2,186.2", "2,238.1", "2,304.7", "2,382.8", "2,412.7", "2,478.4", 
"2,536.9", "2,572.1", "2,572.8", "2,595.8", "2,613.9", "2,627.9", 
"2,633.0", "2,636.6", "2,647.9", "2,737.7", "2,859.8", "2,966.7", 
"3,117.5", "3,215.6", "3,339.8", "3,455.5", "3,540.6", "3,657.7", 
"3,806.9", "3,853.5", "3,921.1", "4,028.3", "4,045.9", "4,055.7", 
"4,063.7", "4,088.4", "4,152.1", "4,275.0", "4,342.3", "4,384.3", 
"4,396.8", "4,682.8", "4,686.3"), class = "factor"), Total.Health.Expenditure.as.a.Percentage.of.GDP = c(7, 
7, 7, 7, 6.8, 7.1, 7.1, 7.9, 8.1, 8, 8, 8.2, 8.1, 8.1, 8.4, 8.8, 
9.5, 9.7, 9.6, 9.2, 8.9, 8.7, 8.7, 8.9, 9, 8.9, 9.4, 9.6, 9.8, 
9.9, 9.9, 10.1, 10.3, 10.4, 11.6, 11.6, 11.2, 11.4, 11.2, 11, 
11.5, 11.7, 11.5, 11.5, 11.6, 13.7, 12.7)), row.names = c(NA, 
47L), na.action = structure(48:105, .Names = c("48", "49", "50", 
"51", "52", "53", "54", "55", "56", "57", "58", "59", "60", "61", 
"62", "63", "64", "65", "66", "67", "68", "69", "70", "71", "72", 
"73", "74", "75", "76", "77", "78", "79", "80", "81", "82", "83", 
"84", "85", "86", "87", "88", "89", "90", "91", "92", "93", "94", 
"95", "96", "97", "98", "99", "100", "101", "102", "103", "104", 
"105"), class = "omit"), class = "data.frame")


    > dput( Prop75pls_df)
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), Prop_75pls = c(2.95766554965851, 
3.00127503220918, 3.05129670837176, 3.11304063523594, 3.18934390585209, 
3.25769147676869, 3.33837995428998, 3.41631016897725, 3.50054745341369, 
3.59622982947609, 3.6940577447635, 3.79014384913296, 3.89859027580637, 
4.00409456787977, 4.10658248874934, 4.2127362212327, 4.28299210465241, 
4.34725032514741, 4.39672019981841, 4.44576578342527, 4.55353117703572, 
4.67241226584368, 4.79907907522439, 4.91693361767564, 5.03853805953953, 
5.15658755870346, 5.67448038744973, 5.78812317405195, 5.91193068088551, 
6.01461053319038, 6.12839020321239, 6.25496029096157, 6.34749433891701, 
6.4232424596923, 6.47606470566458, 6.54317971748121, 6.61162617975518, 
6.67251883104279, 6.73754838318347, 6.81701708941406, 6.89445520796233, 
7.00259186733946, 7.12988965237494, 7.2674973568116, 7.42862666992543, 
7.59432265315821, 7.82893516903733)), class = "data.frame", row.names = 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"))

CodePudding user response：

You've got to use the same transformation on the data that you did on the axes:

ggplot() 
  geom_col(data=Prop75pls_df,aes(x=Year,y=(a Prop_75pls*b)), alpha=.25) 
  geom_point(data=TA1_summ,aes(x=Year,y=Total.Health.Expenditure.per.Capita.in.Dollars)) 
  #
  scale_y_continuous("per capita health care spending (CDN)", sec.axis = sec_axis(~ (. - a)/b, name = "Proportion of population 75 "))  
  theme_bw()