data <- structure(list(A_w = c(0, 0.69, 1.41, 2.89, 6.42, 13.3, 25.5,
36.7, 44.3, 46.4), E_w = c(1.2, 1.2, 1.5, 1.6, 1.9, 2.3, 3.4,
4.4, 10.6, 16.5), A_e = c(0, 0.18, 0.37, 0.79, 1.93, 4.82, 11.4,
21.6, 31.1, 36.2), E_e = c(99.4, 99.3, 98.9, 98.4, 97.1, 93.3,
84.7, 71.5, 58.1, 48.7)), row.names = c(NA, -10L), class = "data.frame")
data
#> A_w E_w A_e E_e
#> 1 0.00 1.2 0.00 99.4
#> 2 0.69 1.2 0.18 99.3
#> 3 1.41 1.5 0.37 98.9
#> 4 2.89 1.6 0.79 98.4
#> 5 6.42 1.9 1.93 97.1
#> 6 13.30 2.3 4.82 93.3
#> 7 25.50 3.4 11.40 84.7
#> 8 36.70 4.4 21.60 71.5
#> 9 44.30 10.6 31.10 58.1
#> 10 46.40 16.5 36.20 48.7
Created on 2021-05-31 by the reprex package (v2.0.0)
I am trying to plot this data with all A values as X and Es as Y. How can I put either a) both of these columns plotted on a ggplot2, or b) rearrange this dataframe to combine the A columns and E columns into a final dataframe with only two columns with 2x as many rows as pictured?
Thanks for any help, I am a beginner (obviously)
Edit for Clarity: It's important that the A_e & E_e values remain as pairs, similar to how the A_w and E_w values remain as pairs. The end result plot should resemble the ORANGE and BLUE lines of this image, but I am trying to replicate this while learning R.

Currently I am capable of plotting each separately when dividing into two dataframes of 2x10
A_w E_w
1 0.00 1.2
2 0.69 1.2
3 1.41 1.5
4 2.89 1.6
5 6.42 1.9
6 13.30 2.3
7 25.50 3.4
8 36.70 4.4
9 44.30 10.6
10 46.40 16.5

and the second plot
# A tibble: 10 x 2
A_e E_e
<dbl> <dbl>
1 0 99.4
2 0.18 99.3
3 0.37 98.9
4 0.79 98.4
5 1.93 97.1
6 4.82 93.3
7 11.4 84.7
8 21.6 71.5
9 31.1 58.1
10 36.2 48.7

But my end goal is to have them both on the same plot, like in the Excel graph (orange + blue graph) above.


