I have a dataset
structure(list(X = c(26.7788998092606, 18.6280163936587, 14.349845629237,
9.66310505252417, 7.94423462318618, 5.04943860391983, 3.27216212415563,
2.94046432374716, 2.16429582651011, 1.63761158654806, 1.11240348866093
), X0 = 1:11, index1 = c(26.7788998092606, 18.6280163936587,
14.349845629237, 9.66310505252417, 7.94423462318618, 5.04943860391983,
3.27216212415563, 2.94046432374716, 2.16429582651011, 1.63761158654806,
1.11240348866093), variance_pct = c(28.6281410315749, 19.9143909665674,
15.3407872385057, 10.3303995390774, 8.49283095274311, 5.39813216797301,
3.49812424840959, 3.14352075545081, 2.31375323843416, 1.75069834043094,
1.18922152083292), cumulative_variance = c(28.6281410315749,
48.5425319981423, 63.883319236648, 74.2137187757255, 82.7065497284686,
88.1046818964416, 91.6028061448512, 94.746326900302, 97.0600801387361,
98.8107784791671, 100)), row.names = c(NA, -11L), class = "data.frame")
and I would like to create a scree plot such that the primary y-axis is scales from 0-30 and the secondary from 0-100.
My code now looks:
p2 <- ggplot(data = pca, aes(x = X0)) +
geom_point(aes(y = variance_pct), size = 4, color = "blue") +
geom_line(aes(y = variance_pct), color = "blue") +
scale_y_continuous(name = "Variance Explained (%)", breaks = seq(0, 30, 5)) +
labs(title = "Scree Plot") +
theme_bw() +
scale_y_continuous(
sec.axis = sec_axis(~ . * 100 / 30, name = "Cumulative Variance Explained (%)", breaks = seq(0, 100, 20)),
limits = c(0, 100)
) +
geom_point(aes(y = cumulative_variance), size = 4, color = "red") +
geom_line(aes(x = X0, y = cumulative_variance), color = "red") +
labs(title = "Scree Plot with Cumulative Variance Explained")
p2
and the figure:
Can I fix the values in the y-axis to be 0-30 and 0-100?
>Solution :
It’s a common misapprehension that adding a secondary axis will transform the data with it. When adding a secondary axis the key thing to remember is that it is just an inert annotation. If you want the red line to be represented by that axis, you need to change the data too, by applying the opposite transformation that you applied to the secondary axis. Also, the limits argument needs to refer to the primary axis, not the secondary axis, so it should be c(0, 30)
ggplot(data = pca, aes(x = X0)) +
geom_point(aes(y = variance_pct, color = "Variance percent"), size = 4) +
geom_line(aes(y = variance_pct,color = "Variance percent")) +
scale_y_continuous(name = "Variance Explained (%)", breaks = seq(0, 30, 5)) +
labs(title = "Scree Plot") +
theme_bw() +
scale_y_continuous(
sec.axis = sec_axis(~ . * 100 / 30,
name = "Cumulative Variance Explained (%)",
breaks = seq(0, 100, 20)),
limits = c(0, 30)
) +
geom_point(aes(y = 3/10 * cumulative_variance, color = "Cumulative variance"),
size = 4) +
geom_line(aes(y = 3/10 *cumulative_variance, color = "Cumulative variance")) +
scale_color_brewer(palette = "Set1") +
labs(title = "Scree Plot with Cumulative Variance Explained")
