Sin curve question

This is not excel-help, but to the best of my knowledge Excel interpolates with splines when you select curved point interpolation.

R, being primarily a science tool rather than a business tool, assumes you want to be precise about how new points are to be interpolated between original data points. Thus, the task of building the spline and deciding how close the points in that interpolation need to be is typically left to the user. If the user knows that the points are part of a periodic continuous function and extrapolation is desired, then choosing a fourier series may be a better choice than a spline. But the data you have provided is insufficient to support a fourier analysis, so there is some sophisticated math in between you and your goal unless you build in heuristics about how to interpolate within these points, or just live with whatever a spline function will give you... but the choice is yours to make.

Colleagues,

Here is my code which plots sin(x) vs x, for angles between 0 and 180
degrees.

library(ggplot2)
library(REdaS)
copdat$degrees <- c(0,45,90,135,180)
copdat$radians <- deg2rad(copdat$degrees)
copdat$sin_x <- sin(copdat$radians)

ggplot(copdat,aes(x=degrees,y=sin_x))+
 geom_point(size = 2)+ geom_line()+
 theme_cowplot()+xlab("x")+
 ylab("sin(x)")+
 scale_x_continuous(breaks=seq(0,180,30))+
 ggtitle("sin(x) vs x\nx is in degrees")

My trig students would prefer a curved line plot similar to what can be
plotted with Excel smooth line functionality.
I wanted to provide a relatively simple R script using ggplot to do
this
without having to resort to fitting a sine curve to these points.

Some guidance would be appreciated.

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Sent from my phone. Please excuse my brevity.