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.
On July 24, 2021 11:41:05 AM PDT, Thomas Subia via R-help
<r-help@r-project.org> wrote:
>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.
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