Although this question is very likely to get closed in the coming hours if you dont make your problem clearer, this might get you started at least:
mydf <- scan(textConnection("12376 167827 3454596 9676112 342102 1232103 546102 5645696 96767110 23423119 4577140 45435158 56767138 635435167 35443160 34534166 3213133 2132148 2342130 7656127 43234117 56545130 5645138 56455149"), )
plot(mydf, log="y", type="l") # Gives you an overview of your time serie (with log axis)
gr <- diff(mydf)/mydf[-length(mydf)] # Gives you a growth rate between each of your values.
par(new=TRUE)
plot((1:(length(mydf)-1))+0.5, gr, type="l", # Plots your growth rate
col="red", axes=FALSE, xaxt="n", yaxt="n")
axis(4)
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solved How to identify the virality growth rate in time series data using R? [closed]