CODEWITHSUNDEEP
rdata.table
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Reputation: 1035

Create a new data.table from sub-tables with the same key columns

I have the data with columns

Time - AgentID -- SimulationID -- discountFactor -- displacement

For each by =.(AgentID,SimulationID,discountFactor), I want to calculate acf(displacement, doPlot=False)$acf, and put its output to new data.table dStat. However, since the size of the output of acf(...)$acf is less than that of Time, I can't directly define a new column, so I need to create a new data.table.

How can I do this?

A portion of my whole data set:

structure(list(Time = c(2.00099550677104, 2.00108827485947, 2.00108827485947, 
2.00108827485947, 2.00108827485947, 2.00108827485947, 2.00108827485947, 
2.00108827485947, 2.00108827485947, 2.00108827485947, 2.00108827485947
), AgentID = c(40L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L), 
    SimulationID = c(2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L), discountFactor = c(0.2, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 
    0.8, 0.8, 0.8, 0.8), displacement = c(-4L, -7L, -1L, 6L, 
    -6L, 6L, -1L, -4L, 0L, 0L, -3L)), row.names = c(NA, -11L), class = c("data.table", 
"data.frame"), .internal.selfref = <pointer: 0x55a2cca3bde0>, sorted = "Time")

Upvotes: 0

Views: 91

Answers (1)

pseudospin
pseudospin

Reputation: 2777

Like this?

dt[, .(acf = c(acf(displacement, plot = FALSE)$acf)), .(AgentID, SimulationID, discountFactor)]

Does't really do much with your sample data as rows are unique on the by.

Upvotes: 1

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