time series - Replace -inf, NaN and NA values with zero in a dataset in R

Question

I am trying to run some trading strategies in R. I have downloaded some stock prices and calculated returns. The new return dataset has a number of -inf, NaN, and NA values. I am reproducing a row of the dataset (log_ret). Its a zoo dataset.

library(zoo)
log_ret <- structure(
  c(0.234,-0.012,-Inf,NaN,0.454,Inf), .Dim = c(1L, 6L), 
  .Dimnames = list(NULL, c("x", "y", "z", "s", "p", "t")),
  index = structure(12784, class = "Date"),
  class = "zoo"
)

               x      y    z   s     p   t
2005-01-01 0.234 -0.012 -Inf NaN 0.454 Inf

How can I replace these unwanted values with 0?

Answer 1

As per ?zoo:

Subscripting by a zoo object whose data contains logical values is undefined.

So you need to wrap the subsetting in a which call:

log_ret[which(!is.finite(log_ret))] <- 0
log_ret
               x      y z s     p t
2005-01-01 0.234 -0.012 0 0 0.454 0