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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?
I don't know too much about manipulating zoo
objects, but for the example above
log_ret[1, !is.finite(log_ret)] <- 0
works. In your actual data you will have to loop over all rows. There might be a zoo
-specific way of doing this.
Edit: The zoo-specific way is log_ret[which(!is.finite(log_ret))] <- 0
.
–
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
–
–
–
Since the lifecycle for mutate_all
has been superseded by the use of across
:
library(dplyr)
fortify.zoo(log_ret) %>% mutate(across(.cols = everything(), ~ ifelse(is.infinite(.x), 0, .x)))
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