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.

Answer 1

Inf, NA and NaN are matched by !is.finite, for example

a <- c(1, Inf, NA, NaN)
a[!is.finite(a)] <- 0
# a is now [1, 0, 0, 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.

Answer 2

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

Answer 3

Another way to do it is (where df=your dataframe):

is.na(df)<-sapply(df, is.infinite)
df[is.na(df)]<-0

I don't know if this works for zoo objects, but it gets around the problem of is.infinite() only working on vectors.

Answer 4

Using mutate_all in dplyr:

library(dplyr)
fortify.zoo(log_ret) %>% mutate_all(function(x) ifelse(is.infinite(x), 0, x))