Can I use any() and next() to get rid of empty data frames in R?

问题

The following link

if else statement gone bad

suggests not to use the formulation

> any( c(5,6,7) )==0
[1] FALSE

I have been using any() to get rid of empty data frames in for() loops like this:

id <- c(1,2,3,4,5,6)
len <- c(11.25,11.75,12,12,12.5,13.25)
df <- data.frame(id,len)
bin.brks <- c(10,11,12,13,14)

options(warn = -1)   # to turn warnings off

for (m in 1: (length(bin.brks)-1)){
  #subset weights into each bin; empty when m=1
  temp <- df[(df$len > bin.brks[m] & df$len <= bin.brks[m+1]),]
  # deal with empty temp data frame; if the dframe is empty, this is FALSE:
  if (any(temp$len)==FALSE)  next
}

options(warn = 0)   # restore default warnings

Of course, if I don't turn the warnings off, I get this:

Warning message:
In any(temp$var1) : coercing argument of type 'double' to logical

Is there a reason I shouldn't be getting around empty data frames this way? What would be a better way?

I actually was online trying to find a way to get around the error when I found the link that suggested I shouldn't be using any() this way at all.

回答1:

Consider creating a list of dataframes with lapply and use Filter() to filter out empty dataframe elements:

dfList <- lapply(seq_along(bin.brks), function(m)      
  df[(df$len > bin.brks[m] & df$len <= bin.brks[m+1]),])

print(dfList)
# [[1]]
# [1] id  len
# <0 rows> (or 0-length row.names)

# [[2]]
#   id   len
# 1  1 11.25
# 2  2 11.75
# 3  3 12.00
# 4  4 12.00

# [[3]]
#   id  len
# 5  5 12.5

# [[4]]
#   id   len
# 6  6 13.25

# [[5]]
# [1] id  len
# <0 rows> (or 0-length row.names)

dfList <- Filter(function(i) nrow(i) > 0, dfList)

print(dfList)
# [[1]]
#   id   len
# 1  1 11.25
# 2  2 11.75
# 3  3 12.00
# 4  4 12.00

# [[2]]
#   id  len
# 5  5 12.5

# [[3]]
#   id   len
# 6  6 13.25