comprehendSummary {eList} | R Documentation |
Functions that summarize the results of a Python-style comprehension. These functions
extend those in comprehension
by applying a post-evaluation function to
the results of the loop.
All(..., clust = NULL, na.rm = FALSE) Any(..., clust = NULL, na.rm = FALSE) None(..., clust = NULL, na.rm = FALSE) Sum(..., clust = NULL, na.rm = FALSE) Prod(..., clust = NULL, na.rm = FALSE) Min(..., clust = NULL, na.rm = FALSE) Max(..., clust = NULL, na.rm = FALSE) Mean(..., clust = NULL, na.rm = FALSE, trim = 0) Stats(..., clust = NULL, na.rm = FALSE, trim = 0) Paste(..., clust = NULL, collapse = "")
... |
vectors of any type or a |
clust |
cluster to use for |
na.rm |
logical; should missing values be removed? Defaults to |
trim |
fraction between 0 and 0.5 describing percent of observations to be trimmed from each side for the mean |
collapse |
character describing how the results from |
Single numeric or character value, or a list of results for Stats
All
: Are all results TRUE
?
Any
: Are any results TRUE
?
None
: Are all results FALSE
?
Sum
: Calculate the sum
of results
Prod
: Calculate the prod
of results
Min
: Find the minimum in the result
Max
: Find the maximum in the result
Mean
: Calculate the arithmetic mean of the result
Stats
: Find the 7 number summary (5 number + mean & sd) of the result
Paste
: Collapse the result into a single character
## Calculate the sum of all even numbers to 100 Sum(for (i in seq(2, 100, 2)) i) ## Find the mean Mean(for (i in 1:10) log(i)) ## Combine character values greet <- c("Hello", "World", "Nice", "To", "Meet", "You") val <- Paste(for (i.j in enum(greet)) paste0(i, ": ", j), collapse="\n") cat(val)