# Create a data frame
df <- tibble::tibble(
a = rnorm(10),
b = rnorm(10),
c = rnorm(10),
d = rnorm(10),
)
set.seed(1234)
# Rescale each column
df$a <- (df$a - min(df$a, na.rm = TRUE)) /
(max(df$a, na.rm = TRUE) - min(df$a, na.rm = TRUE))
df$b <- (df$b - min(df$b, na.rm = TRUE)) /
(max(df$b, na.rm = TRUE) - min(df$b, na.rm = TRUE))
df$c <- (df$c - min(df$c, na.rm = TRUE)) /
(max(df$c, na.rm = TRUE) - min(df$c, na.rm = TRUE))
df$d <- (df$d - min(df$d, na.rm = TRUE)) /
(max(df$d, na.rm = TRUE) - min(df$d, na.rm = TRUE))
df
## # A tibble: 10 × 4
## a b c d
## <dbl> <dbl> <dbl> <dbl>
## 1 0.336 0 0.614 1
## 2 0.230 0.876 0.376 0.0865
## 3 0 1 0.0713 0
## 4 0.321 0.781 0.265 0.904
## 5 0.254 0.477 0.399 0.576
## 6 0.523 0.223 0.332 0.863
## 7 0.392 0.635 0 0.656
## 8 0.0928 0.452 0.605 0.0924
## 9 0.415 0.764 1 0.378
## 10 1 0.355 0.845 0.137
rescale <- function(x) {
# body
x <- (x - min(x, na.rm = TRUE)) /
(max(x, na.rm = TRUE) - min(x, na.rm = TRUE))
# return values
return(x)
}
df$a <- rescale(df$a)
df$b <- rescale(df$b)
df$c <- rescale(df$c)
df$d <- rescale(df$d)
df
## # A tibble: 10 × 4
## a b c d
## <dbl> <dbl> <dbl> <dbl>
## 1 0.336 0 0.614 1
## 2 0.230 0.876 0.376 0.0865
## 3 0 1 0.0713 0
## 4 0.321 0.781 0.265 0.904
## 5 0.254 0.477 0.399 0.576
## 6 0.523 0.223 0.332 0.863
## 7 0.392 0.635 0 0.656
## 8 0.0928 0.452 0.605 0.0924
## 9 0.415 0.764 1 0.378
## 10 1 0.355 0.845 0.137
detect_sign <- function(x) {
if(x> 0) {
message("Value is positive")
print(x)
} else if(x == 0) {
warning("Value is not positive, but it can be accepted")
print(x)
} else {
stop("Value is negative, the function must stop")
}
}
3 %>% detect_sign()
## Value is positive
## [1] 3
0 %>% detect_sign()
## Warning in detect_sign(.): Value is not positive, but it can be accepted
## [1] 0
# -1 %>% detect_sign()
?mean
## starting httpd help server ... done
x <- c(1:10, 100, NA)
x
## [1] 1 2 3 4 5 6 7 8 9 10 100 NA
x %>% mean()
## [1] NA
x %>% mean(na.rm = TRUE)
## [1] 14.09091
x %>% mean(na.rm = TRUE, trim = 0.01)
## [1] 14.09091
mean_remove_na <- function(x, na.rm = TRUE, ...) {
avg <- mean(x, na.rm = na.rm, ...)
return(avg)
}
x %>% mean_remove_na()
## [1] 14.09091
x %>% mean_remove_na(na.rm = FALSE)
## [1] NA
x %>% mean_remove_na(trim = 0.1)
## [1] 6
Two types of function
one that takes a vector as the input another that takes a data frame as the input