# Create a data frame
df <- tibble::tibble(
a = rnorm(10),
b = rnorm(10),
c = rnorm(10),
d = rnorm(10)
)
#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$b, na.rm = TRUE) - min(df$a, 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 0.265 0.421 0.895 1
## 2 0.614 0.639 0.961 0
## 3 0.582 0.428 0.287 0.640
## 4 0.0873 0.692 0 0.0444
## 5 0.0726 1.03 0.807 0.0678
## 6 0.529 1.30 0.194 0.290
## 7 0 0.578 0.415 0.101
## 8 0.495 0.467 0.372 0.240
## 9 0.252 0 1 0.269
## 10 1 0.111 0.564 0.525
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 0.265 0.324 0.895 1
## 2 0.614 0.492 0.961 0
## 3 0.582 0.329 0.287 0.640
## 4 0.0873 0.533 0 0.0444
## 5 0.0726 0.791 0.807 0.0678
## 6 0.529 1 0.194 0.290
## 7 0 0.445 0.415 0.101
## 8 0.495 0.359 0.372 0.240
## 9 0.252 0 1 0.269
## 10 1 0.0852 0.564 0.525
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")
print(x)
}
}
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 = 0.1)
## [1] 6
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 Functions