Functional Programming

Check out this purrr tutorial by Jenny Bryan: https://jennybc.github.io/purrr-tutorial/ls02_map-extraction-advanced.html

Additional content to read up on: https://jennybc.github.io/purrr-tutorial/ls01_map-name-position-shortcuts.html

0. Create a new dataset from iris called iris_lab. Use this for the lab.

iris_lab <- iris

1. Working with the iris_lab data, use mutate and across to change the numeric variables to be rounded with the round function. Take a look with head()- do this for the rest of the questions in which you create an output of data.

iris_lab %>% 
  mutate(across(.cols = !Species, round)) %>%
  head()

##   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1            5           4            1           0  setosa
## 2            5           3            1           0  setosa
## 3            5           3            1           0  setosa
## 4            5           3            2           0  setosa
## 5            5           4            1           0  setosa
## 6            5           4            2           0  setosa

# OR 
iris_lab %>% 
  mutate(across(.cols = where(is.numeric), round)) %>%
  head()

##   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1            5           4            1           0  setosa
## 2            5           3            1           0  setosa
## 3            5           3            1           0  setosa
## 4            5           3            2           0  setosa
## 5            5           4            1           0  setosa
## 6            5           4            2           0  setosa

2. Now do the same thing as question one, but this time set the number of digits for rounding to be 1.

iris_lab %>% 
  mutate(across(.cols = !Species, ~ round(.x, digits = 1))) %>%
  head()

##   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1          5.1         3.5          1.4         0.2  setosa
## 2          4.9         3.0          1.4         0.2  setosa
## 3          4.7         3.2          1.3         0.2  setosa
## 4          4.6         3.1          1.5         0.2  setosa
## 5          5.0         3.6          1.4         0.2  setosa
## 6          5.4         3.9          1.7         0.4  setosa

3. Create a function for adding 2 to a value and dividing by 6. Call the function new_function and use x as the input. Apply this function to the numeric columns of the iris_lab data. Hint: start with function(x){}. Fill in the curly brackets.

new_function <- function(x){(x+2)/6}
iris_lab %>% 
  mutate(across(.cols = !Species, ~ new_function(.x))) %>%
  head()

##   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1     1.183333   0.9166667    0.5666667   0.3666667  setosa
## 2     1.150000   0.8333333    0.5666667   0.3666667  setosa
## 3     1.116667   0.8666667    0.5500000   0.3666667  setosa
## 4     1.100000   0.8500000    0.5833333   0.3666667  setosa
## 5     1.166667   0.9333333    0.5666667   0.3666667  setosa
## 6     1.233333   0.9833333    0.6166667   0.4000000  setosa

4. Now create a function that includes x and y inputs. Call the function div_function and use it to divide x by y and then add 3 to the outcome. Hint: start with function(x, y){}. Fill in the curly brackets.

div_function <- function(x, y){(x/y)+ 3}

5. Use if_all() to check if there are iris flowers with sepal and petal widths and lengths (all the iris_lab numeric variables) greater than 2 centimeters but less than 6 centimeters (which is the unit, if you type in ?iris you can learn more about the data). Hint - use filter. If any are, how many?

iris_lab %>%
filter(if_all(starts_with(c("Petal", "Sepal")), ~.x > 2 & .x < 6))  %>%
  head()

##   Sepal.Length Sepal.Width Petal.Length Petal.Width   Species
## 1          5.8         2.8          5.1         2.4 virginica

6. the function format() with the argument scientific = TRUE can be used to format numbers in scientific notation. For example:

format(10000, scientific = TRUE)

## [1] "1e+04"

Use modify_if to convert numeric columns of iris_lab to be in scientific notation.

iris_lab <- iris_lab %>%
  modify_if(is.numeric, ~ format(.x, scientific = TRUE))

head(iris_lab)

##   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1      5.1e+00     3.5e+00      1.4e+00     2.0e-01  setosa
## 2      4.9e+00     3.0e+00      1.4e+00     2.0e-01  setosa
## 3      4.7e+00     3.2e+00      1.3e+00     2.0e-01  setosa
## 4      4.6e+00     3.1e+00      1.5e+00     2.0e-01  setosa
## 5      5.0e+00     3.6e+00      1.4e+00     2.0e-01  setosa
## 6      5.4e+00     3.9e+00      1.7e+00     4.0e-01  setosa