Challenge 10

Sorry for submitting this late!

Use Purrr to Perform Some Data Science Task

Here, I use purrr to compute the z-scores for all variables of the debt dataframe which are numeric.

library(tidyverse)

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.4
✔ forcats   1.0.0     ✔ stringr   1.5.1
✔ ggplot2   3.4.4     ✔ tibble    3.2.1
✔ lubridate 1.9.3     ✔ tidyr     1.3.0
✔ purrr     1.0.2     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(readxl)

read_and_clean <- function(path){
  debt <- read_excel(path)
  debt <- debt %>%
    mutate(`Year and Quarter` = yq(`Year and Quarter`)) %>%
    rename(Date = `Year and Quarter`)
  return(debt)
}
debt <- read_and_clean("challenge_datasets/debt_in_trillions.xlsx")

z_score <- function(vec) {
  if (is.numeric(vec)) {
      mu <- mean(vec)
      s <- sd(vec)
      return((vec - mu) / s)
  }
}
map_dfr(debt, z_score)

# A tibble: 74 × 7
   Mortgage `HE Revolving` `Auto Loan` `Credit Card` `Student Loan` Other Total
      <dbl>          <dbl>       <dbl>         <dbl>          <dbl> <dbl> <dbl>
 1    -2.81        -2.22        -1.24         -0.996          -1.59 2.06  -2.61
 2    -2.70        -2.07        -1.32         -0.923          -1.58 2.25  -2.53
 3    -2.61        -2.00        -1.05         -0.923          -1.57 2.06  -2.43
 4    -2.21        -1.73        -0.967        -0.851          -1.56 1.43  -2.13
 5    -2.05        -1.52        -0.899        -0.894          -1.54 1.38  -2.01
 6    -1.95        -1.21        -0.801        -0.865          -1.53 0.873 -1.91
 7    -1.74        -0.728       -0.766        -0.734          -1.38 0.587 -1.69
 8    -1.62        -0.389       -0.864        -0.574          -1.34 0.869 -1.57
 9    -1.49        -0.114       -0.877        -0.676          -1.30 0.241 -1.48
10    -1.33         0.0965      -0.668        -0.574          -1.27 0.422 -1.31
# ℹ 64 more rows