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decs922 R package

This is a package of odds and ends originally created for the class Data Exploration, DECS-922, now DECS-461, at the Kellogg School of Management.

## Loading soln_notes chunk engine

Document production

  • Templates to perform routine setup steps to produce beamer slides and pdf homework assignments. Upon package installation these become automatically available from RStudio’s rmarkdown templates list, as templates named “decs922 Beamer presentation” and “decs922 homework submissions”.

    Note that the decs922 homework submission template contains a mini-tutorial concerning aspects of producing a document with markdown, including examples of cross-referencing of tables and figures.

  • A knitr chunk engine, soln_notes, which allows you to insert optional text within a standalone chunk with the engine soln_notes. When evaluated, the text will be rendered in italic and (by default) preceded by Solution notes:. The goal is to make it easier to create homework solutions. The implementation is currently functional but buggy.

  • nbsp which takes a string as input and returns the string with spaces replaced by non-breaking spaces.

Utility functions

  • translate_datestr parses a string for POSIX date codes and returns documentation for the codes (taken from ?strftime).

    translate_datestr('%Y-%M-%d')
    ##   abbrevs category                           short_description
    ## 1      %d      day Day of the month as decimal number (01-31).
    ## 2      %M     time           Minute as decimal number (00-59).
    ## 3      %Y     year                          Year with century.
    
  • data_summary reports for a data set the number of observations, number of missing values, the class of each variable, and various summary statistics. I view this as pedagogical, as there are many similar functions available, such as summary, psych::describe, etc. Using the built-in dataset iris:

    data_summary(iris)
    ##              Sepal.Length Sepal.Width Petal.Length Petal.Width Species
    ## N                     150         150          150         150     150
    ## Unique                 35          23           43          22       3
    ## Missing                 0           0            0           0       0
    ## Class             numeric     numeric      numeric     numeric  factor
    ## Mean                5.843       3.057        3.758       1.199    <NA>
    ## StdDev              0.828       0.436        1.765       0.762    <NA>
    ## Minimum               4.3           2            1         0.1    <NA>
    ## 5% quantile           4.6       2.345          1.3         0.2    <NA>
    ## 25% quantile          5.1         2.8          1.6         0.3    <NA>
    ## Median                5.8           3         4.35         1.3    <NA>
    ## 75% quantile          6.4         3.3          5.1         1.8    <NA>
    ## 95% quantile        7.255         3.8          6.1         2.3    <NA>
    ## Maximum               7.9         4.4          6.9         2.5    <NA>
    
  • wordle_assist finds 5-letter words that match against excluded letters and positional included letters (a vector named with the letter, with positive values specifying confirmed positions and negative values specifying positional exclusions). The function matches against the length-5 words in the words package. For example, suppose you have played arose, until and chump, and you’ve learned that there is an s in position 1 but not in position 4; there is an h in position 2; and there is an o in position 3. Enter that information like this:

    wordle_assist(no = 'areuntilcump', yes = list(s = c(1, -4), h = 2, o = 3))
    ## [1] "shogs" "shojo" "shook" "shoos" "shows" "showy"
    

    The function returns the remaining possible words.

  • wordle_sub given 1 to 5 letters, return 5-letter words containing those letters, in any order.

    wordle_sub(ltrs='cawk')
    ## [1] "wacke" "wacko" "wacks" "wacky" "whack" "wrack"
    
  • colorkey given a regex, returns matching values from colors(). For example, to find a version of “orange” which does not contain “red” in the color name:

    colorkey(colortext = 'orange', excludetext = 'red')

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