(Applied) Data Science

(Applied) Data Science

Please help!

reprex

Goal: create the simplest example possible to illustrate the problem/question, that anyone can run on their own machine

• Can't use data stored on your computer (others won't have that)

• Can't assume options or settings are the same across computers

reprex to the rescue!

Example

Question: How do I sort by a sum and then all component columns?

My use case

dat3
#> # A tibble: 50 x 4
#>    student_id skill_1 skill_2 skill_3
#>         <int>   <int>   <int>   <int>
#>  1       3462       0       0       1
#>  2       3510       1       1       1
#>  3       9717       1       0       1
#>  4       3985       0       1       0
#>  5       2841       1       0       1
#>  6       4370       1       0       1
#>  7       5760       0       0       1
#>  8       7745       0       0       0
#>  9       3756       0       0       1
#> 10       6106       1       0       1
#> # … with 40 more rows

dat4
#> # A tibble: 50 x 5
#>    student_id skill_1 skill_2 skill_3 skill_4
#>         <int>   <int>   <int>   <int>   <int>
#>  1       1472       0       1       1       1
#>  2       7097       0       1       0       1
#>  3       2148       0       1       1       0
#>  4       3036       0       1       0       1
#>  5       3312       1       1       1       1
#>  6       8740       0       1       0       0
#>  7       9649       0       1       1       1
#>  8       2077       0       0       0       1
#>  9       6014       0       1       0       0
#> 10       6657       1       0       0       1
#> # … with 40 more rows

Include data

Question: How do I sort a data frame by total skills and then each component skill?

dat3
#> # A tibble: 50 x 4
#>    student_id skill_1 skill_2 skill_3
#>         <int>   <int>   <int>   <int>
#>  1       3462       0       0       1
#>  2       3510       1       1       1
#>  3       9717       1       0       1
#>  4       3985       0       1       0
#>  5       2841       1       0       1
#>  6       4370       1       0       1
#>  7       5760       0       0       1
#>  8       7745       0       0       0
#>  9       3756       0       0       1
#> 10       6106       1       0       1
#> # … with 40 more rows

Include reproducible example data

library(tidyverse)
ex_data <- tibble(stu     = c(1, 2, 3, 4, 5),
                  skill_1 = c(0, 0, 1, 1, 1),
                  skill_2 = c(1, 1, 0, 0, 0),
                  skill_3 = c(0, 1, 0, 1, 1))
ex_data
#> # A tibble: 5 x 4
#>     stu skill_1 skill_2 skill_3
#>   <dbl>   <dbl>   <dbl>   <dbl>
#> 1     1       0       1       0
#> 2     2       0       1       1
#> 3     3       1       0       0
#> 4     4       1       0       1
#> 5     5       1       0       1

Asking questions

Bad: How do I sort by a sum and then all component columns?

Better: How can I sort a data frame by total skills and then each component skill?

Best: Provide an example of what you want (including the better question), and solutions you've tried.

# What I want:
ex_data %>%
  mutate(total = skill_1 + skill_2 + skill_3) %>%
  arrange(total, desc(skill_1, skill_2, skill_3))
#> # A tibble: 5 x 5
#>     stu skill_1 skill_2 skill_3 total
#>   <dbl>   <dbl>   <dbl>   <dbl> <dbl>
#> 1     3       1       0       0     1
#> 2     1       0       1       0     1
#> 3     4       1       0       1     2
#> 4     5       1       0       1     2
#> 5     2       0       1       1     2

But without specifying each skill individually, because the number of skills may change.

# What I've tried
ex_data %>%
  rowwise() %>%
  mutate(total = sum(c_across(starts_with("skill")))) %>%
  ungroup() %>%
  arrange(total, desc(starts_with("skill")))
#> Error: arrange() failed at implicit mutate() step. 
#> * Problem with `mutate()` input `..2`.
#> x `starts_with()` must be used within a *selecting* function.
#> ℹ See <https://tidyselect.r-lib.org/reference/faq-selection-context.html>.
#> ℹ Input `..2` is `starts_with("skill")`.

Anatomy of a good question

• Brief description of what you're doing

• Reproducible data

• What you've tried

• What you've gotten

• What you want to get

Anatomy of a good question

• Reproducible data

• What you've tried

• What you've gotten

reprex()

The reprex() function from the reprex package will run code, format it nicely, and render the output to your clipboard.

reprex(x = NULL, venue, session_info, style)

reprex()

The reprex() function from the reprex package will run code, format it nicely, and render the output to your clipboard.

reprex(x = NULL, venue, session_info, style)

reprex()

The reprex() function from the reprex package will run code, format it nicely, and render the output to your clipboard.

reprex(x = NULL, venue, session_info, style)

reprex()

The reprex() function from the reprex package will run code, format it nicely, and render the output to your clipboard.

reprex(x = NULL, venue, session_info, style)

reprex()

The reprex() function from the reprex package will run code, format it nicely, and render the output to your clipboard.

reprex(x = NULL, venue, session_info, style)

Answer

ex_data %>%
  rowwise() %>%
  mutate(total = sum(c_across(starts_with("skill")))) %>%
  ungroup() %>%
  arrange(total, across(starts_with("skill"), desc))
#> # A tibble: 5 x 5
#>     stu skill_1 skill_2 skill_3 total
#>   <dbl>   <dbl>   <dbl>   <dbl> <dbl>
#> 1     3       1       0       0     1
#> 2     1       0       1       0     1
#> 3     4       1       0       1     2
#> 4     5       1       0       1     2
#> 5     2       0       1       1     2

Useful resources

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