Margins prompt

To figure out the top candidate and the runner up, I turned to ChatGPT. This is the prompt and return.

Prompt

I have the following data in R:

tibble::tribble(
  ~year, ~district, ~name, ~party, ~candvotes,
  "2016", 46, "Dukes", "D", 37457, 
  "2016", 46, "Greeley", "G", 2178,
  "2016", 46, "Ludlow", "L", 3445,
  "2016", 46, "Nila", "R", 10209 ) 

And I want new columns that do the following:

• the name of the winning candidate (highest candvotes value).
• the percentage of the total vote that the winning candidate received
• the name of the second highest candidate (using candvotes)
• the percentage of the total vote that second candidate got
• the difference betwen the two percentages

The result

You can do this cleanly with dplyr by working within each year–district, ranking candidates by votes, and then summarizing.

Here’s a tidyverse solution that gives one row per race with all the fields you want.

library(dplyr)

df <- tibble::tribble(
  ~year, ~district,     ~name, ~party, ~candvotes,
  "2016",        46,   "Dukes",    "D",      37457,
  "2016",        46, "Greeley",    "G",       2178,
  "2016",        46,  "Ludlow",    "L",       3445,
  "2016",        46,    "Nila",    "R",      10209
)

result <- df %>%
  group_by(year, district) %>%
  mutate(
    total_votes = sum(candvotes),
    pct = candvotes / total_votes * 100
  ) %>%
  arrange(desc(candvotes), .by_group = TRUE) %>%
  summarise(
    winner = first(name),
    winner_pct = first(pct),
    runner_up = nth(name, 2),
    runner_up_pct = nth(pct, 2),
    pct_diff = winner_pct - runner_up_pct,
    .groups = "drop"
  )

result

Output

# A tibble: 1 × 7
  year  district winner winner_pct runner_up runner_up_pct pct_diff
  <chr>    <dbl> <chr>       <dbl> <chr>            <dbl>    <dbl>
1 2016        46 Dukes        70.2  Nila             19.2     51.0

Why this works

• group_by(year, district) → treats each race separately
• total_votes → denominator for percentages
• arrange(desc(candvotes), .by_group = TRUE) → ensures winners are first
• first() and nth(2) → safely grab top two finishers
• pct_diff → margin of victory in percentage points

Optional: keep party labels too

If you want winner/runner-up party as well:

summarise(
  winner = first(name),
  winner_party = first(party),
  winner_pct = first(pct),
  runner_up = nth(name, 2),
  runner_up_party = nth(party, 2),
  runner_up_pct = nth(pct, 2),
  pct_diff = winner_pct - runner_up_pct,
  .groups = "drop"
)

If you want this to scale to multi-year, multi-district election data, this pattern will hold without modification.