Excel BI’s Excel Challenge #321 — solved in R

Defining the Puzzle:

Soccer came back to play. According to matches rusult we have to find which matches has biggest difference in goals scored. In task we see question for 3 matches, but in solution we see 4 matches because one difference has ex aequo positions. And I will use dense rank for this.

“List the Top 3 Matches where difference between goals are the maximum and list them in descending order of goal difference.”

Loading Data from Excel:

We need to load data and libraries.

library(tidyverse)
library(data.table)
library(readxl)

input = read_excel(“Teams Max Goal Diff.xlsx”, range = “A1:D11”)
test = read_excel(“Teams Max Goal Diff.xlsx”, range = “F2:G6”)

Approach 1: Tidyverse with purrr

result = input %>%
 separate(Result, into = c(“T1goals”, “T2goals”)) %>%
 mutate(diff = abs(as.numeric(T1goals) — as.numeric(T2goals))) %>%
 arrange(desc(diff)) %>%
 mutate(rank = dense_rank(desc(diff)),
 diff = as.character(diff)) %>%
 filter(rank <= 3) %>%
 select(Match, ‘Goal Diff’ = diff)

Approach 2: Base R

input$T1goals <- as.numeric(sub("-.*", "", input$Result))
input$T2goals <- as.numeric(sub(".*-", "", input$Result))
input$diff <- abs(input$T1goals - input$T2goals)
input <- input[order(-input$diff), ]

dense_rank <- function(x) {
  unique_vals <- unique(x)
  rank_dict <- setNames(seq_along(unique_vals), sort(unique_vals, decreasing = TRUE))
  return(rank_dict[as.character(x)])
}

input$rank <- dense_rank(input$diff)

result_base <- input[input$rank <= 3, c("Match", "diff")]
names(result_base)[names(result_base) == "diff"] <- "Goal Diff"
result_base

Approach 3: data.table

setDT(input) 

input[, c(“T1goals”, “T2goals”) := tstrsplit(Result, “-”, type.convert = TRUE)]
input[, diff := abs(as.numeric(T1goals) — as.numeric(T2goals))]
input <- input[order(-diff)]
input[, rank := frank(-diff, ties.method = “dense”)]
result_dt <- input[rank <= 3, .(Match, `Goal Diff` = as.character(diff))] 

identical(test$Match,result_dt$Match)

Validation:

         
identical(test, result)
#> [1] TRUE

identical(test, result_base %>% mutate(`Goal Diff` = as.character(`Goal Diff`)))
#> [1] TRUE

identical(test$Match,result_dt$Match)
#> [1] TRUE

If you like my publications or have your own ways to solve those puzzles in R, Python or whatever tool you choose, let me know.

Dominant Teams was originally published in Numbers around us on Medium, where people are continuing the conversation by highlighting and responding to this story.