PowerQuery Puzzle solved with R

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Author: ExcelBI

All files (xlsx with puzzle and R with solution) for each and every puzzle are available on my Github. Enjoy.

Puzzle #157

We are getting long table of logs, and don’t really know what is going on here. But our manager wants to know when data in certain groups and variables changes. And nothing else should stay in table. Tough job, but who else will do it.

Loading libraries and data


input = read_excel("Power Query/PQ_Challenge_157.xlsx", range = "A1:E31")
test  = read_excel("Power Query/PQ_Challenge_157.xlsx", range = "G1:K31") %>%
  mutate(across(everything(), as.character))


log_changes <- function(data) {
  data %>%
    mutate(across(everything(), as.character)) %>%
    group_by(Group) %>%
                  ~if_else(lag(.x) != .x & !is.na(lag(.x)), .x, NA_character_))) %>%

result = log_changes(input) 


identical(result, test)
# [1] TRUE

Wow! Much faster than we was thinking before.

Puzzle #158

I assume that almost all PQ puzzles are about cleaning data. And this time is again what we need to do. We have table with data about several people, but they are looking like different people wrote different parts. Some data are lacking, but we need to make it consistent in shape. And one more thing… we have two levels of column headers.

Load libraries and data


input = read_excel("Power Query/PQ_Challenge_158.xlsx", range = "A1:K5", 
                   col_names = T, .name_repair = "unique") 
test  = read_excel("Power Query/PQ_Challenge_158.xlsx", range = "A10:G17") %>%
  mutate(across(everything(), as.character))


r1 = input %>%
  pivot_longer(cols = -c(1), values_to = "value", names_to = "variable") %>%
  mutate(variable = if_else(str_starts(variable, "D"), variable, NA_character_)) %>%
  fill(variable, .direction = "down") %>%
  group_by(Dept) %>%

headers = r1[[2]][[1]]$value

r2 = r1 %>%
  filter(Dept != "Group") %>%
  unnest(data) %>%
  mutate(headers = headers) %>%
  pivot_wider(names_from = headers, values_from = value) %>%
  filter(!is.na(`Emp ID`)) %>%
  select(Group = Dept, Dept = variable, everything()) %>%


identical(r2, test)
# [1] TRUE

Feel free to comment, share and contact me with advices, questions and your ideas how to improve anything. Contact me on Linkedin if you wish as well.

PowerQuery Puzzle solved with R was originally published in Numbers around us on Medium, where people are continuing the conversation by highlighting and responding to this story.

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