Tidying datasets with multiple sections/headers at variable positions

Question

Context

I am trying to read in and tidy an excel file with multiple headers/sections placed at variable positions. The content of these headers need to

Answer 1

For completeness' sake, here's a base R solution that also depends on the expectation that you can make a vector of the elements of col1 that are not city names and use it for reference:

# make your vector of non-city elements of col1 for reference
types <- c("Diesel","Gasoline","LPG","Electric")

# use that reference vector to flag city names
df$city = ifelse(!df$col1 %in% types, 1, 0)
# use cumsum with that flag to create a group id
df$group = cumsum(df$city) 

# use the split/apply/combine approach, splitting on that group id, restructuring
# each element of the resulting list as desired through lapply, then recombining 
# the results with do.call and rbind
newdf <- do.call(rbind, lapply(split(df, df$group), function(x) {

  data.frame(city = x$col1[1], type = x$col1, value = x$col2, stringsAsFactors = FALSE)[-1,]

}))

Result:

> newdf
       city     type value
1.2 Seattle   Diesel    80
1.3 Seattle Gasoline    NA
1.4 Seattle      LPG    10
1.5 Seattle Electric    10
2.2  Boston   Diesel    65
2.3  Boston Gasoline    25
2.4  Boston Electric    10