df (df.nbl.win.2) contains country, yr1, y2 and yr3. Helper / Workhorse fn (fn_get_rank) takes country and year, returning rank. Using pmap I need to rename cols for proper mapping in pmap.

pmap-v1.r

# -------------------
# HELPER FUNCTION 
# -------------------
# fn to search rank
# INPUT: year (integer)
# OUTPUT: rank (integer)
# SRC: 
# http://adv-r.had.co.nz/Functions.html
# https://cran.r-project.org/web/packages/ArgumentCheck/vignettes/ArgumentChecking.html

# fn_get_rank = function (c.country = "finland", i.search.year = 2008) # for testing
fn_get_rank = function (c.country, i.search.year)
{
  print("entering fn")
  
  # if input args are missing
  # SRC: 
  # https://www.r-bloggers.com/programming-with-r-%E2%80%93-checking-function-arguments/
  
  if (missing(c.country))
    stop("Need to specify country for calculations.")
  
  if (missing(i.search.year))
    stop("Need to specify year for calculations.")
  
  if (!is.character(c.country))
    stop("Country should be character.")
  
  if (!is.numeric(i.search.year))
    stop("Year should be numeric.")
  
  # search the year in df.1 
  # if found return corresponding rank
  # else return NA
  i.flag =     
    df.1 %>%
    filter(year == i.search.year & country == c.country) %>%
    count() %>%
    unlist(use.names = FALSE) # to convert df into a vector **1
  
  # src: for **1
  # http://stackoverflow.com/questions/21618423/extract-a-dplyr-tbl-column-as-a-vector
  
  #str(i.flag)
  #print(i.flag)
  
  if (i.flag == 1)
  {
    return(
      df.1 %>%
        filter(year == i.search.year & country == c.country) %>%
        select(rank) %>%
        unlist(use.names = FALSE)
    )
  }
  else
  {
    return(NA)
  }
  
  
} # end fn_get_rank

# -------------------
# dput the data structure / df used below
# -------------------
# > dput(df.nbl.win.1)
structure(list(c.country = c("finland", "usa", "china", "liberia", 
"yemen", "cross-national", "cross-national", "india", "pakistan", 
"tunisia", "colombia"), i.search.year = c(2008L, 2009L, 2010L, 
2011L, 2011L, 2012L, 2013L, 2014L, 2014L, 2015L, 2016L)), class = "data.frame", row.names = c(NA, 
-11L), .Names = c("c.country", "i.search.year"))

# -------------------
# ACTUAL CODE FOLLOWS
# -------------------

# Naming cols is necessary
# https://github.com/hadley/purrr/issues/203
names(df.nbl.win.1) = c("c.country", "i.search.year")

# extending the df to include year2 and year3, post winning the medal
df.nbl.win.2 = 
  df.nbl.win.1 %>%
  group_by(c.country) %>%
  mutate(year2 = i.search.year + 1, 
         year3 = i.search.year + 2) %>%
  ungroup()

# mapping medal year >> ITERATION 1
df.nbl.win.3$rank.in.nbl.yr = 
  df.nbl.win.3 %>%
  select(c.country,i.search.year) %>%
  pmap(fn_get_rank) %>%
  unlist()

# mapping medal year + 1 >> ITERATION 2
df.nbl.win.4 = 
  df.nbl.win.3 %>%
  # rename cols for pmap 
  rename(year1=i.search.year) %>% #new.name=old.name
  rename(i.search.year=year2) 
  
df.nbl.win.4$nbl.yr1 = 
  df.nbl.win.4 %>%
  select(c.country,i.search.year) %>%
  pmap(fn_get_rank) %>%
  unlist()

# mapping medal year + 2 >> ITERATION 3
df.nbl.win.4 = 
  df.nbl.win.4 %>%
  # rename cols for pmap
  rename(year2=i.search.year) %>%
  rename(i.search.year=year3) 
  

df.nbl.win.4$nbl.yr2 = 
  df.nbl.win.4 %>%
  select(c.country,i.search.year) %>%
  pmap(fn_get_rank) %>%
  unlist()

df.nbl.win.4 = 
  df.nbl.win.4 %>%
  # rename cols for pmap
  rename(year3=i.search.year)

df.nbl.win.4