How to extract the first letter of the past, actual and before monthly names in R?-CodePudding

I need to input an column in R using dplyr::mutate that can return to me the first letters of before month actual month next month.

My dataframe is looks like this:

library(dplyr)

Months <- c(

"jan-50",
"feb-50",
"mar-50",
"apr-50",
"may-50",
"jun-50",
"jul-50",
"aug-50",
"sep-50",
"oct-50",
"nov-50",
"dec-50"

)

three_months <- c(

"DJF", # Is the same as D = December J = January and F = February
"JFM", # Is the same as J = January, F = February, M = March and so on...
"FMA",
"MAM",
"AMJ",
"MJJ",
"JJA",
"JAS",
"ASO",
"SON",
"OND",
"NDJ"

)

df <- data.frame(Months, three_months)
df
#Months three_months
#1  jan-50          DJF
#2  feb-50          JFM
#3  mar-50          FMA
#4  apr-50          MAM
#5  may-50          AMJ
#6  jun-50          MJJ
#7  jul-50          JJA
#8  aug-50          JAS
#9  sep-50          ASO
#10 oct-50          SON
#11 nov-50          OND
#12 dec-50          NDJ

df <- df %>%
mutate(three_months = 
       # Formula to initial letters of the past month   actual month   next month
)

How did I can I use this formula to access the past and the next values of each month relative initials letters ?

I only can make for the actual month by using something like:

df <- df%>%
mutate(
   
three_months = abbreviate(Data, 1, strict=TRUE),
three_months = gsub('[1 2]', '', `3 months`),
three_months = toupper(`3 months`) # Shows the time t month initial letter
  
)

Thanks!

CodePudding user response：

I think the easiest way is using a lookup vector:

lookup <- c("jan"= "DJF",
            "feb" = "JFM",
            "mar" = "FMA",
            "apr" = "MAM",
            "may" = "AMJ",
            "jun" = "MJJ",
            "jul" = "JJA",
            "aug" = "JAS",
            "sep" = "ASO",
            "oct" = "SON",
            "nov" = "OND",
            "dec" = "NDJ")

library(dplyr)
library(stringr)

df %>% 
  mutate(three_months = lookup[str_replace(Months, "(\\w )-.*", "\\1")])

This returns

   Months three_months
1  jan-50          DJF
2  feb-50          JFM
3  mar-50          FMA
4  apr-50          MAM
5  may-50          AMJ
6  jun-50          MJJ
7  jul-50          JJA
8  aug-50          JAS
9  sep-50          ASO
10 oct-50          SON
11 nov-50          OND
12 dec-50          NDJ

CodePudding user response：

By seen the @Martin Gal answer, I thought:

df <- df %>%  
mutate(`3 months` = 
       
       case_when( 
         month(Months) ==  1 ~ "DJF",
         month(Months) ==  2 ~ "JFM",    
         month(Months) ==  3 ~ "FMA",
         month(Months) ==  4 ~ "MAM",
         month(Months) ==  5 ~ "AMJ",
         month(Months) ==  6 ~ "MJJ",
         month(Months) ==  7 ~ "JJA",
         month(Months) ==  8 ~ "JAS",
         month(Months) ==  9 ~ "ASO",
         month(Months) ==  10 ~ "SON",
         month(Months) ==  11 ~ "OND",
         month(Months) ==  12 ~ "NDJ",
                               )
     )

As I´m expecting an cyclical monthly time series the case_when here works well too.

CodePudding user response：

We may do this with regex_left_join

library(fuzzyjoin)
regex_left_join(tibble(Months), 
    stack(setNames(three_months, tolower(month.abb))), 
         by = c("Months" = "ind")) %>% 
    select(-ind)
# A tibble: 12 × 2
   Months values
   <chr>  <chr> 
 1 jan-50 DJF   
 2 feb-50 JFM   
 3 mar-50 FMA   
 4 apr-50 MAM   
 5 may-50 AMJ   
 6 jun-50 MJJ   
 7 jul-50 JJA   
 8 aug-50 JAS   
 9 sep-50 ASO   
10 oct-50 SON   
11 nov-50 OND   
12 dec-50 NDJ