CODEWITHSUNDEEP
rvectordplyrstringi
ah bon
ah bon

Reputation: 10051

Dynamically generate subset column names for a dataframe using for loop

For the following dataframe df:

df <- structure(list(id = c("M0000607", "M0000609", "M0000612"), `2021-08(actual)` = c(12.6, 
19.2, 8.3), `2021-09(actual)` = c(10.3, 17.3, 6.4), `2021-10(actual)` = c(8.9, 
15.7, 5.3), `2021-11(actual)` = c(7.3, 14.8, 3.1), `2021-12(actual)` = c(6.1, 
14.2, 3.5), `2021-08(pred)` = c(11.65443222, 14.31674997, 7.084180415
), `2021-09(pred)` = c(12.29810914, 17.7143733, 6.057927385), 
    `2021-10(pred)` = c(9.619846116, 15.54553601, 6.525992602
    ), `2021-11(pred)` = c(8.352097939, 13.97318204, 3.164682627
    ), `2021-12(pred)` = c(6.113631596, 14.16243166, 3.288372517
    ), `2021-08(error)` = c(2.082307066, 1.146759554, 0.687406723
    ), `2021-09(error)` = c(1.631350383, 2.753457736, 2.952737781
    ), `2021-10(error)` = c(0.945567783, 4.883250027, 1.215819585
    ), `2021-11(error)` = c(1.998109138, 0.414373304, 0.342072615
    ), `2021-12(error)` = c(0.719846116, 0.154463985, 1.225992602
    )), class = "data.frame", row.names = c(NA, -3L))

Let's say my final objective is to repeatively apply a plotting function to the subsets of df:

plot_fun <- function(...)
  ggplot()

To be more specific, I'll loop each element of year_months <- c('2021-12', '2021-11', '2021-10') and apply plot_fun, so firstly, I need to subset selected columns for each element of year_months.

The logic is: for specific year-month, I will choose: id, actual values of last three months, last one month's error and predicted values. For example, for year_month '2021-12', '2021-11', '2021-10', the subset columns are:

2021-12: selected_cols <- c('id', "2021-10(actual)", "2021-11(actual)", "2021-12(actual)",
                            "2021-12(pred)", "2021-12(error)")

2021-11: selected_cols <- c('id', "2021-09(actual)", "2021-10(actual)", "2021-11(actual)",
                            "2021-11(pred)", "2021-11(error)")

2021-10: selected_cols <- c('id', "2021-08(actual)", "2021-09(actual)", "2021-10(actual)",
                            "2021-12(pred)", "2021-12(error)")

Finaly, I'll run code (pseudo) like this:

for year_month in year_months{
  selected_cols <- ...
  plot_fun(selected_cols)
}

Now my question is how could I write a for loop function to generate column name vector for each of selected year_months?

My trial code (not concise yet) to generate columns for 2021-12:

date_pre_n_months <- function(end_date, x) {
  floor_date(as.Date(end_date) - months(x), 'month')  
}

end_date <- '2021-12-31'
begin_date <- date_pre_n_months(end_date, 3)

year_month <- seq(as.Date("2021-10-31"), as.Date("2021-12-31"), by = "month")
act <- paste0(strftime(year_month, format="%Y-%m"), '(actual)')
pred <- paste0(strftime(end_date, format="%Y-%m"), '(pred)')
error <- paste0(strftime(end_date, format="%Y-%m"), '(error)')

selected_cols <- c('id', act, pred, error)
selected_cols

Out:

"id"              "2021-10(actual)" "2021-12(actual)" "2021-12(actual)" "2021-12(pred)"   "2021-12(error)"

Upvotes: 0

Views: 143

Answers (1)

ekoam
ekoam

Reputation: 8844

You can do it in base R like this with a bit of help from the lubridate package.

year_months <- c('2021-12', '2021-11', '2021-10')  
curr <- lubridate::ym(year_months)
prev <- curr - months(2L)
mapply(function(x, y) {
  df[c(
    "id", 
    format(seq.Date(y, x, by = "month"), "%Y-%m(actual)"), 
    format(x, "%Y-%m(pred)"), 
    format(x, "%Y-%m(error)")
  )]
}, curr, prev, SIMPLIFY = FALSE)

Output

[[1]]
        id 2021-10(actual) 2021-11(actual) 2021-12(actual) 2021-12(pred) 2021-12(error)
1 M0000607             8.9             7.3             6.1      6.113632      0.7198461
2 M0000609            15.7            14.8            14.2     14.162432      0.1544640
3 M0000612             5.3             3.1             3.5      3.288373      1.2259926

[[2]]
        id 2021-09(actual) 2021-10(actual) 2021-11(actual) 2021-11(pred) 2021-11(error)
1 M0000607            10.3             8.9             7.3      8.352098      1.9981091
2 M0000609            17.3            15.7            14.8     13.973182      0.4143733
3 M0000612             6.4             5.3             3.1      3.164683      0.3420726

[[3]]
        id 2021-08(actual) 2021-09(actual) 2021-10(actual) 2021-10(pred) 2021-10(error)
1 M0000607            12.6            10.3             8.9      9.619846      0.9455678
2 M0000609            19.2            17.3            15.7     15.545536      4.8832500
3 M0000612             8.3             6.4             5.3      6.525993      1.2158196

If you want to apply a plot function to the selected dataframe, then

year_months <- c('2021-12', '2021-11', '2021-10')  
curr <- lubridate::ym(year_months)
prev <- curr - months(2L)
plots <- mapply(function(x, y) {
  plot_fun(df[c(
    "id", 
    format(seq.Date(y, x, by = "month"), "%Y-%m(actual)"), 
    format(x, "%Y-%m(pred)"), 
    format(x, "%Y-%m(error)")
  )])
}, curr, prev, SIMPLIFY = FALSE)

gives you a list of (gg)plots.

Update (to also select last year of the current month). However, you need to ensure that the columns you want to select exist in the dataframe; otherwise, you will get an error.

year_months <- c('2021-12', '2021-11', '2021-10')  
curr <- lubridate::ym(year_months)
prev <- curr - months(2L)
mapply(function(x, y) {
  df[c(
    "id", 
    format(c(x - lubridate::years(1L), seq.Date(y, x, by = "month")), "%Y-%m(actual)"),  
    format(x, "%Y-%m(pred)"), 
    format(x, "%Y-%m(error)")
  )]
}, curr, prev, SIMPLIFY = FALSE)

Upvotes: 1

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