每行合并/加入 data.tables

Question

I have the following data tables and I would like to make a single data table out of all three.

library(dplyr)
set.seed(123)

dt.Ger <- data.table(date = seq(as.Date('2020-01-01'), by = '1 day', length.out = 365),
                     Germany = rnorm(365, 2, 1), check.names = FALSE)
dt.Aut <- data.table(date = seq(as.Date('2020-01-01'), by = '1 day', length.out = 365),
                     Austria = rnorm(365, 4, 2), check.names = FALSE)
dt.Den <- data.table(date = seq(as.Date('2020-01-01'), by = '1 day', length.out = 365),
                     Denmark = rnorm(365, 3, 1), check.names = FALSE)

dt.Ger <- dt.Ger %>%
  mutate(month = format(date, '%b'), 
         date = format(date, '%d')) %>%
  tidyr::pivot_wider(names_from = date, values_from = Germany)

dt.Aut <- dt.Aut %>%
  mutate(month = format(date, '%b'), 
         date = format(date, '%d')) %>%
  tidyr::pivot_wider(names_from = date, values_from = Austria)

dt.Den <- dt.Den %>%
  mutate(month = format(date, '%b'), 
         date = format(date, '%d')) %>%
  tidyr::pivot_wider(names_from = date, values_from = Denmark)

Now I would like to link all tables together, ie first dt.Ger , then possibly add two empty lines and then append dt.Aut , now add again two empty lines and finally add dt.Den . Ideally, it would be great if Germany were the first headline, then Austria (in the second empty line before dt.Aut ) and then Denmark (in the second empty line before dt.Den ).

So that I only have a single table as a return. This table should look something like this (I only did it with SnippingTool, so it only serves to explain):

EDIT: Using

l <- list(dt.Ger, dt.Aut, dt.Den)
l.result <- rbindlist(l)

yields to:

And I want to get an extra space/line/row (at the red parts) where Germany, Austria and Denmark is written.

Answer 1

I'm still not sure, what you are trying to achive - for me it seems you are better of working with a list of data.tables.

Furthermore, I switched to using dcast instead of pivot_wider so you can drop tidyr / dplyr .

However, here is an approach inserting NA s inbetween the different data.tables using rbindlist :

library(data.table)
set.seed(123)

dt.Ger <- data.table(date = seq(as.Date('2020-01-01'), by = '1 day', length.out = 365),
                     Germany = rnorm(365, 2, 1), check.names = FALSE)
dt.Aut <- data.table(date = seq(as.Date('2020-01-01'), by = '1 day', length.out = 365),
                     Austria = rnorm(365, 4, 2), check.names = FALSE)
dt.Den <- data.table(date = seq(as.Date('2020-01-01'), by = '1 day', length.out = 365),
                     Denmark = rnorm(365, 3, 1), check.names = FALSE)

# or rather date  ~ month?
dt.Ger[, c("month", "date") := list(format(date, '%b'), format(date, '%d'))]
dt.Ger <- dcast(dt.Ger, month ~ date, value.var = "Germany")

dt.Aut[, c("month", "date") := list(format(date, '%b'), format(date, '%d'))]
dt.Aut <- dcast(dt.Aut, month ~ date, value.var = "Austria")

dt.Den[, c("month", "date") := list(format(date, '%b'), format(date, '%d'))]
dt.Den <- dcast(dt.Den, month ~ date, value.var = "Denmark")

# use a list of data.tables:
recommended <- list(Germany = dt.Ger, Austria = dt.Aut, Denmark = dt.Den)

DT <- rbindlist(list(data.table(month = c("", "Germany")), dt.Ger, data.table(month = c("", "Austria")), dt.Aut, data.table(month = c("", "Denmark")), dt.Den), fill = TRUE) # [, V1 := NULL]
DT[,(names(DT)):= lapply(.SD, as.character), .SDcols = names(DT)]
for (j in seq_len(ncol(DT))){
  set(DT, which(is.na(DT[[j]])), j, "")
}

print(DT)