Databank

Databank Tables

df_tables <- dkstat::dst_get_tables(lang = "en")
knitr::kable(df_tables[1:n_table,])

id	text	unit	updated	firstPeriod	latestPeriod	active	variables
FOLK1A	Population at the first day of the quarter	number	2017-05-11T09:00:00	2008Q1	2017Q2	TRUE	region,sex,age,marital status,time
FOLK1B	Population at the first day of the quarter	number	2017-05-11T09:00:00	2008Q1	2017Q2	TRUE	region,sex,age,citizenship,time
FOLK1C	Population at the first day of the quarter	number	2017-05-11T09:00:00	2008Q1	2017Q2	TRUE	region,sex,age,ancestry,country of origin,time
FOLK1D	Population at the first day of the quarter	number	2017-05-11T09:00:00	2008Q1	2017Q2	TRUE	region,sex,age,citizenship,time
FOLK1E	Population at the first day of the quarter	number	2017-05-11T09:00:00	2008Q1	2017Q2	TRUE	region,sex,age,ancestry,time

## write.table(df_tables, file = "~/Downloads/databank-tables.tsv", sep = "\t", row.names = FALSE)

Getting Data

table <- "camp1"

folk1_meta <- dkstat::dst_meta(table = table, lang = "en")

my_query <-
  list(
    OMRÅDE = "All Denmark",
    NATION1 = "*",
    OVERNAT1 = "Nights stay",
    PERIODE = "Whole year",
    Tid = "*"
  )
df_data <- dkstat::dst_get_data(table = table, query = my_query, lang = "en")
## head(df_data)
## str(df_data)
knitr::kable(df_data[1:n_table, ])

OMRÅDE	NATION1	OVERNAT1	PERIODE	TID	value
All Denmark	Total	Nights stay	Whole year	1992-01-01	13083768
All Denmark	Total	Nights stay	Whole year	1993-01-01	11792034
All Denmark	Total	Nights stay	Whole year	1994-01-01	11955208
All Denmark	Total	Nights stay	Whole year	1995-01-01	12392260
All Denmark	Total	Nights stay	Whole year	1996-01-01	11677936

library(ggplot2)

## table(df_data$NATION1)

## nations <- sample(unique(df_data$NATION1), 5)

df_bottom <-
  df_data %>%
  filter(!NATION1 %in% c("Total", "Denmark", "World outside Denmark")) %>%
  group_by(NATION1) %>%
  summarize(SUM = sum(value)) %>%
  arrange(-SUM) # %>%
  ## head(10)

df_plot <-
  df_data %>%
  filter(!TID == "2017-01-01")
## head(df_data)
## head(df_plot)

df_plot$NATION1 <- factor(df_plot$NATION1,
                          ## levels = rev(as.character(df_bottom$NATION1))
                          levels = as.character(df_bottom$NATION1)
                          )

## number of countries
m <- 5

p <-
  df_plot %>%
  filter(NATION1 %in% df_bottom$NATION1[1:m]) %>%
  ggplot(aes(x = TID, y = value, fill = NATION1)) +
  geom_bar(stat = "identity", color = "black") +
  scale_x_date(name = NULL, expand = c(0,0)) +
  scale_y_continuous(name = "Foreign National Campers in Denmark, Number",
                     expand = c(0,0)) +
  guides(fill = guide_legend(title = NULL)) +
  theme_bw() +
  scale_fill_manual(values = c("#F92672", rep("transparent", m)))
p