SBB StatBank Statistics Norway

Statistics Norway Data

baseURL <- "http://data.ssb.no/api/v0"
## flow <- "OrgsatEksUlonn"
## req_uri <- as.character(ssb_tables$Statistic[ssb_tables$ID==flow])[1]
## flow <- "SnusUtdKj"
req_uri <- "http://data.ssb.no/api/v0/en/table/he/he03/royk/SnusUtdKj"

## req_uri <- file.path(baseURL, path, flow)
bottom_node <- pxweb::get_pxweb_metadata(req_uri)
dims <- pxweb::get_pxweb_dims(bottom_node)
## dims_list <- as.list(rep("*", length(names(dims))))
## names(dims_list) <- names(dims)
dims_list <- lapply(dims, function(x) sample(x$values, min(3, length(x$values))))
pxweb_data <-                           # retrieve data
  pxweb::get_pxweb_data(
           url = req_uri,
           dims = dims_list,
           clean = TRUE)
knitr::kable(pxweb_data[1:10,])

sex	level of education	year	contents	values
Both sexes	Below upper secondary level	2012	Takes snuff daily (per cent)	12
Both sexes	Below upper secondary level	2014	Takes snuff daily (per cent)	14
Both sexes	Below upper secondary level	2015	Takes snuff daily (per cent)	15
Both sexes	Below upper secondary level	2012	Takes snuff occasionally (per cent)	6
Both sexes	Below upper secondary level	2014	Takes snuff occasionally (per cent)	6
Both sexes	Below upper secondary level	2015	Takes snuff occasionally (per cent)	6
Both sexes	Tertiary education	2012	Takes snuff daily (per cent)	7
Both sexes	Tertiary education	2014	Takes snuff daily (per cent)	6
Both sexes	Tertiary education	2015	Takes snuff daily (per cent)	7
Both sexes	Tertiary education	2012	Takes snuff occasionally (per cent)	3

library(ggplot2)

## unique(pxweb_data$`type of activity`)
## unique(pxweb_data$`level of education`)
## dput(unique(pxweb_data$`how often during the last 12 months`))
## str(pxweb_data)
data_plot <- pxweb_data

## data_plot$`how often during the last 12 months` <-
##   factor(data_plot$`how often during the last 12 months`,
##          levels = c(
##            "not at all",
##            "a few times during the last three months or less often", 
##            "every day (by and large)"
##          ))

p <-
  data_plot %>%
  filter(!(sex %in% c("Both sexes"))) %>%
  ## filter(!(`level of education` %in% c("total"))) %>%
  ## filter(observations %in% c("Estimated numbers in thousands")) %>%
  ggplot(aes(x = year, y = values, fill = contents)) +
  ## geom_point() +
  geom_bar(position = "dodge", stat = "identity") +
    ## facet_grid(`level of education` ~ `sex`) +
    facet_grid(sex ~ `level of education`) +
  scale_fill_manual(values = c("#F92672", "black")) +
scale_x_discrete(name = NULL, expand = c(0,0)) +
  scale_y_continuous(name = "Estimated Numbers", expand = c(0,0)) +
  theme_bw() +
  theme(legend.position = "top")
p

## Warning: Removed 1 rows containing missing values (geom_bar).