Code
library(dplyr)
library(tidyr)
library(purrr)
library(g2r)
library(DT)
library(myPackage)
data("unemp")
<- unemp %>%
unemp mutate(year = as.character(year)) %>%
::clean_names() %>%
janitorfilter(level == "Commune")
library(dplyr)
library(tidyr)
library(purrr)
library(g2r)
library(DT)
library(myPackage)
data("unemp")
<- unemp %>%
unemp mutate(year = as.character(year)) %>%
::clean_names() %>%
janitorfilter(level == "Commune")
There are 105 communes in the dataset. Below we plot the unemployment rate for 3 communes:
%>%
unemp filter(place_name %in% c("Luxembourg", "Esch-sur-Alzette", "Wiltz")) %>%
g2(data = .) %>%
fig_line(asp(year, unemployment_rate_in_percent, color = place_name))
%>%
unemp ::datatable(filter = "top") DT
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