Quarto and JS libraries

Basic plot interactivity using {g2r}

Code

library(dplyr)
library(tidyr)
library(purrr)
library(g2r)
library(DT)
library(myPackage)

data("unemp")

unemp <- unemp %>%
  mutate(year = as.character(year)) %>% 
  janitor::clean_names() %>%
  filter(level == "Commune")

There are 105 communes in the dataset. Below we plot the unemployment rate for 3 communes:

Code

unemp %>%
  filter(place_name %in% c("Luxembourg", "Esch-sur-Alzette", "Wiltz")) %>%
  g2(data = .) %>% 
  fig_line(asp(year, unemployment_rate_in_percent, color = place_name)) 

Interactive tables with {DT}

Code

unemp %>%
  DT::datatable(filter = "top") 

Show 102550100 entries

Search:

	year	place_name	level	total_employed_population	of_which_wage_earners	of_which_non_wage_earners	unemployed	active_population	unemployment_rate_in_percent
				305 41650	267 37510	30 4140	14 3855	330 45221	2.19907407407407 14.65201465201470
1	2013	Dippach	Commune	1703	1535	168	114	1817	6.27407815079802
2	2013	Garnich	Commune	844	750	94	25	869	2.87686996547756
3	2013	Hobscheid	Commune	1431	1315	116	74	1505	4.91694352159468
4	2013	Kaerjeng	Commune	4094	3800	294	261	4355	5.99311136624569
5	2013	Kehlen	Commune	2146	1874	272	98	2244	4.36720142602496
6	2013	Koerich	Commune	971	858	113	45	1016	4.42913385826772
7	2013	Kopstal	Commune	1218	1029	189	66	1284	5.14018691588785
8	2013	Mamer	Commune	3002	2664	338	207	3209	6.45060766593955
9	2013	Septfontaines	Commune	369	331	38	30	399	7.5187969924812
10	2013	Steinfort	Commune	2024	1837	187	151	2175	6.94252873563218

Showing 1 to 10 of 315 entries

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