Communicating with Data in the Tidyverse
Timo Grossenbacher
Data Journalist
ilo_working_hours
# A tibble: 737 x 3
country year working_hours
<chr> <chr> <dbl>
1 Australia 1980.0 34.57885
2 Canada 1980.0 34.85000
3 Denmark 1980.0 31.89808
4 Finland 1980.0 35.56346
5 France 1980.0 35.42308
6 Iceland 1980.0 35.84615
7 Italy 1980.0 35.74635
8 Japan 1980.0 40.78846
9 Korea, Rep. 1980.0 55.30769
10 Norway 1980.0 30.37885
# ... with 727 more rows
ilo_hourly_compensation
# A tibble: 831 x 3
country year hourly_compensation
<chr> <chr> <dbl>
1 Australia 1980.0 8.44
2 Austria 1980.0 8.87
3 Belgium 1980.0 11.74
4 Canada 1980.0 8.87
5 Denmark 1980.0 10.83
6 Finland 1980.0 8.61
7 France 1980.0 8.90
8 Greece 1980.0 3.72
9 Hong Kong, China 1980.0 1.50
10 Ireland 1980.0 6.44
# ... with 821 more rows
x %>%
inner_join(y, by = "key")
#> # A tibble: 2 × 3
#> key val_x val_y
#> <dbl> <chr> <chr>
#> 1 1 x1 y1
#> 2 2 x2 y2
Communicating with Data in the Tidyverse