Introduction to the data

Communiceren met data in de Tidyverse

Timo Grossenbacher

Data Journalist

This is me

Find examples of data journalism on https://srfdata.github.io

The last step in the Tidyverse process

¹ R for Data Science (http://r4ds.had.co.nz/communicate-intro.html)

What you are going to create

The data you are going to work with

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

The data you are going to work with

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

The inner_join() verb / function

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

¹ R for Data Science (http://r4ds.had.co.nz/relational-data.html#inner-join)

Let's do this!

Communiceren met data in de Tidyverse