I have this list of dataframes. Within the individual dataframes, they all have columns 'country' and '2009' because this is the data I choose to work with. How do I combine all these dataframes by country, using the dataframes' names as the columns of my single dataframe (the result)? I am providing a picture of what my list and the dataframes look like.
The outcome dataframe should have the columns of 'water', 'childMort', 'totalFertility', etc. with 2009 COMPLETE data (no nas or columns with no matching country) but the rows would be the countries like for example:
country water childMort totalFertility ...
Albania 91.4 13.30 1.65
Angola 50.4 120.00 6.16
Afghanistan 48.3 88.00 5.82
I tried using reduce like below:
country2009df %>% reduce(left_join)
but I get an error of
Error in `fn()`:
! join columns must be character vectors.
update: I tried using bind_rows and it gives me the countries, but also '2009' as another column which I do not want and the column names I do want are under column 'name'.
bind_rows(country2009df, .id='name')
name country 2009
1 water Aruba 97.30
2 water Afghanistan 48.30
3 water Angola 50.40
4 water Albania 91.40
5 water Andorra 100.00
