How to combine Data.Frames with different number of columns

March 20, 2022

I have two data.frames, a and b, in which a‘s columns are a subset of b‘s columns. I want to concatenate a and b and fill with NA where necessary. Is there a function that does this easily?

Here are the data.frames:

> a
                   1979     1980     1981     1982     1983     1984     1985
area_harvested 51.22632 51.22632 41.62139 57.62961 54.42797 54.42797 38.41974
                   1986     1987     1988     1989     1990     1991     1992
area_harvested 61.47159 40.02057 48.02468 38.41974 44.82303 24.01234 22.41152
                   1993     1994     1995     1996     1997     1998     1999
area_harvested 22.41152 16.00823 29.13497 24.01234 25.61316 32.01645 32.01645
                   2000   2001     2002     2003     2004    2005     2006
area_harvested 26.89382 25.293 20.49053 18.24938 18.56954 19.8502 16.64856
                   2007     2008     2009     2010     2011     2012     2013
area_harvested 16.64856 22.73168 16.64856 17.92921 12.48642 10.24526 11.20576
                   2014     2015     2016     2017     2018     2019     2020
area_harvested 11.20576 14.08724 12.80658 12.80658 13.12675 13.76707 12.48642
                   2021
area_harvested 15.04773

> b
             1980    1981     1982     1983     1984     1985     1986     1987
import_p 20.46107 18.7567 16.89872 15.22738 10.74414 11.56598 11.94875 14.14608
             1988     1989     1990     1991     1992     1993    1994     1995
import_p 13.26701 11.94164 10.73588 9.207249 7.090021 8.310488 10.4217 13.34546
             1996     1997     1998     1999     2000     2001     2002    2003
import_p 10.88678 9.163747 8.057007 5.915273 4.326179 4.334085 4.655614 5.28608
             2004     2005     2006     2007     2008     2009     2010
import_p 6.420974 6.571366 6.735536 11.21129 13.33486 11.58492 10.44943
             2011     2012     2013     2014     2015     2016     2017
import_p 11.78057 10.91844 8.063265 8.646034 9.146645 9.594348 9.817362
             2018     2019     2020     2021    2022     2023     2024     2025
import_p 9.047568 10.69488 11.05412 8.536996 10.1282 9.454707 9.531522 9.247525
             2026     2027     2028     2029     2030     2031     2032
import_p 8.999797 8.739282 8.473118 8.205516 7.937321 7.712599 7.435103
             2033     2034     2035     2036    2037     2038     2039     2040
import_p 7.175643 6.912851 6.725843 6.602985 6.44261 6.269521 5.937039 5.869732
             2041     2042     2043     2044    2045     2046     2047     2048
import_p 5.850492 5.648758 5.427907 5.185563 4.94964 4.714463 4.490712 4.260437
             2049     2050     2051     2052 2053
import_p 4.024635 3.827092 3.143441 3.283348   NA