Dear all,
In my dataset I have a list of countries as string data, and I have country codes for those countries which are numeric. Below I have an example of this using the dataex command
I would like to merge the string variable "countryname" and the numeric variable "country" into a single numeric variable with the string names as labels.
The two ways I thought of doing this was,
1. Encode countryname as the specific country values.
2. Label country the specific values of countryname.
However I know how to do neither.
Your help would be welcome! Thanks in advance!
In my dataset I have a list of countries as string data, and I have country codes for those countries which are numeric. Below I have an example of this using the dataex command
I would like to merge the string variable "countryname" and the numeric variable "country" into a single numeric variable with the string names as labels.
The two ways I thought of doing this was,
1. Encode countryname as the specific country values.
2. Label country the specific values of countryname.
However I know how to do neither.
Your help would be welcome! Thanks in advance!
Code:
* Example generated by -dataex-. For more info, type help dataex clear input float(year country) str52 countryname float pop 2008 4 "Afghanistan" 27722280 2009 4 "Afghanistan" 28394806 2010 4 "Afghanistan" 29185512 2011 4 "Afghanistan" 30117412 2012 4 "Afghanistan" 31161378 2013 4 "Afghanistan" 32269592 2014 4 "Afghanistan" 33370804 2015 4 "Afghanistan" 34413604 2016 4 "Afghanistan" 35383028 2017 4 "Afghanistan" 36296112 2018 4 "Afghanistan" 37171920 2004 5 "Albania" 3026939 2005 5 "Albania" 3011487 2006 5 "Albania" 2992547 2007 5 "Albania" 2970017 2008 5 "Albania" 2947314 2009 5 "Albania" 2927519 2010 5 "Albania" 2913021 2011 5 "Albania" 2905195 2012 5 "Albania" 2900401 2013 5 "Albania" 2895092 2014 5 "Albania" 2889104 2015 5 "Albania" 2880703 2016 5 "Albania" 2876101 2017 5 "Albania" 2873457 2018 5 "Albania" 2866376 1980 6 "Algeria" 19221660 1981 6 "Algeria" 19824296 1982 6 "Algeria" 20452900 1983 6 "Algeria" 21101876 1984 6 "Algeria" 21763578 1985 6 "Algeria" 22431508 1986 6 "Algeria" 23102386 1987 6 "Algeria" 23774288 1988 6 "Algeria" 24443472 1989 6 "Algeria" 25106192 1990 6 "Algeria" 25758872 1991 6 "Algeria" 26400468 1992 6 "Algeria" 27028330 1993 6 "Algeria" 27635516 1994 6 "Algeria" 28213776 1995 6 "Algeria" 28757788 1996 6 "Algeria" 29266416 1997 6 "Algeria" 29742980 1998 6 "Algeria" 30192750 1999 6 "Algeria" 30623406 2001 6 "Algeria" 31451512 2002 6 "Algeria" 31855110 2003 6 "Algeria" 32264160 2004 6 "Algeria" 32692152 2005 6 "Algeria" 33149720 2006 6 "Algeria" 33641008 2007 6 "Algeria" 34166976 2008 6 "Algeria" 34730604 2009 6 "Algeria" 35333880 2010 6 "Algeria" 35977452 2011 6 "Algeria" 36661440 2012 6 "Algeria" 37383900 2013 6 "Algeria" 38140136 2014 6 "Algeria" 38923688 2015 6 "Algeria" 39728020 2016 6 "Algeria" 40551400 2017 6 "Algeria" 41389176 2018 6 "Algeria" 42228416 1990 8 "Angola" 11848385 1991 8 "Angola" 12248901 1992 8 "Angola" 12657361 1993 8 "Angola" 13075044 1994 8 "Angola" 13503753 1995 8 "Angola" 13945205 2002 8 "Angola" 17519418 2003 8 "Angola" 18121476 2004 8 "Angola" 18758138 2005 8 "Angola" 19433604 2006 8 "Angola" 20149904 2007 8 "Angola" 20905360 2008 8 "Angola" 21695636 2009 8 "Angola" 22514276 2010 8 "Angola" 23356248 2011 8 "Angola" 24220660 2012 8 "Angola" 25107924 2013 8 "Angola" 26015786 2014 8 "Angola" 26941772 2015 8 "Angola" 27884380 2016 8 "Angola" 28842482 2017 8 "Angola" 29816768 2018 8 "Angola" 30809788 1980 11 "Argentina" 27896532 1981 11 "Argentina" 28338514 1982 11 "Argentina" 28794550 1983 11 "Argentina" 29262048 1984 11 "Argentina" 29737096 1985 11 "Argentina" 30216284 1986 11 "Argentina" 30698964 1987 11 "Argentina" 31184412 1988 11 "Argentina" 31668940 1989 11 "Argentina" 32148136 1990 11 "Argentina" 32618648 1991 11 "Argentina" 33079002 1992 11 "Argentina" 33529320 end
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