> On Sep 7, 2017, at 12:56 PM, David Winsemius <dwinsem...@comcast.net> wrote:
> 
> 
>> On Sep 7, 2017, at 12:21 PM, Miluji Sb <miluj...@gmail.com> wrote:
>> 
>> df is a data frame consisting of one variable (iso3 codes) such as
>> 
>> USA
>> RUS
>> ARG
>> BGD
>> ITA
>> FRA
>> 
>> 
>> Some of these iso3 codes are repeated and I would like the corresponding 
>> continent name, the countrycode package does not seem to distinguish between 
>> North and South America. Thanks.
> 
> Well it does actually: There are two different region codes:
> 
> First load the package that has countryExData. I'm presuming this is:
> 
> library(rworldmap)
> 
>> table(countryExData$EPI_regions)
> 
>   Central and Eastern Europ    East Asia and the Pacific                      
>  Europe 
>                          19                           18                      
>      24 
>   Latin America and Caribbe Middle East and North Africa                North 
> America 
>                          24                           19                      
>       2 
>                  South Asia           Sub-Saharan Africa 
>                           5                           38 
>> table(countryExData$GEO_subregion)
> 
>      Arabian Peninsula Australia + New Zealand               Caribbean 
>                      5                       2                       5 
>         Central Africa            Central Asia          Central Europe 
>                      6                       5                      16 
>         Eastern Africa          Eastern Europe                 Mashriq 
>                      7                       7                       4 
>           Meso America           North America          Northeast Asia 
>                      8                       2                       5 
>        Northern Africa           South America              South Asia 
>                      5                      11                       6 
>        South East Asia           South Pacific         Southern Africa 
>                      8                       3                      10 
>         Western Africa          Western Europe    Western Indian Ocean 
>                     13                      19                       2 
> 
> Then create the described dataframe:
> 
> df<- data.frame(iso3=scan(what="") )
> 1: USA
> 2: RUS
> 3: ARG
> 4: BGD
> 5: ITA
> 6: FRA
> 7: 
> Read 6 items
> 
> 
>> region <- merge(countryExData,df,by.x='ISO3V10',by.y='iso3')$EPI_regions
> 
>> region
> [1] "Latin America and Caribbe" "South Asia"                "Europe"          
>          
> [4] "Europe"                    "Central and Eastern Europ" "North America"   
>  

Looking at that one might wonder about the degree of success. The ordering of 
the matched results was not determined by the order in the second df-object:

 merge(countryExData,df,by.x='ISO3V10',by.y='iso3')
  ISO3V10       Country               EPI_regions  GEO_subregion Population2005
1     ARG     Argentina Latin America and Caribbe  South America        38747.2
2     BGD    Bangladesh                South Asia     South Asia       141822.3
3     FRA        France                    Europe Western Europe        60495.5
4     ITA         Italy                    Europe Western Europe        58092.7
5     RUS        Russia Central and Eastern Europ Eastern Europe       143201.6
6     USA United States             North America  North America       298212.9
  GDP_capita.MRYA landlock   landarea density  EPI ENVHEALTH ECOSYSTEM 
ENVHEALTH.1 AIR_E
1         13652.4        0  2736296.0     1.3 81.8      91.1      72.5        
91.1  87.3
2          1916.2        0   136248.1    95.0 58.0      53.6      62.4        
53.6  95.7
3         28876.5        0   547106.7    17.9 87.8      99.4      76.2        
99.4  95.9
snipped

-- 
David.


> -- 
> David.
> 
>> 
>> Sincerely,
>> 
>> Milu
>> 
>> On Thu, Sep 7, 2017 at 9:00 PM, David Winsemius <dwinsem...@comcast.net> 
>> wrote:
>> 
>>> On Sep 7, 2017, at 11:36 AM, Miluji Sb <miluj...@gmail.com> wrote:
>>> 
>>> Dear all.
>>> 
>>> Is it possible to convert.identify iso3 country names to the seven
>>> continent names?
>>> 
>>> # Asia, Africa, Antarctica, Australia, Europe, South America, and North
>>> America,
>>> 
>>> I have tried the following:
>>> 
>>> ###
>>> region <- merge(countryExData,df,by.x='ISO3V10',by.y='iso3')
>>> 
>>> where df is the name of my dataset with iso3 the identification variable
>>> but there seems to be a a lot of missing values.
>> 
>> Please provide a sufficient amount of the dataframe named `df` to allow a 
>> properly tested response.
>> 
>>> 
>>>      [[alternative HTML version deleted]]
>> 
>> And do read the Posting Guide. This is a plain text mailing list.
>>> 
>>> ______________________________________________
>>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>>> and provide commented, minimal, self-contained, reproducible code.
>> 
>> David Winsemius
>> Alameda, CA, USA
>> 
>> 'Any technology distinguishable from magic is insufficiently advanced.'   
>> -Gehm's Corollary to Clarke's Third Law
>> 
>> 
>> 
>> 
>> 
>> 
> 
> David Winsemius
> Alameda, CA, USA
> 
> 'Any technology distinguishable from magic is insufficiently advanced.'   
> -Gehm's Corollary to Clarke's Third Law
> 
> ______________________________________________
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

David Winsemius
Alameda, CA, USA

'Any technology distinguishable from magic is insufficiently advanced.'   
-Gehm's Corollary to Clarke's Third Law

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