*Total 80 pts;
*This workshop is to practice dataset concatenation and transpose;

*Q1. (20pts) Add proper statements in the two data steps below to read the instream
     data properly. Check the provided data descriptions and make sure the created
     variable names are intuitive.
     Hint: when reading instream data using DATALINES statement, if need to specify a
     delimiter other than a blank, add an INFILE statement following the example below:
     INFILE DATALINES DLM=YourDelimiter;
*    The use of this INFILE statement and DLM= option is similar to that when reading
     external data files;

*    Below is an annual GDP data (in million dollars) for selected countries from 2017
     to 2022. Add proper statements to complete the data step;
data GDP;

datalines;
Australia  1220649.3  1291061.7  1368951.8  1382826.1     1557538.5  1809327.4
Canada     1765763.2  1852987.8  1899695    1847838.8     2133084.7  2415839.7
Germany    4386729.2  4576056.5  4840311.8  4815445     5153137.1  5582292.1
Japan 5262255    5344060.9  5404463.3  5358320.7  5599031.8     5895686.8
United Kingdom   3041891.8  3129647.8  3335878.3  3220295.9     3541780.7  3847919.4
United States    19612102.5 20656515.5 21521395   21322949.5     23594030.8 25744108.3
India 8053222.3  8919533.1  9375503.1  8832913.6  10088351.4     11515567.6
;

run;

*    Below is the population for selected countries from 2019 to 2022. A three-letter
     country code is included in addition to the country names. Add proper statements
     to complete the data step;
data Population;

datalines;
Japan JPN   126633000  126261000  125681593  125124989
United Kingdom   GBR   66836327   67081234   67026292   66971395
United States    USA   328329953  331511512  332031554     333287557
Canada     CAN   37601230   38007166   38226498   38929902
Australia  AUS   25334826   25649248   25685412   26005540
Germany    DEU   83092962   83160871   83196078   83797985
India IND   1383112050 1396387127 1407563842 1417173173
China CHN   1407745000 1411100000 1412360000 1412175000
;

run;

*Q2. (20pts)Concatenate the two datasets above, so that for each country, there is one
     observation for GDP amount and another observation for population.
     In the same data step, use proper method to create a charater variable to indicate
     which observations are GDP and which obeservations are population.;


*Q3. (20pts)The final goal is to calculate GDP per capita(in Q4), which is GDP amount
     divided by population for the corresponding year. Utilize the concatenated data
     created in Q2 and restructure it in a way that’s easier to calculate GDP per capita.
     Consider what your desired data structure is and leverage proc transpose to achieve
     it.
     The output data only needs to cover the years when both GDP and population values
     are available.;
    

*Q4. (20pts)Calculate GDP per capita as described above using the data created in Q3.
     Note that in the initial instream data, GDP is recorded in million dollars.
     In the same data step, create a NUMERIC variable called Year to indicate the
     correspoinding year for GPD per capita values;